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Near infrared spectroscopy (NIRS) is a non-invasive method for monitoring hemoglobin oxygen saturation within the microvessels. It is therefore also sometimes (erroneously) referred to as a measure of tissue oxygenation. By using self-adhesive optodes on the body surface, measurements can be taken in tissues below the skin up to a depth of 3–4 cm. The near infrared light (unlike visible light) even penetrates bone tissue, allowing measurement of regional cerebral oxygenation (SrcO2). There are numerous devices using NIRS technology available on the market, and the main applications for use include monitoring of SrcO2 during cardiothoracic and vascular (particularly carotid artery) surgery, as well as non-cardiac surgery that is performed in the sitting or so-called beach chair position [1]. Another widespread use is the assessment of SrcO2 in neonates and preterm infants [2]. Furthermore, there have been attempts to use peripheral tissue oxygenation (SptO2) measurements by NIRS for guiding therapy and predicting outcome in emergency medicine (both pre-hospital and emergency room use) and in the perioperative setting [3]. Finally, the ability to measure SptO2 at different sites [4] raised interest in researchers to look at physiological changes, e.g. during exercise, in musculature of the leg or arm. For this, a special provocation test (the vascular occlusion test (VOT) by inflating a tourniquet proximal to the measurement site) has been developed. The VOT looks at the rate of deoxygenation during ischemia (vascular occlusion), which is considered as a measure of muscle and mitochondrial oxygen consumption, and at the rate of reoxygenation during reperfusion, reflecting the reactivity of the microcirculation [5]. The Journal of Clinical Monitoring and Computing (JCMC) has become an ideal platform for publishing NIRS-related research, as reflected by an increasing number of articles published in the recent years. This article will review two papers on peripheral (SptO2) and two papers on cerebral hemoglobin oxygen saturation (SrcO2) published last year in the JCMC.
Tissue perfusion monitoring is increasingly being employed clinically in a non-invasive fashion. In this end-of-year summary of the Journal of Clinical Monitoring and Computing, we take a closer look at the papers published recently on this subject in the journal. Most of these papers focus on monitoring cerebral perfusion (and associated hemodynamics), using either transcranial doppler measurements or near-infrared spectroscopy. Given the importance of cerebral autoregulation in the analyses performed in most of the studies discussed here, this end-of-year summary also includes a short description of cerebral hemodynamic physiology and its autoregulation. Finally, we review articles on somatic tissue oxygenation and its possible association with outcome.
The microcirculation is the ultimate goal of hemodynamic optimization in the perioperative and critical care setting. In this fourth end-of-year summary of the Journal of Clinical Monitoring and Computing on this topic, we take a closer look at papers published in the last 2 years that focus on this important aspect. The majority of these papers investigated the use of either cerebral or peripheral tissue oxygen saturation, derived non-invasively using near infrared spectroscopy (NIRS). In some of these studies, the microcirculation was "provocated" by inducing short-term tissue hypoxia, allowing the assessment of functional microvascular reserve. Additionally, studies on technical differences between NIRS monitors are summarized, as well as studies investigating the feasibility of NIRS monitoring, mainly in the pediatric patient population. Last but not least, novel monitoring tools allow assessing oxygenation at a (sub)cellular level, and those papers incorporating these techniques are also reviewed here.
Last year we started this series of end of year summaries of papers published in the 2014 issues of the Journal Of Clinical Monitoring And Computing with a review on near infrared spectroscopy (Scheeren et al. in J Clin Monit Comput 29(2):217-220, 2015). This year we will broaden the scope and include papers published in the field of tissue oxygenation and microcirculation, or a combination of both entities. We present some promising new technologies that might enable a deeper insight into the (patho)physiology of certain diseases such as sepsis, but also in healthy volunteers. These may help researchers and clinicians to evaluate both tissue oxygenation and microcirculation beyond macro-hemodynamic measurements usually available at the bedside.
Hemodynamic management is a mainstay of patient care in the operating room and intensive care unit (ICU). In order to optimize patient treatment, researchers investigate monitoring technologies, cardiovascular (patho-) physiology, and hemodynamic treatment strategies. The Journal of Clinical Monitoring and Computing (JCMC) is a well-established and recognized platform for publishing research in this field. In this review, we highlight recent advancements and summarize selected papers published in the JCMC in 2018 related to hemodynamic monitoring and management.
and cerebral autoregulation published in the Journal of Clinical Monitoring and Computing in 2016.
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PRACTICE advisories are systematically developed reports that are intended to assist decision making in areas of patient care. Advisories provide a synthesis and analysis of expert opinion, clinical feasibility data, open forum commentary, and consensus surveys. Advisories are not intended as standards, guidelines, or absolute requirements. They may be adopted, modified, or rejected according to clinical needs and constraints.The use of practice advisories cannot guarantee any specific outcome. Practice advisories summarize the state of the literature and report opinions derived from a synthesis of task force members, expert consultants, open forums, and public commentary. Practice advisories are not supported by scientific literature to the same degree as are standards or guidelines because sufficient numbers of adequately controlled studies are lacking. Practice advisories are subject to periodic revision as warranted by the evolution of medical knowledge, technology, and practice.Intraoperative awareness under general anesthesia is a rare occurrence, with a reported incidence of 0.1–0.2%.1–4Significant psychological sequelae (e.g. , post–traumatic stress disorder) may occur after an episode of intraoperative awareness, and affected patients may remain severely disabled for extended periods of time.5However, in some circumstances, intraoperative awareness may be unavoidable to achieve other critically important anesthetic goals.The following terms or concepts discussed in this Advisory include: consciousness, general anesthesia, depth of anesthesia or depth of hypnosis, recall, amnesia, intraoperative awareness, and brain function monitors. Consistent definitions for these terms are not available in the literature. For purposes of this Advisory, these terms are operationally defined or identified as follows:Consciousness is a state in which a patient is able to process information from his or her surroundings. Consciousness is assessed by observing a patient’s purposeful responses to various stimuli. Identifiers of purposeful responses include organized movements following voice commands or noxious/painful stimuli.*For example, opening of the eyes is one of several possible identifiers or markers of consciousness. Purposeful responses may be absent when paralysis is present as a consequence of neurologic disease or the administration of a neuromuscular blocking drug.General anesthesia is defined as a drug-induced loss of consciousness during which patients are not arousable, even by painful stimulation.†The ability to maintain ventilatory function independently is often impaired. Patients often require assistance in maintaining a patent airway, and positive-pressure ventilation may be required because of depressed spontaneous ventilation or drug-induced depression of neuromuscular function. Cardiovascular function may be impaired.Depth of anesthesia or depth of hypnosis refers to a continuum of progressive central nervous system depression and decreased responsiveness to stimulation.For the purpose of this Advisory, recall is the patient’s ability to retrieve stored memories. Recall is assessed by a patient’s report of previous events, in particular, events that occurred during general anesthesia. Explicit memory is assessed by the patient’s ability to recall specific events that took place during general anesthesia. Implicit memory is assessed by changes in performance or behavior without the ability to recall specific events that took place during general anesthesia that led to those changes.6A report of recall may be spontaneous or it may only be elicited in a structured interview or questionnaire. This Advisory does not address implicit memory.Amnesia is the absence of recall. Many anesthetic drugs produce amnesia at concentrations well below those necessary for suppression of consciousness. Anterograde amnesia is intended when a drug with amnestic properties is administered before induction of anesthesia. Retrograde amnesia is intended when a drug such as a benzodiazepine is administered after an event that may have caused or been associated with intraoperative consciousness in the hope that it will suppress memory formation and “rescue” from recall.Intraoperative awareness occurs when a patient becomes conscious during a procedure performed under general anesthesia and subsequently has recall of these events. For the purpose of this Advisory, recall is limited to explicit memory and does not include the time before general anesthesia is fully induced or the time of emergence from general anesthesia, when arousal and return of consciousness are intended. Dreaming is not considered intraoperative awareness.Brain function monitors are devices that record or process brain electrical activity and convert these signals mathematically into a continuous measure typically scaled from 0 to 100. In addition to monitoring spontaneous cortical electrical activity (electroencephalogram [EEG]), these devices may also record and process evoked cortical and subcortical activity (auditory evoked potentials [AEPs]) as well as electromyographic (EMG) activity from scalp muscles. For the purpose of this Advisory, only monitors purported to measure depth of anesthesia or hypnosis will be considered. Other, non-EEG, non-AEP, non-EMG devices are also available but are not addressed by this Advisory.Intraoperative awareness under general anesthesia is an important clinical problem that clearly is within the foundation of training and continuing medical education in anesthesiology. The purposes of this Advisory are to identify risk factors that may be associated with intraoperative awareness, provide decision tools that may enable the clinician to reduce the frequency of unintended intraoperative awareness, stimulate the pursuit and evaluation of strategies that may prevent or reduce the frequency of intraoperative awareness, and provide guidance for the intraoperative use of brain function monitors as they relate to intraoperative awareness.This Advisory focuses on the perioperative treatment of patients who are undergoing a procedure during which general anesthesia is administered. This Advisory is not intended for the perioperative management of minimal, moderate, or deep sedation in the operating room or intensive care unit; regional or local anesthesia without general anesthesia; monitored anesthesia of patients or those undergoing in after the administration of a neuromuscular or intraoperative (e.g. , for the purposes of intraoperative neurologic In this Advisory is not intended to address the perioperative treatment of Advisory is intended for use by other who the administration of general anesthesia, and other who general anesthesia. The Advisory may also as a for other and who are in the perioperative management of patients general of this of to and the available scientific literature on intraoperative awareness, expert consensus and public opinion, and a practice The is of from various areas of the an from The and from the on Practice the to the because of or in the medical of and the of practice The include but are not limited to with or in the of of the of from or a in a or brain function these have a in the use of such monitors. may also have from or have a in other such as or of that may be affected by the use of brain function monitors. The not for to such because they and to present of in from consultants, of who knowledge, in intraoperative awareness and brain function monitors. or is in in some on or by a or brain function monitors. of the of from or a in a or brain function monitors. also may have from or have a in other that may be affected by the use of brain function monitors. The not for to such because they and to present of a the consensus on the for of perioperative for the of intraoperative they in to this who or in intraoperative awareness and who or in (e.g. , in and to in on the of various perioperative management strategies and to and on a of the Advisory developed by the opinions from a of of the the open at and anesthesia to on the concepts of this available information to consensus within the on the available for on the and to considered by the in the advisories are developed by a to that of an practice a and evaluation of the literature. practice advisories the of a sufficient of adequately controlled studies to of with such as from reports and other studies are considered during the of the This literature often the of of clinical with a practice information is from and of the The following terms responses for any are on a from to with a of responses are on as of of the responses are of of the responses are or and of of the responses are or other or of at of the of of responses are or and of of responses are information is from open forum and other and public The in this a of the of clinical and evaluation a , medical patient or a patients at risk for intraoperative awareness (e.g. , of and patients of the of intraoperative studies and reports that patient may be associated with intraoperative awareness, and drug or studies and reports that (e.g. , well as anesthetic (e.g. , anesthetic with or without the of be associated with an risk of intraoperative studies that the clinical of the patient before of the of intraoperative and that a evaluation may be in patients at risk for intraoperative awareness In they that a evaluation to identify patients at risk of intraoperative awareness include of a patient’s medical a and a patient or They that patient that may place a patient at risk for intraoperative awareness include use or limited and of or The and the that a of intraoperative awareness may place a patient at The and the are patients be of the of intraoperative The and that only patients considered to be at risk of intraoperative awareness be of the of intraoperative the and the that the patient of the risk of intraoperative awareness the risk of intraoperative that some of the evaluation may be in a patient at risk for evaluation a of a patient’s medical for previous of awareness or other risk a patient interview to of or previous with anesthesia, and a risk factors to for patients undergoing general anesthesia include use or (e.g. , a of awareness, a of or patients of and anesthetic in the of use of during the of general anesthesia, anesthesia, the use of anesthesia, of or and limited The consensus of the is that patients the clinician to be at risk of intraoperative awareness be of the of intraoperative awareness when the of anesthesia to the of intraoperative awareness include the of anesthesia and the administration of the of anesthesia is some of intraoperative awareness have from concentrations of or drug drug clinical the of the administration of as an anesthetic during under anesthesia and reported a frequency of intraoperative awareness in the with the clinical amnesia by as after administration of but before induction of general anesthesia. these studies reported recall in patients administered the of consciousness during general anesthesia and intraoperative awareness not and that the of anesthesia (e.g. , be to reduce the risk of intraoperative The and the are that a benzodiazepine or be as a of the anesthetic to reduce the risk of intraoperative awareness for The that a benzodiazepine or be for patients of patients undergoing and patients undergoing They are patients undergoing and anesthesia. The that a benzodiazepine or be for patients of and patients undergoing and anesthesia. They are patients undergoing intraoperative awareness may be caused by or the that be to a for anesthesia and to that the anesthetic drugs and will be be extended to include of the of and The consensus is that the decision to a benzodiazepine be on a for patients (e.g. , patients of The that emergence may the use of awareness cannot be during the intraoperative of general anesthesia, because the recall of awareness only be by information from the the intraoperative monitoring addressed by this Advisory is the use of clinical monitoring or brain function monitors the of intraoperative of literature during the and process not address these or monitors reduce the frequency of intraoperative studies that report intraoperative or from monitoring This not the of an on awareness, often reported or that occurred at during the perioperative with the of or in the depth of anesthesia. reported from this literature are literature for is in the following clinical studies (e.g. , studies (e.g. , of with concentrations of drugs or with in to reports of monitored at during a and reports of or unintended or during a monitoring studies often report a measure of continuous (e.g. , the and anesthetic drug include a that a measure of well a or clinical (e.g. , to of an and a clinical a of a to the clinical to intraoperative consciousness are for to responses or and monitoring include well as the anesthetic clinical or other studies that the of clinical or monitoring on the incidence of intraoperative studies reported from to for the or purposeful and for depth of reported a to and memory when continuous of as the induction for from to for a state from an state and from to for an state from emergence after anesthesia , for from to for a state from an state and from to for of and reported during various intraoperative reported of as before induction or at during at emergence or of and during reported as before induction or at during at emergence or of and during has been reported to occur in the absence of or and that clinical (e.g. , for purposeful or are and be to intraoperative consciousness. In the and that monitoring (e.g. , anesthetic are and be to intraoperative of the devices to brain electrical activity for the purpose of anesthetic record activity from on the be into those that process spontaneous and electromyographic activity and those that evoked responses to and of the to the various are to the derived from the or to a often to as an typically scaled 0 and 100. This the of clinical of consciousness with a of associated with the state and of 0 with an absent may be and in the public or of the various to may be intended to and are an important of the in electromyographic activity from scalp be considered an from the of it may be an important of of electromyographic activity to from and may of For this some monitors provide information on the of electromyographic The is a that a of into an of is available as a or under from in by various anesthesia the several derived from the time frequency are into a of are scaled from 0 to with specific (e.g. , reported to a of consciousness under general anesthesia. The factors for the various in the that the derived from a of The for the of activity by to the as the changes with concentrations of various in a in have available and as and to suppress have been of the and have been controlled have with anesthetic administration clinical practice without In one that patients at risk of intraoperative awareness, explicit recall occurred in of patients when monitors and in of patients by clinical practice , the to the monitoring with clinical during and reported one episode of recall in the clinical with in the other to or opening and of anesthetic drugs with the use of of the use of monitoring a of explicit recall in of the patients of the to the incidence of awareness with recall during general anesthesia and to associated with intraoperative awareness events reported when of with when not of studies reported on in the care and anesthetic use patients monitored with with patients not monitored with studies reported for from to for loss of after induction with or without and from to for reported a of for from electrical of have been reported during various intraoperative of as before induction or at or after during at emergence or of and during reports that intraoperative events to of anesthetic produce changes in (e.g. , or of anesthesia drug reports that intraoperative events (e.g. , administration of of or patient or may with reports that reported patients intraoperative awareness monitored an depth of other reports that patient may the or of a a from a The for of in the as in the is in the public and have been is of absolute such as the or the frequency of the The available time of and reports is an from 0 to the frequency from to the cortical state of the is an from 0 to a frequency from to the and will also to the electromyographic activity from clinical or other studies that the of monitoring on the incidence of intraoperative clinical reported to to and of anesthetic drugs with the use of studies report the following for loss of for for the following are for and for of and as before induction or and during and and at emergence or of and The is derived from a system developed for the of the associated with various of and the the according to the following anesthesia with deep anesthesia with The system a of in a of possible and the of the the has been into a the scaled from 0 to with the of a to the clinical or other studies that the of monitoring on the incidence of intraoperative has the use of controlled anesthetic administration and a time in the , after of for from to for loss of after induction with with an and from to for are as after induction of and at emergence or of state The is derived from a The of the is on the that are changes in of at loss and return of consciousness. The has a of with of consciousness or of to and The analysis on of derived after of the and to be to changes in the of clinical or other studies that the of monitoring on the incidence of intraoperative reported a of for to with a of and of reported a of the with are as before induction or during at emergence or of and during The a from a of The is on a analysis of activity in the 0 to and to frequency and a suppression are on the to the which is on a of and clinical or other studies that the of monitoring on the incidence of intraoperative that reported a of to be of a loss of consciousness in of The is a that a and a scaled from 0 to 100. In it also suppression and a measure of electromyographic activity literature that the of the on the incidence of intraoperative evoked potentials are the electrical responses of the the and the to The of on have been the is to cortical as the with concentrations of and The to anesthetic concentrations is and decreased of the various signals are from the spontaneous time have in an that record and a of from a analysis of the the an that a of anesthetic The or is scaled from 0 to 100. In to the with of consciousness is the associated with the other monitors. The is by the and but is not in controlled that monitoring (e.g. , to to clinical practice without reported to opening or of reported for loss of after induction with and an of and reported for responsiveness after of or reported a of for reported a of for awareness after studies reported of as before induction or at or after during at emergence or of and during who in this Advisory typically a or an in intraoperative awareness and brain function monitors. The of these of from or a in a or brain function monitors. not to with other that may be affected by the use of brain function monitors. from a of of the and that a brain electrical activity is and be to reduce the risk of intraoperative awareness for The and that a brain electrical activity is and be to reduce the risk of intraoperative awareness for The that a brain electrical activity be for patients with that may place at risk and patients of general and anesthesia. They are the use of brain electrical activity monitoring for and The with the use of such monitors for patients with that may place at patients of general and patients undergoing They are the use of these monitors for patients undergoing and and that a brain electrical activity is and be to intraoperative depth of anesthesia for The and with the that brain electrical activity is and be to intraoperative depth of anesthesia for The that a brain electrical activity be to intraoperative depth of anesthesia for The with the use of brain electrical activity monitors for patients with that may place at risk and patients of general They are the use of such monitors for patients undergoing and monitoring of depth of anesthesia, for the purpose of the of awareness, on clinical (e.g. , for clinical such as purposeful or and monitoring (e.g. , anesthetic The use of neuromuscular blocking drugs may purposeful or movements and to the use of monitoring that the of function monitors are to the of the of on the brain and provide information that with some depth of anesthesia such as concentrations of (e.g. , In the by these monitors in with other of depth of anesthesia, the by devices in any anesthetic state the various monitoring In the by devices in the of a depth of anesthesia by of anesthetic drugs (e.g. , with or without also In other a specific may not with a specific depth of anesthesia. the not have anesthetic drugs or of with other in the operating room may into the derived by these monitors (e.g. , general clinical of these monitors in the of intraoperative awareness has not been a clinical reported a in the frequency of awareness in is to a or absolute that these devices be to reduce the of intraoperative awareness in patients undergoing general anesthesia. In is to a or absolute that these devices be to reduce the of intraoperative awareness for any other of patients undergoing general is the consensus of the that brain function monitoring is not for patients undergoing general anesthesia, to reduce the frequency of intraoperative awareness or to depth of anesthesia. This consensus is in on the state of the literature and responses from the and who with the following function monitors are and be to reduce the risk of intraoperative awareness for patients under general and function monitors are and be when possible to intraoperative depth of anesthesia for patients under general is the consensus of the that the decision to use a brain function be on a by the for patients (e.g. , This consensus is in on the state of the literature and from and specific risk factors The that maintaining brain function in an to prevent intraoperative awareness may with other important anesthesia (e.g. , of the of is the of the that brain function monitors have the of the other monitoring that are in at the of and include the intraoperative administration of to patients who may have a structured interview to patients to the of the episode after an episode of intraoperative awareness has been a to patients to the of the and or psychological studies that the of the intraoperative administration of to patients who have conscious in the of clinical amnesia by as to patients before administration of and induction of general anesthesia. The studies reported of these studies not the of a benzodiazepine to patients after the of consciousness during general several studies have structured and to information reported of intraoperative studies that in patient or psychological state after such studies that on the of or psychological to patients who a incidence of intraoperative are and that or be administered to prevent awareness after a patient has The and the that an episode of intraoperative awareness has been a structured interview be to the of the the and are a be to the of the The and the that in of intraoperative awareness, patients be or psychological the and the that in of intraoperative awareness, an report the event be for the purpose of consensus is that the decision to a benzodiazepine after a patient becomes conscious be on a This consensus is in on the state of the literature and on responses from the and the following or be administered to prevent awareness after a patient has the that from the literature is not sufficient to provide guidance this the that the use of may in unintended (e.g. , emergence with patients who report recall of intraoperative events to of the event and to possible for or structured interview may be to a of the patient’s an episode of intraoperative awareness has been an report the event be for the purpose of the patient be or psychological this Advisory, a literature in with opinions from and other (e.g. , members, open forums, to provide guidance to intraoperative the literature and on , of specific perioperative and intraoperative The are or report that in the literature is in the of an the is to one of the reports a or of that be or (e.g. , that only are not and is the of an or report , or studies that summarize previous are not the literature studies identified and of the literature. The a from The a of time from a of that addressed to the and for of the studies not provide and subsequently of studies with and information to a analysis , and by a for as of of and literature for of and literature to of of this Advisory to studies with such as that the of an as a brain function on the or frequency of intraoperative only controlled that reported intraoperative awareness as the controlled will be necessary before from literature be to provide a for , other that reported other intraoperative awareness, emergence of anesthetic and In other studies to or For example, literature , reports of frequency or may provide an of the of the or provide information the and of of from patient monitoring devices with other intraoperative such as concentrations of anesthetic time to loss of and time to reports are typically as a forum for and or unintended or reports as well as or provide information that may stimulate of the of intraoperative studies on when that use of the following for the of for intraoperative awareness is studies the of one other to treatment with and of of and The because intraoperative awareness is a such studies may be and The required for a to the of an (e.g. , brain function on the incidence of intraoperative awareness is The also with data, a in the of one or of intraoperative awareness the of the to patient to have a risk for intraoperative awareness (e.g. , may for a and provide information these the that the of these to the of general anesthesia patients may be from from who on or in intraoperative awareness, opinions from a of of the from of open at anesthesia commentary, and and The of return of for and for the are in the of the and in and of the and of the that they a brain function in the of the that they use in practice of a brain function or of the that they use in practice of a brain function or also to of the clinical the Advisory The of return of The of associated with as patients of the of intraoperative anesthesia use of as use of clinical to for intraoperative use of monitoring to for intraoperative use of brain function monitors to for intraoperative intraoperative use of for use of a structured interview for patients who report recall of intraoperative use of a for patients who report recall of intraoperative and for patients who report recall of intraoperative of the that the Advisory have on the of time on a that be an in the of time they on a with the of this The of time by these from to
No AccessJournal of Speech and Hearing DisordersResearch Article1 Aug 1963Speech Characteristics of Patients with Parkinson's Disease: I. Intensity, Pitch, and Duration Gerald J. Canter Gerald J. Canter Google Scholar https://doi.org/10.1044/jshd.2803.221 SectionsAboutPDF ToolsAdd to favoritesDownload CitationTrack Citations ShareFacebookTwitterLinked In Additional Resources FiguresReferencesRelatedDetailsCited byJournal of Speech, Language, and Hearing Research65:4 (1402-1415)4 Apr 2022Longitudinal Effects of Parkinson's Disease on Speech Breathing During an Extemporaneous Connected Speech TaskMeghan Darling-White, Zeina Anspach and Jessica E. 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Gerratt (2020) Acoustic Analysis and Voice Quality in Parkinson Disease Automatic Assessment of Parkinsonian Speech10.1007/978-3-030-65654-6_1 Laureano Moro-Velazquez and Najim Dehak (2020) A Review of the Use of Prosodic Aspects of Speech for the Automatic Detection and Assessment of Parkinson's Disease Automatic Assessment of Parkinsonian Speech10.1007/978-3-030-65654-6_3 Perspectives of the ASHA Special Interest Groups4:5 (825-841)31 Oct 2019Research-Based Updates in Swallowing and Communication Dysfunction in Parkinson Disease: Implications for Evaluation and ManagementC. K. Broadfoot, D. Abur, J. D. Hoffmeister, C. E. Stepp and M. R. Ciucci The Japanese Journal of Rehabilitation Medicine56:3 (209-212)18 Mar 2019Speech and Voice Disorders in Parkinson's Diseaseパーキンソン病の音声障害Takashi Maeno and Chihiro Oda Ahmad Habbie Thias, Isca Amanda, Jessika, Navila Akhsanil Fitri, Raih Rona Althof, Suksmandhira Harimurti, Widyawardana Adiprawita and Isa Anshori (2019) Preliminary Study on Machine Learning Application for Parkinson's Disease Diagnosis 2019 Asia Pacific Conference on Research in Industrial and Systems Engineering (APCoRISE)10.1109/APCoRISE46197.2019.9318828978-1-7281-1554-2 Oxidative Medicine and Cellular Longevity2018 (1-17)27 Jun 2018Rutin as a Potent Antioxidant: Implications for Neurodegenerative DisordersAdaze Bijou Enogieru, William Haylett, Donavon Charles Hiss, Soraya Bardien and Okobi Eko Ekpo Wentao Gu, Ping Fan and Weiguo Liu (2018) Acoustic Analysis of Mandarin Speech in Parkinson's Disease with the Effects of Levodopa Studies on Speech Production10.1007/978-3-030-00126-1_19 Neurodegenerative Disease Management8:5 (337-348)1 Oct 2018Speech disorders in Parkinson's disease: pathophysiology, medical management and surgical approachesKhashayar Dashtipour, Ali Tafreshi, Jessica Lee and Brianna Crawley Dementia and Geriatric Cognitive Disorders46:3-4 (207-216)An Informant-Based Simple Questionnaire for Language Assessment in Neurodegenerative DisordersChi-Mo Lin, Guang-Uei Hung, Cheng-Yu Wei, Ray-Chang Tzeng and Pai-Yi Chiu Methods151 (41-54)1 Dec 2018Speech analysis for health: Current state-of-the-art and the increasing impact of deep learningNicholas Cummins, Alice Baird and Björn W. 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Hammouch (2016) Comparison of classification methods to detect the Parkinson disease 2016 International Conference on Electrical and Information Technologies (ICEIT)10.1109/EITech.2016.7519634978-1-4673-8469-8 D. Meghraoui, B. Boudraa, T. Merazi Meksen and M. Boudraa (2016) Features dimensionality reduction and multi-dimensional voice processing program to Parkinson disease discrimination 2016 4th International Conference on Control Engineering & Information Technology (CEIT)10.1109/CEIT.2016.7929107978-1-5090-1055-4 Neurología31:7 (466-472)1 Sep 2016Estudio controlado del ritmo del habla en la enfermedad de ParkinsonF. Martínez-Sánchez, J.J.G. Meilán, J. Carro, C. Gómez Íñiguez, L. Millian-Morell, I.M. Pujante Valverde, T. López-Alburquerque and D.E. López Journal of Cognitive Neuroscience28:4 (621-635)1 Apr 2016The Neural Basis of Vocal Pitch Imitation in HumansMichel Belyk, Peter Q. 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Kell Jorge Proença, Arlindo Veiga, Sara Candeias, João Lemos, Cristina Januário and Fernando Perdigão (2014) Characterizing Parkinson's Disease Speech by Acoustic and Phonetic Features Computational Processing of the Portuguese Language10.1007/978-3-319-09761-9_3 Journal of Neural Transmission120:2 (319-329)1 Feb 2013Evaluation of speech impairment in early stages of Parkinson's disease: a prospective study with the role of pharmacotherapyJan Rusz, Roman Čmejla, Hana Růžičková, Jiří Klempíř, Veronika Majerová, Jana Picmausová, Jan Roth and Evžen Růžička Neurologia i Neurochirurgia Polska47:3 (263-270)Charakter zaburzeń mowy w chorobie ParkinsonaWioletta Pawlukowska, Krystyna Honczarenko and Monika Gołąb-Janowska Journal of Clinical Neuroscience19:8 (1125-1129)1 Aug 2012A study of voice profiles and acoustic signs in patients with Parkinson's disease in North IndiaJayam P Lazarus, Deepti Vibha, K.K. Handa, Sumit Singh, Vinay Goyal, Trilochan Srivastava, Vijay Aggarwal and Madhuri Behari Parkinson's Disease2012 (1-10)Effect of Deep Brain Stimulation on Speech Performance in Parkinson's DiseaseSabine Skodda Journal of Neurolinguistics25:2 (104-120)1 Mar 2012Some prosodic characteristics of parkinsonian French speech: Effects of bilateral stimulation of the subthalamic nucleusDanielle Duez, Ludovic Jankowski, Alain Purson and François Viallet Basal Ganglia2:1 (49-54)1 Mar 2012Effects of levodopa and deep brain stimulation on motor speech performance in Parkinson's diseaseSabine Skodda, Uwe Schlegel, Martin Südmeyer, Alfons Schnitzler and Lars Wojtecki Journal of Speech, Language, and Hearing Research55:5 (1472-1484)1 Oct 2012Characterizing Intonation Deficit in Motor Speech Disorders: An Autosegmental–Metrical Analysis of Spontaneous Speech in Hypokinetic Dysarthria, Ataxic Dysarthria, and Foreign Accent SyndromeAnja Lowit and Anja Kuschmann Neurodegenerative Disease Management2:5 (535-545)1 Oct 2012Analysis of voice and speech performance in Parkinson's disease: a promising tool for the monitoring of disease progression and differential diagnosisSabine Skodda Jiri Mekyska, Irena Rektorova and Zdenek Smekal (2011) Selection of optimal parameters for automatic analysis of speech disorders in Parkinson's disease 2011 34th International Conference on Telecommunications and Signal Processing (TSP)10.1109/TSP.2011.6043700978-1-4577-1410-8 Parkinson's Disease2011 (1-12)High-Level Language Production in Parkinson's Disease: A ReviewLori J. 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Schlauch Clinical Neurology and Neurosurgery109:6 (495-500)1 Jul 2007The effect of levodopa on respiration and word intelligibility in people with advanced Parkinson's diseaseMiet De Letter, Patrick Santens, Marc De Bodt, Georges Van Maele, John Van Borsel and Paul Boon Lorraine Olson Ramig, Cynthia Fox and Shimon Sapir (2007) Speech disorders in Parkinson's disease and the effects of pharmacological, surgical and speech treatment with emphasis on Lee Silverman voice treatment (LSVT®) Parkinson's Disease and Related Disorders, Part I10.1016/S0072-9752(07)83017-X Journal of Neurolinguistics20:3 (221-241)1 May 2007An acoustic investigation of Parkinsonian speech in linguistic and emotional contextsHenry S. Cheang and Marc D. Pell Clinical Linguistics & Phonetics20:1 (19-33)1 Jan 2006Speech production in Parkinson's disease: II. Acoustic and electropalatographic investigation of sentence, word and segment durationsMegan J. Mcauliffe, Elizabeth C. Ward and Bruce E. Murdoch Journal of Multilingual Communication Disorders4:1 (45-57)1 Jan 2006Syllable structure, syllable duration and final lengthening in Parkinsonian French speechDanielle Duez Folia Phoniatrica et Logopaedica58:2 (114-131)Comparison of Speaking Rate, Articulation Rate and Alternating Motion Rate in Dysarthric SpeakersMasaki Nishio and Seiji Niimi Journal of Speech, Language, and Hearing Research49:2 (395-411)1 Apr 2006Parametric Quantitative Acoustic Analysis of Conversation Produced by Speakers With Dysarthria and Healthy SpeakersKristin M. Rosen, Raymond D. Kent, Amy L. Delaney and Joseph R. Duffy Acoustical Science and Technology26:6 (540-543)Evaluation of fundamental frequency (F0) characteristics of speech in dysarthrias: A comparative studyHiroki Mori, Yasunori Kobayashi, Hideki and Hajime Folia Phoniatrica et of Vocal in Parkinson's M. Rosen, Raymond D. Kent and Joseph R. Duffy Journal of Communication May effects of levodopa on word intelligibility in Parkinson's diseaseMiet De Letter, Patrick Santens and John Van Borsel Journal of Communication May analysis of speech in individuals with Parkinson M. Goberman and W. in Communication Science and Mar Speech in Parkinson DiseaseAlexander M. Goberman and Jessica on and Speech and Language Jun and Disorders of on Voice and Voice Mar Function in Individuals With Parkinson's Ramig, Cynthia and Michele Tagliati Movement Apr of on the intelligibility of speech in patients with Parkinson's disease with subthalamic deep brain and Cognitive Brain Oct speech: a review of and Brain and Oct in fundamental frequency speech in and Parkinson's disease: A longitudinal Michael and Peter J. Snyder The Sep for in Parkinson's and Journal of Nov characteristics of Parkinsonian speech: a of early disease progression and T. Michael S. and Peter J. Snyder Journal of Speech, Language, and Hearing Dec Characteristics of the Contrast in Dysarthria to Patel Brain and Mar of Speech Task on Intelligibility in Dysarthria: A Study of Parkinson's and Van Lancker and Jan in with and Patel Journal of Communication May characteristics of Parkinsonian speech and the and and Michael Clinical Linguistics & Jan rate and in Seiji Niimi Brain and Aug of Bilateral Stimulation of the Subthalamic Nucleus on Parkinsonian P. S. P. and Journal of Dec in vocal intensity in Parkinson's disease M. and William Clinical Linguistics & Jan over time in patients with a study of changes in rate and repetition rate Seiji Niimi Journal of Communication Jan of speech and and surgical on voice and speech in and K Journal of Speech, Language, and Hearing Aug Preliminary Study of Factors Perception of Rate in Parkinson Tjaden The Aug and Levodopa in Parkinson's Lin, and David G. Journal of Mar measures in diseaseEmily Lin, and David G. Journal of Speech, Language, and Hearing Oct and Speech Characteristics of Persons With Parkinson's Disease and M. M. and William in Geriatric Dec of Speech and Voice Associated with Parkinson's Olson Ramig Clinical Linguistics & Jan speech in Parkinson's disease: A M. Watson and John Journal of Jan voice analysis in patients with Félix Javier Ignacio Cobeta, and Parkinsonism & Related Apr voice analysis in untreated patients with Parkinson's Javier Javier and Ignacio Clinical Linguistics & Jan and in Parkinson's E. Murdoch, C. Y. D. G. and E. C. Journal of Sep voice analysis in patients with Parkinson's disease with Félix Javier and Ignacio Jan of voice on of Parkinson's disease C. L. H. B. M. S. P. A. L. and L. A. J. H. S. P. and H. American Journal of Speech-Language May and of Speech and Voice in and With Parkinson M. Fox and Lorraine Olson Ramig Journal of Clinical and Apr Language, and Speech in A J. M. J. B. and A. Dec the Prosodic in Parkinson's D. Pell Jul of in a Parkinsonian C. H. and J. A. H. and Between and Methods and in Language and Cognitive Feb analysis of a Parkinsonian and Jan impairment in of G. W. and in Clinical Aug in Parkinson's Ward and Voice in the Voice Disorders and Journal of Jun and effect on and I. David Brain and Feb effects of and on E. and C. Journal of Human Communication Dec in Parkinson's Disease: I. Perceptual Speech J. Bruce E. Murdoch and John Brain and Jul characterization of the prosodic in Parkinson's W. A. and Journal of Sep between the Parkinsonian and a and Journal of Sep between the Parkinsonian and a and Journal of Communication Oct and in and R. of Mar and speech production in Parkinson's A. and S. Journal of Human Communication Jun Comparison of the and Spontaneous Speech Intelligibility for Dysarthric Journal of Communication Oct of the of speech bilateral in a with Parkinson's J. Canter and Van Lancker of & Jan in G. L. and J. Medical & Engineering & Mar of speech in Journal of Communication Jan of in the speech of with and of & Jan in Parkinson Disease with Elaine and Seiji Niimi John T. The in Human Communication Studies in Journal of Communication Jun characteristics of with disease R. Journal of Communication Jan and to disorders of speech and Journal of the American Feb and B. Journal of the Neurological Mar of language and E. J. and with Parkinson's H. and H. International Journal of Jan of analysis of and Review of Feb The Speech J. Canter and E. Movement Jul speech impairment in Parkinson's and Expert Review of Aug speech and language of Parkinson's David and Adam P. in Jun Variation in Parkinson's Disease: A Study on Speaking De and Anna De in Rehabilitation Jan a and a in Parkinson's Disease: A and Peter Dec habla de Evaluation & the Jun of the of a for Speech Disorders in Patients With Parkinson's Lin, and to in Aug & American
No AccessJournal of Speech and Hearing DisordersResearch Article1 Feb 1962Revised CNC Lists for Auditory Tests Gordon E. Peterson, and Ilse Lehiste Gordon E. Peterson Google Scholar More articles by this author and Ilse Lehiste Google Scholar More articles by this author https://doi.org/10.1044/jshd.2701.62 SectionsAboutPDF ToolsAdd to favoritesDownload CitationTrack Citations ShareFacebookTwitterLinked In Additional Resources FiguresReferencesRelatedDetailsCited by Otology & Neurotology28 Sep 2023Incidence of Cochlear Implant Electrode Contacts in the Functional Acoustic Hearing Region and the Influence on Speech Recognition with Electric–Acoustic StimulationEvan P. Nix, Nicholas J. Thompson, Kevin D. Brown, Matthew M. Dedmon, A. Morgan Selleck, Andrea B. Overton, Michael W. Canfarotta and Margaret T. 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Gifford Otology & Neurotology44:3 (e146-e154)1 Mar 2023Predictors of Short-Term Changes in Quality of Life after Cochlear ImplantationAmit Walia, James Bao, Noel Dwyer, Susan Rathgeb, Stephanie Chen, Matthew A. Shew, Nedim Durakovic, Jacques A. Herzog, Craig A. Buchman and Cameron C. Wick Otology & Neurotology44:3 (e125-e132)1 Mar 2023Quality of Life Impact of Cochlear Implantation for Single-Sided Deafness: Assessing the Interrelationship of Objective and Subjective MeasuresAnthony M. Tolisano, Elicia M. Pillion, Coral E. Dirks, Matthew T. Ryan and Joshua G. W. Bernstein Ear & Hearing44:2 (371-384)1 Mar 2023Relationships Between the Auditory Nerve Sensitivity to Amplitude Modulation, Perceptual Amplitude Modulation Rate Discrimination Sensitivity, and Speech Perception Performance in Postlingually Deafened Adult Cochlear Implant UsersShuman He, Jeffrey Skidmore, Brandon Koch, Monita Chatterjee, Brittney L. Carter and Yi Yuan American Journal of Audiology32:1 (251-260)1 Mar 2023Influence of Electric Frequency-to-Place Mismatches on the Early Speech Recognition Outcomes for Electric–Acoustic Stimulation UsersMargaret T. Dillon, Michael W. Canfarotta, Emily Buss, Meredith A. Rooth, Margaret E. Richter, Andrea B. Overton, Noelle E. Roth, Sarah M. Dillon, Jenna H. Raymond, Allison Young, Adrienne C. Pearson, Amanda G. Davis, Matthew M. Dedmon, Kevin D. Brown and Brendan P. O'Connell JAMA Otolaryngology–Head & Neck Surgery149:3 (212)1 Mar 2023Association of Genetic Diagnoses for Childhood-Onset Hearing Loss With Cochlear Implant OutcomesRyan J. Carlson, Tom Walsh, Jessica B. Mandell, Amal Aburayyan, Ming K. Lee, Suleyman Gulsuner, David L. Horn, Henry C. Ou, Kathleen C. Y. Sie, Lisa Mancl, Jay Rubinstein and Mary-Claire King Cochlear Implants International (1-7)27 Feb 2023Influence of listening environment on usage patterns in cochlear implant patients with single-sided deafnessAlejandro Garcia, Afash Haleem, Divya A. Chari, Charlotte Morse-Fortier, Julie G. Arenberg and Daniel J. Lee Trends in Hearing271 Jan 2023Grouping by Time and Pitch Facilitates Free but Not Cued Recall for Word Lists in Normally-Hearing ListenersAnastasia G. Sares, Annie C. Gilbert, Yue Zhang, Maria Iordanov, Alexandre Lehmann and Mickael L. D. Deroche Ear & HearingPublish Ahead of Print17 May 2023The Relationship Between Cochlear Implant Speech Perception Outcomes and Electrophysiological Measures of the Electrically Evoked Compound Action PotentialJeffrey Skidmore, Jacob J. Oleson, Yi Yuan and Shuman He Otology & Neurotology43:10 (e1094-e1099)1 Dec 2022Voluntary Field Recall of Advanced Bionics HiRes Cochlear Implants: A Single-Institution ExperienceChristopher I. McHugh, Britta K. Swedenborg, Jenny X. Chen, David H. Jung, Leila A. Mankarious, Alicia M. Quesnel, Michael S. Cohen, Julie G. Arenberg, Kevin H. Franck and Felipe Santos Otology & Neurotology43:10 (1149-1154)1 Dec 2022Speech Recognition Performance Differences Between Precurved and Straight Electrode Arrays From a Single ManufacturerRahul K. Sharma, Miriam R. Smetak, Ankita Patro, Nathan R. Lindquist, Elizabeth L. Perkins, Jourdan T. Holder, David S. Haynes and Kareem O. Tawfik Ear & Hearing43:6 (1605-1619)1 Nov 2022American Cochlear Implant Alliance Task Force Guidelines for Clinical Assessment and Management of Adult Cochlear Implantation for Single-Sided DeafnessMargaret T. Dillon, Armine Kocharyan, Ghazal S. Daher, Matthew L. Carlson, William H. Shapiro, Hillary A. Snapp and Jill B. Firszt Ear & Hearing43:6 (1761-1770)1 Nov 2022Postlingually Deafened Adult Cochlear Implant Users With Prolonged Recovery From Neural Adaptation at the Level of the Auditory Nerve Tend to Have Poorer Speech Perception PerformanceShuman He, Jeffrey Skidmore, Brittney L. Carter, Stanley Lemeshow and Shuai Sun PLOS ONE17:10 (e0275772)13 Oct 2022Within- and across-frequency temporal processing and speech perception in cochlear implant usersChelsea M. Blankenship, Jareen Meinzen-Derr, Fawen Zhang and Prashanth Prabhu PLOS ONE17:10 (e0274643)7 Oct 2022Cortical auditory evoked potential in cochlear implant users: An objective method to improve speech perceptionDayse Távora-Vieira, Andre Wedekind, Ellen Ffoulkes, Marcus Voola, Roberta Marino and Paul Hinckley Delano The Journal of the Acoustical Society of America152:4 (2336-2356)1 Oct 2022Speech-in-noise testing: Innovative applications for pediatric patients, underrepresented populations, fitness for duty, clinical trials, and remote servicesVictoria A. Sanchez, Michelle L. Arnold, David R. Moore, Odile Clavier and Harvey B. Abrams Otology & Neurotology43:9 (e1008-e1012)1 Oct 2022Electrode Impedance Fluctuations and Sudden Decline in Cochlear-Implant BenefitCache Pitt, Naveen K. Nagaraj and Anna Salisbury Otology & Neurotology43:9 (e1000-e1007)1 Oct 2022External Validation of Cochlear Implant Screening Tools Demonstrates Modest GeneralizabilityDavid S. Lee, Jacques A. 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Yost and Jungmee Lee The Journal of the Acoustical Society of America152:3 (1639-1645)1 Sep 2022On the use of the TIMIT, QuickSIN, NU-6, and other widely used bandlimited speech materials for speech perception experimentsBrian B. Monson and Emily Buss JASA Express Letters2:91 Sep 2022Speech recognition as a function of the number of channels for pediatric cochlear implant recipientsRené H. Gifford, Linsey W. Sunderhaus, Jourdan T. Holder, Katelyn A. Berg, Benoit M. Dawant, Jack H. Noble, Elizabeth Perkins and Stephen Camarata Otology & Neurotology43:8 (915-923)1 Sep 2022Promontory Electrocochleography Recordings to Predict Speech-Perception Performance in Cochlear Implant RecipientsAmit Walia, Matthew A. Shew, David S. Lee, Shannon M. Lefler, Dorina Kallogjeri, Cameron C. Wick, Nedim Durakovic, Douglas C. Fitzpatrick, Amanda J. Ortmann, Jacques A. Herzog and Craig A. Buchman Otology & Neurotology43:8 (e895-e902)1 Sep 2022(Even Off-Label) Cochlear Implantation in Single-Sided Deafness and Asymmetric Hearing Loss Results in Measurable Objective and Subjective BenefitSarah A. Sydlowski, Nathan Farrokhian, Marisa Carrozza, Carmen Jamis and Erika Woodson Otology & Neurotology43:8 (e888-e894)1 Sep 2022Association of Self-Reported Coping Strategies With Speech Recognition Outcomes in Adult Cochlear Implant UsersMana Espahbodi, Erin Harvey, Austin J. Livingston, William Montagne, Kristin Kozlowski, Jamie Jensen, Xuerong Liu, Wanlin Juan, Sergey Tarima, Mark Rusch and Michael S. Harris American Journal of Audiology31:3 (698-706)1 Sep 2022Cochlear Implants in Veterans: 10-Year Experience at a Single Referral CenterColleen A. O'Brien, Susan B. Waltzman, Joshua Chodosh and David R. 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Yeagle, Francis X. Creighton, Nae-Yuh Wang, Stephen P. Bowditch, Charles C. Della Santina and Daniel Q. Sun Hearing Research421 (108379)1 Aug 2022Effects of extended high frequency bandwidth in osseointegrated bone conduction device usersHillary A. Snapp and Brianna Kuzbyt Cochlear Implants International23:4 (225-231)4 Jul 2022Speech perception abilities of adult cochlear implant listeners with single-sided deafness vs. bilateral hearing lossDouglas P. Sladen and Daniel M. Zeitler Otolaryngology–Head and Neck Surgery167:1 (149-154)1 Jul 2022Cochlear Implantation Outcomes in Observed Vestibular Schwannoma: A Preliminary ReportElizabeth S. Longino, Nauman F. Manzoor, Nathan D. Cass, Kareem O. Tawfik, Marc L. Bennett, Matthew R. O’Malley, David S. Haynes and Elizabeth L. Perkins Otology & Neurotology43:6 (632-637)1 Jul 2022Cochlear Implant Outcomes in CHARGE Syndrome: Updated PerspectivesEmily Kay-Rivest, Sean O. McMenomey, Daniel Jethanamest, J. Thomas Roland, William H. Shapiro, Susan B. Waltzman and David R. Friedmann Ear & Hearing43:4 Jul and Evaluation of a Test of Auditory Discrimination for for Cochlear Implant Candidacy Harvey Dillon, Mark and American Journal of Jun of on Recognition in for Cochlear Implant G. Matthew M. Dedmon, Emily Buss, Meredith A. Rooth, Margaret E. and Margaret T. Dillon Audiology and Neurotology May 2022Effects of Cochlear Implantation on for and Hillary Meredith and Sandra Otology & Apr Hearing Preservation Outcomes Cochlear Implantation With Electrode Using Walia, Matthew A. Shew, Shannon M. Lefler, Cameron C. Wick, Nedim Durakovic, Craig A. Buchman and Jacques A. Herzog Otology & Ahead of Mar of Speech Test Outcomes Cochlear Implantation in With and Asymmetric Hearing Sandra Meredith and Christine T. Otolaryngology–Head and Neck Mar 2022Cochlear Implantation Hearing in Barbara S. and D. Ear & Mar Aug of a for Modulation M. Landsberger and Ear & Mar Jul of A Clinical for and of Cochlear Implant and Ear & Mar Feb 2022American Cochlear Implant Alliance Task Force Guidelines for Determining Cochlear Implant Candidacy in D. J. Thomas Roland, Kristin and Journal of the American of Mar for Cochlear Implant Recipients in Jace Wolfe, Sara Neumann, Erin C. and The Mar Benefits of Cochlear Implantation in Unilateral Hearing Loss Kevin D. Brown, Margaret T. Dillon and Lisa R. Feb and of speech perception outcomes in noise for cochlear implant Walia, Matthew A. Shew, Dorina Kallogjeri, Cameron C. Wick, Nedim Durakovic, Shannon M. Lefler, Amanda J. Ortmann, Jacques A. Herzog and Craig A. Buchman Otology & Feb and Cochlear Implant Speech Recognition Outcomes: A of and W. Canfarotta, Margaret T. Dillon, Kevin D. Brown, C. Matthew M. and Brendan P. Otology & Feb and Cochlear Implant Electrode in M. R. Matthew J. J. Joseph B. Felipe David H. Jung, Aaron K. and D. of Jan 2022Speech and Language Outcomes in Adults and Children with Cochlear N. David B. and Aaron C. Moberly Trends in Jan and Validation of a Chinese Adaptation of Test Wang, Shi, Li, and Trends in Jan of a Cochlear Implant Changes in and Cochlear K. S. L. Robert H. Marcus Robert J. and Trends in Jan Relationship Between and Word Recognition in a Clinical of Cochlear Implant Caswell-Midwinter, Elizabeth M. K. Arjmandi, N. Jahn, Barbara S. and Julie G. Arenberg Audiology and of after Cochlear Implant the on Sound Field and Speech G. Kevin D. Brown, Emily Buss, Andrea L. Matthew M. Dedmon, Brendan P. Jenna and Margaret T. Dillon Audiology and Adaptation and Impact Word Recognition in Adults with Cochlear N. Tamati and Aaron C. Moberly Otology & Neurotology Jun Jun for in the Management of Adults Using Hearing T. Holder, Meredith A. Hillary Robert F. Christine Camille Dunn and René H. Gifford Otology & Jan 2022Speech Perception Performance Growth and Score Cochlear Implantation for Single-Sided M. P. Christine M. John P. A. L. W. A. and Matthew L. Otology & Jan Impact of Age on Sensitivity in Cochlear Implant A. Shew, Jacques A. Herzog, Dorina Kallogjeri, Stephanie Chen, Cameron Wick, Nedim Durakovic, and Craig A. Buchman Otology & Jan of Duration of Deafness on Speech Perception in Single-Sided Deafness Cochlear Implantation in M. P. A. A. L. W. and Matthew L. Ear & Jan Jun for the of the Electrically Evoked Compound Action Potential Amplitude Growth Skidmore, J. C. E. and Shuman He of Dec of for Pediatric Cochlear Brown and René H. Gifford Ear & Nov Auditory Implant Outcomes and Electrode Array on Samuel R. Christine L. Carter, Mary E. M. Brown, Barbara S. and Daniel J. Lee in Nov Assessment of Hearing Verification and Speech Recognition Testing A. Sydlowski, Michelle and in Nov Cochlear Implant Candidacy in and for A. and Frontiers in Human Oct Acoustic in to Changes and to Cochlear Implant Speech M. Zhang and Fawen Zhang Journal of Speech, Language, and Hearing Oct of Daily Cochlear Implant Use on Auditory Perception in T. Holder and René H. Gifford Otology & Oct of Cochlear Implant Use on Perceived in Adult and Pediatric of Unilateral and Asymmetric Hearing M. Margaret T. Dillon, Lisa R. Park, Meredith A. Rooth, Margaret E. Richter, Nicholas J. Thompson, Brendan P. C. and Kevin D. Brown Journal of Oct of on A and Cochlear Implants International Sep of electrode to cochlear on speech understanding P. A. H. and Matthew B. Ear & Sep Apr in to for Cochlear L. and Matthew B. Journal of the American of Sep of with Cochlear Implant RecipientsLisa G. Potts, and L. Journal of the American of Sep Impact of on Recognition of H. and Aaron C. Moberly The Sep Recognition as a of Age and Experience in Adult Cochlear Implant T. Michael W. Canfarotta, Brendan P. Emily Buss, English R. Andrea L. Sarah A. Dillon, Meredith A. Rooth, Matthew M. Dedmon, Kevin D. Brown and Margaret T. Dillon PLOS Jul in cochlear implant listening T. Joseph Chen, Trung Vincent Lin, Andrew and Otology & Jul of Hearing Preservation in Cochlear Perkins, Lee, Nauman Manzoor, Matthew O’Malley, Marc Bennett, Robert David Haynes and René Gifford Otology & Jul Evidence for the of Adult Cochlear Implant Candidacy Perkins, Mary S. Dietrich,
Previous article Next article Fractional Brownian Motions, Fractional Noises and ApplicationsBenoit B. Mandelbrot and John W. Van NessBenoit B. Mandelbrot and John W. Van Nesshttps://doi.org/10.1137/1010093PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] I. Adelman, Long cycles—fact or artifact?, Amer. Economic Rev., 60 (1965), 444–463 Google Scholar[2] William Feller, The asymptotic distribution of the range of sums of independent random variables, Ann. Math. Statistics, 22 (1951), 427–432 MR0042626 0043.34201 CrossrefISIGoogle Scholar[3] I. M. Gel'fand and , N. Ya. Vilenkin, Generalized functions. Vol. 4, Academic Press [Harcourt Brace Jovanovich Publishers], New York, 1964 [1977]xiv+384 MR0435834 Google Scholar[4] C. W. J. Granger, The typical spectral shape of an economic variable, Econometrica, 34 (1966), 150–161 CrossrefISIGoogle Scholar[5] G. A. Hunt, Random Fourier transforms, Trans. Amer. Math. Soc., 71 (1951), 38–69 MR0051340 0043.30601 CrossrefISIGoogle Scholar[6] H. E. Hurst, , R. P. Black and , Y. M. Sinaika, Long Term Storage in Reservoirs. An Experimental Study, Constable, London, 1965 Google Scholar[7] A. N. Kolmogoroff, Wienersche Spiralen und einige andere interessante Kurven im Hilbertschen Raum, C. R. (Doklady) Acad. Sci. URSS (N.S.), 26 (1940), 115–118 MR0003441 0022.36001 Google Scholar[8] John Lamperti, Semi-stable stochastic processes, Trans. Amer. Math. Soc., 104 (1962), 62–78 MR0138128 0286.60017 CrossrefGoogle Scholar[9] Paul Lévy, Random functions: General theory with special reference to Laplacian random functions, Univ. California Publ. Statist., 1 (1953), 331–390 MR0055607 0052.14402 Google Scholar[10] Michel Loève, Probability theory, 2nd ed. The University Series in Higher Mathematics. D. Van Nostrand Co., Inc., Princeton, N. J.-Toronto-New York-London, 1960xvi+685 MR0123342 0095.12201 Google Scholar[11] Benoı⁁t Mandelbrot, Une classe processus stochastiques homothétiques à soi; application à la loi climatologique H. E. Hurst, C. R. Acad. Sci. Paris, 260 (1965), 3274–3277 MR0176521 0127.09501 Google Scholar[12] B. Mandelbrot, Self-similar error-clusters in communication systems and the concept of conditional stationarity, IEEE Trans. Comet. Tech., COM-13 (1965), 71–90 10.1109/TCOM.1965.1089090 CrossrefISIGoogle Scholar[13] B. Mandelbrot, Noises with an $l/f$ spectrum, a bridge between direct current and white noise, IEEE Trans. Information Theory, IT-13 (1967), 289–298 10.1109/TIT.1967.1053992 0148.40507 CrossrefISIGoogle Scholar[14] Benoit Mandelbrot, Sporadic random functions and conditional spectral analysis: Self-similar examples and limitsProc. Fifth Berkeley Sympos. Mathematical Statistics and Probability (Berkeley, Calif., 1965/66), Vol. III: Physical Sciences, Univ. California Press, Berkeley, Calif., 1967, 155–179 MR0224243 0189.18302 Google Scholar[15] B. Mandelbrot and , J. R. Wallis, Noah, Joseph and operational hydrology, Water Resources Research, to appear Google Scholar[16] B. Mandelbrot and , J. R. Wallis, Computer experiments with fractional Gaussian noise, Water Resources Research, to appear Google Scholar[17] B. Mandelbrot and , J. R. Wallis, Some long run properties of geophysical records, Water Resources Research, to appear. Google Scholar[18] G. Maruyama, The harmonic analysis of stationary stochastic processes, Mem. Fac. Sci. Kyusyu Univ. A., 4 (1949), 45–106 MR0032127 0045.40602 CrossrefGoogle Scholar[19] M. Rosenblatt, Independence and dependenceProc. 4th Berkeley Sympos. Math. Statist. and Prob., Vol. II, Univ. California Press, Berkeley, Calif., 1961, 431–443 MR0133863 0105.11802 Google Scholar[20] G. I. Taylor, Statistical theory of turbulence, Proc. Roy. Sac. Ser. A, 151 (1935), 421–478 CrossrefGoogle Scholar[21] H. Weyl, Bemerkungen zum Begriff der Differential-Quotenten gebrochener Ordnung, Vierteljschr. Naturforsch. Ges. Zürich, 62 (1967), 296–302 Google Scholar[22] A. M. Yaglom, Correlation theory of processes with random stationary nth increments, Amer. Math. Soc. Transl. (2), 8 (1958), 87–141 MR0091554 0080.34903 CrossrefGoogle Scholar[23] A. M. Yaglom, L. M. LeCam and , J. Neyman, Stationary Gaussian processes satisfying the strong mixing condition and best predictable functionalsBernoulli-Bayes-Laplace Anniversary Volume, Springer-Verlag, New York, 1965, 241–252 0142.13904 CrossrefGoogle Scholar[24] A. M. Yaglom, Outline of some topics in linear extrapolation of stationary random processesProc. Fifth Berkeley Sympos. Math. Statist. and Probability (Berkeley, Calif., 1965/66), Vol. II:Contributions to Probability Theory, Part 1, Univ. California Press, Berkeley, Calif., 1967, 259–278 MR0215358 0189.18401 Google Scholar[25] Antoni Zygmund, Trigonometrical series, Chelsea Publishing Co., New York, 1952vi+329, 2nd ed. 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SeriesSensors, Vol. 22, No. 16 | 21 August 2022 Cross Ref A Model Based on Fractional Brownian Motion for Temperature Fluctuation in the Campi Flegrei CalderaFractal and Fractional, Vol. 6, No. 8 | 30 July 2022 Cross Ref Acceleration scaling and stochastic dynamics of a fluid particle in turbulencePhysical Review Fluids, Vol. 7, No. 8 | 24 August 2022 Cross Ref Multifractional Brownian motion characterization based on Hurst exponent estimation and statistical learningChaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 32, No. 8 | 1 Aug 2022 Cross Ref Stability analysis of the Iraqi GNSS stationsJournal of Applied Geodesy, Vol. 16, No. 3 | 31 March 2022 Cross Ref Multifractal test for nonlinearity of interactions across scales in time seriesBehavior Research Methods, Vol. 61 | 19 July 2022 Cross Ref Rolling Bearing Fault Diagnosis Based on MFDFA-SPS and ELMMathematical Problems in Engineering, Vol. 2022 | 18 Jul 2022 Cross Ref Encoding Protest Duration In An Agent-Based Model As Characteristic Phase Transitions2022 Annual Modeling and Simulation Conference (ANNSIM) | 18 Jul 2022 Cross Ref Decomposing the effect of anomalous diffusion enables direct calculation of the Hurst exponent and model classification for single random pathsJournal of Physics A: Mathematical and Theoretical, Vol. 55, No. 27 | 13 June 2022 Cross Ref Classification of stochastic processes by convolutional neural networksJournal of Physics A: Mathematical and Theoretical, Vol. 55, No. 27 | 24 June 2022 Cross Ref A generalized two‐factor square‐root framework for modeling occurrences of natural catastrophesJournal of Forecasting, Vol. 4 | 6 July 2022 Cross Ref The first exit time of fractional Brownian motion from the minimum and maximum parabolic domainsStatistics & Probability Letters, Vol. 186 | 1 Jul 2022 Cross Ref Fractional stochastic Loewner evolution and scaling curvesPhysica A: Statistical Mechanics and its Applications, Vol. 597 | 1 Jul 2022 Cross Ref Stochastic pursuit-evasion curves for foraging dynamicsPhysica A: Statistical Mechanics and its Applications, Vol. 597 | 1 Jul 2022 Cross Ref Power‐type derivatives for rough volatility with jumpsJournal of Futures Markets, Vol. 42, No. 7 | 13 May 2022 Cross Ref Simultaneous Identification of Volatility and Mean-Reverting Parameter for European Option under Fractional CKLS ModelFractal and Fractional, Vol. 6, No. 7 | 21 June 2022 Cross Ref Absence of stationary states and non-Boltzmann distributions of fractional Brownian motion in shallow external potentialsNew Journal of Physics, Vol. 24, No. 7 | 7 July 2022 Cross Ref Sublinear diffusion in the generalized triangle mapPhysical Review E, Vol. 106, No. 1 | 11 July 2022 Cross Ref Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19International Review of Financial Analysis, Vol. 82 | 1 Jul 2022 Cross Ref Unravelling the origins of anomalous diffusion: From molecules to migrating storksPhysical Review Research, Vol. 4, No. 3 | 18 July 2022 Cross Ref Fractality of Borsa Istanbul during the COVID-19 PandemicMathematics, Vol. 10, No. 14 | 18 July 2022 Cross Ref Probing local chromatin dynamics by tracking telomeresBiophysical Journal, Vol. 121, No. 14 | 1 Jul 2022 Cross Ref Are the top six cryptocurrencies efficient? Evidence from time‐varying long memoryInternational Journal of Finance & Economics, Vol. 27, No. 3 | 7 December 2020 Cross Ref The anomalous process in singlet fission kinetic model with time-dependent coefficientPhysica B: Condensed Matter, Vol. 117 | 1 Jul 2022 Cross Ref A Unified Convergence Analysis for the Fractional Diffusion Equation Driven by Fractional Gaussian Noise with Hurst Index $H\in(0,1)$Daxin Nie and Weihua DengSIAM Journal on Numerical Analysis, Vol. 60, No. 3 | 28 June 2022AbstractPDF (498 KB)Elimination of Image Saturation Effects on Multifractal Statistics Using the 2D WTMM in Vol. 13 | 28 June 2022 Cross Ref the relationship between processes with fractional Brownian motion errors of Statistical and Simulation, Vol. 8 | 28 June 2022 Cross Ref under a fractional Brownian motion with Stochastic in and Vol. 2 | 27 June 2022 Cross Ref of rough stochastic volatility models on Journal, Vol. 19 | June 2022 Cross Ref the of anomalous diffusion with the of of Physics A: Mathematical and Theoretical, Vol. 55, No. 24 | 26 May 2022 Cross Ref impact on Evidence from a Hurst A: Statistical Mechanics and its Applications, Vol. | 1 2022 Cross Ref method to the of in fractal and Vol. 10, No. 2 | 18 May 2022 Cross Ref of Using and Statistical in Journal of Science and Transactions of Engineering, Vol. No. 3 | 26 September 2021 Cross Ref The of fractional Brownian Annals of Applied Vol. 32, No. 3 | 1 2022 Cross Ref behavior during the a comparison between and European based on Economic Vol. 12, No. 2 | 20 September 2021 Cross Ref On fractional Lévy motion: and in Applied Vol. No. 2 | 6 June 2022 Cross Ref Time and Persistence in An Using Fractional Journal of Research, Vol. 16, No. 3 | 7 April 2022 Cross Ref A for time fractional with Vol. No. | 2 2021 Cross Ref and Vol. No. 2 | 13 June 2022 Cross Ref Long short time the rough and in and Finance, Vol. No. 1 | 8 2021 Cross Ref properties for a fractional and Applied Analysis, Vol. No. 3 | 13 May 2022 Cross Ref Fractional Lévy motion with for and analysis of Vol. | 1 2022 Cross Ref random in Review E, Vol. No. 6 | 27 June 2022 Cross Ref of of fractional Brownian Review E, Vol. No. 6 | 30 June 2022 Cross Ref of for fractional impulsive differential equations driven by fractional Brownian and Stochastic Vol. 0, No. 0 | 31 May 2022 Cross Ref of fractional stochastic differential equation with and fractional Brownian Vol. | 30 May 2022 Cross Ref the of scales in and Planning B: Urban Analytics and City Science, Vol. 11 | May 2022 Cross Ref the of on of International Conference on and | 23 May 2022 Cross Ref the of in Multivariate by in the Wavelet 2022 - 2022 IEEE International Conference on and Signal | 23 May 2022 Cross Ref estimation for the model driven by the complex fractional Brownian Vol. No. 4 | 28 July 2021 Cross Ref Anomalous diffusion and memory in Computational Biology, Vol. 18, No. 5 | 18 May 2022 Cross Ref OF OF A | 13 May 2022 Cross Ref On the of Vol. 10, No. 9 | 22 April 2022 Cross Ref Convergence of for for with of Computing, Vol. No. 2 | 21 March 2022 Cross Ref Entropy of in a Review E, Vol. No. 5 | 2 May 2022 Cross Ref Analysis of during 26 August Vol. 24, No. 5 | 14 May 2022 Cross Ref stability of stochastic A and Dynamics, Vol. 22, No. | 18 April 2022 Cross Ref behavior in a model with A, Vol. | 1 May 2022 Cross Ref Asymptotic for driven by fractional Brownian motion in the of Mathematical Analysis and Applications, Vol. No. 1 | 1 May 2022 Cross Ref Generalized and rough Ornstein–Uhlenbeck Vol. | 30 April 2022 Cross Ref The the distribution of processes for the estimation of the Sciences Journal, Vol. No. 6 | 12 April 2022 Cross Ref and Application of Some Fractional Driven by Fractional Economics, Vol. 2 | April 2022 Cross Ref for processes and to Vol. No. 4 | 1 March 2022 Cross Ref Stochastic with to fractional processes in of Analysis, Vol. No. 8 | 1 2022 Cross Ref of and in Hurst exponents from spectral analysis of atomic force microscopy topographic Science, Vol. | 1 2022 Cross Ref in Distribution to Stochastic Driven by a Fractional Brownian Journal of Mathematics, Vol. No. 2 | 21 2022 Cross Ref a Under Random and Stochastic and Transactions on Science and Engineering, Vol. No. 2 | 1 2022 Cross Ref A new fractional based on nonlinear structure to systems with and of and Vol. No. | 30 January 2021 Cross Ref and The Transactions on and Systems, Vol. No. 2 | 1 2022 Cross Ref Analysis on with of and Fractional, Vol. 6, No. 4 | 14 April 2022 Cross Ref The of the Fractional and Fractional, Vol. 6, No. 4 | 15 April 2022 Cross Ref A and for complex Review E, Vol. No. 4 | 18 April 2022 Cross Ref of under in Review E, Vol. No. 4 | April 2022 Cross Ref theory of of an Review A, Vol. No. 4 | 26 April 2022 Cross Ref method for model in fractal Solitons & Fractals, Vol. | 1 2022 Cross Ref Time fractional equation with a based fractional Solitons & Fractals, Vol. | 1 2022 Cross Ref stochastic and of with complex in Applied Mechanics and Engineering, Vol. | 1 2022 Cross Ref OF Journal, Vol. No. 2 | 18 August 2022 Cross Ref The of of Fractional by in Vol. 2 | 24 March 2022 Cross Ref Bayesian of scaled fractional Brownian motionJournal of Physics A: Mathematical and | 24 March 2022 Cross Ref Anomalous diffusion: fractional Brownian motion fractional motionJournal of Physics A: Mathematical and Theoretical, Vol. 55, No. 11 | 23 2022 Cross Ref process with noise as a anomalous diffusion of Physics A: Mathematical and | 8 March 2022 Cross Ref by and Analysis and Vol. | 4 March 2022 Cross Ref Stochastic for the stochastic differential equations with & Probability Letters, Vol. | 1 Mar 2022 Cross Ref Multivariate range A: Statistical Mechanics and its Applications, Vol. | 1 Mar 2022 Cross Ref the memory for and time with Vol. No. 3 | 31 January 2022 Cross Ref for the Fractional Ornstein–Uhlenbeck of Vol. No. 1 | 22 October 2020 Cross Ref Properties of a Generalized Fractional Brownian of Vol. No. 1 | 9 January 2021 Cross Ref The for Time of Stochastic Vol. 10, No. 3 | 23 2022 Cross Ref A for Long in Higher Vol. 10, No. 5 | 24 2022 Cross Ref The of time Journal of Statistics, Vol. No. 1 | 14 August 2021 Cross Ref Estimation on of time generalized Dynamics, Vol. No. 4 | 12 January 2022 Cross Ref of the in the of fields by the of the Vol. | 1 Mar 2022 Cross Ref Statistical of nonlinear time and application to Review Research, Vol. 4, No. 1 | 17 March 2022 Cross Ref Price Modeling of under for Vol. 13, No. 3 | 18 March 2022 Cross Ref and in Advances of Physical Sciences, Vol. 06 | 27 April 2022 Cross Ref of of under fractional Brownian motionStatistics & Probability Letters, Vol. | 1 Mar 2022 Cross Ref Fractional and Statistical An of the Indian of Science, Vol. 29 | 24 2022 Cross Ref diffusion with stochastic of Physics A: Mathematical and Theoretical, Vol. 55, No. 7 | 28 January 2022 Cross Ref On the fractional stochastic for random Analysis and Applications, Vol. | 2 2022 Cross Ref of and Systems to
Describing the distribution of disease between different populations and over time has been a highly successful way of devising hypotheses about causation and for quantifying the potential for preventive activities.1 Statistical data are also essential components of disease surveillance programs. These play a critical role in the development and implementation of health policy, through identification of health problems, decisions on priorities for preventive and curative programs and evaluation of outcomes of programs of prevention, early detection/screening and treatment in relation to resource inputs. Over the last 12 years, a series of estimates of the global burden of cancer have been published in the International Journal of Cancer.2-6 The methods have evolved and been refined, but basically they rely upon the best available data on cancer incidence and/or mortality at country level to build up the global picture. The results are more or less accurate for different countries, depending on the extent and accuracy of locally available data. This “data-based” approach is rather different from the modeling method used in other estimates.7-10 Essentially, these use sets of regression models, which predict cause-specific mortality rates of different populations from the corresponding all-cause mortality.11 The constants of the regression equations derive from datasets with different overall mortality rates (often including historic data from western countries). Cancer deaths are then subdivided into the different cancer types, according to the best available information on relative frequencies. GLOBOCAN 2000 updates the previously published data-based global estimates of incidence, mortality and prevalence to the year 2000.12 The data sources that have been used to build up the global estimates are as follows. Incidence, the number of new cases occurring, can be expressed as the annual number of cases (the volume of new patients presenting for treatment) or as a rate per 100,000 persons per year. Incidence data are produced by population-based cancer registries.13 Registries may cover national populations or, more often, certain regions. In developing countries in particular, coverage is often confined to the capital city and its environs. It was estimated that, in 1990, about 18% of the world population were covered by registries, 64% of developed countries and 5% of developing countries, although the situation is improving each year. The most recent volume of “Cancer Incidence in Five Continents” (CI5) contains comparable incidence information from 150 registries in 50 countries, primarily over the period 1988–1992.14 Survival statistics are also produced by cancer registries by the follow-up of registered cancer cases. Population-based figures are published by registries in many developed countries, for example, the SEER program covering 10% of the U.S. population15 and the EUROCARE II project, including 17 countries of Europe.16 Survival data from populations of China, the Philippines, Thailand, India and Cuba have been published by Sankaranarayanan et al.17 Mortality is the number of deaths occurring and the mortality rate the number of deaths per 100,000 persons per year. It is the product of incidence and fatality (the inverse of survival) of a given cancer. Mortality rates measure the average risk to the population of dying from a specific cancer, while fatality (1-survival) represents the probability that an individual with cancer will die from it. Mortality data are derived from vital registration systems, where the fact and “underlying” cause of death are certified, usually by a medical practitioner. Their great advantage is comprehensive coverage and availability. By 1990, about 42% of the world population was covered by vital registration systems producing mortality statistics on cancer. Not all are, however, of the same quality in all countries. National-level statistics are collated and made available by the World Health Organiztion (http://www-dep.iarc.fr/dataava/globocan/who.htm), although for some countries coverage of the population is manifestly incomplete (so that the so-called mortality rates produced are implausibly low) and in others, quality of cause of death information is poor. Frequency data, e.g., case series from hospitals and pathology laboratories, provide an indication of the relative importance of different cancers in a country or region in the absence of a population-based registry and mortality statistics. There are problems in extrapolating the results to the general population, since such series are subject to various forms of selection bias. Such data are generally published locally or in journal articles, although a few compendia are available.18, 19 Prevalence is the proportion of a population that has the disease at a given point in time.20 For many diseases (e.g., hypertension, diabetes), prevalence usefully describes the number of individuals requiring care. For cancer, however, many persons diagnosed in the past have been “cured”—they no longer have an excess risk of death (although some residual disability may be present, for example, following a resective operation). A straightforward comparison of need for cancer services can be made using partial prevalence, cases diagnosed within 1, 3 and 5 years, to indicate the numbers of persons undergoing initial treatment (cases within 1 year of diagnosis), clinical follow-up (within 3 years) or not considered “cured” (before 5 years). Patients alive 5 years after diagnosis are usually considered cured since, for most cancers, the death rates of such patients are similar to those in the general population. The methods used to produce the estimates are summarised in several recent articles.5, 6, 21, 22 The “Help” option of GLOBOCAN 2000 lists the sources of data and methods used for each country. National incidence data from good-quality cancer registries. National mortality data, with estimation of incidence using sets of regression models specific for site, sex and age, derived from local cancer registry data (incidence plus mortality). Local (regional) incidence data from 1 or more regional cancer registries within a country. When there are several cancer registries in the country, their incidence rates must be combined into a common set of values by some weighted average. Local mortality data from some sort of sample survey of deaths, converted to incidence using specific models. Frequency data. For several developing countries, only data on the relative frequency of different cancers (by age and sex) are available. These are applied to an estimated “all sites” incidence rate, derived from existing cancer registry results, in 7 world regions (Eastern Africa, Middle Africa, Northern Africa, Southern Africa, Western Africa, Middle East and Other Oceania). No data. The country-specific rates are those of the corresponding world area (calculated from the other countries for which estimates could be made). There are few large countries that fall into this category. Those with a population greater than 10 million were Morocco, Afghanistan, Nepal, Sri Lanka, Mozambique, Madagascar and Yemen. National mortality rates, with for some countries a correction factor applied to account for known and quantified underreporting of deaths. Rates for missing sites were computed using proportions from mortality files provided by cancer registries. When no national mortality data are available, local (regional) mortality rates derived from the data of 1 or more cancer registries covering a part of a country (state, province, etc.) were used. When mortality data were unavailable or known to be of poor quality, mortality was estimated from incidence, using country/region-specific survival (see prevalence data). In the absence of any data, country-specific rates are calculated from the average of those of neighbouring countries in the same regions. Estimates of partial prevalence in each country were derived by combining the annual number of new cases and the corresponding probability of survival by time. For example, 1-year prevalence at a fixed point in mid-2000 was estimated from the number of new cases in 2000 multiplied by the probability of surviving at least 6 months, and 3-year prevalence sums the numbers alive at 0.5, 1.5 and 2.5 years. Relative survival data were obtained from the sources cited above and converted to observed survival using “normal” mortality probability (derived from the corresponding life tables). The shape of the survival curve from 0 to 5 years postdiagnosis was assumed to follow a Weibull distribution.22 GLOBOCAN 2000 presents incidence, mortality and prevalence data for 5 broad age groups (0–14, 15–44, 45–54, 55–64 and 65 and over) and sex for all countries of the world for 24 different types of cancer. Since cancer data are collected and compiled sometime after the events to which they relate, the most recent statistics available are from periods from 3–10 years earlier. The actual number of cancer cases, deaths and prevalent cases are calculated by applying these rates to the estimated world population for 2000, obtained from the most recent projections prepared by the United Nations Population Division.23 On the CD-ROM are computer programs to analyse and present the cancer database. The database itself may be downloaded from the Internet (http://www-dep.iarc.fr/globocan/globocan.htm). This site contains the most recently available estimates of the incidence and mortality rates in different countries worldwide. GLOBOCAN 2000 can present the statistics described at any level of geographical aggregation and in tabular or graphical format (maps, bar charts, age-specific curves and pie charts). Some examples of these graphical presentations are shown on the cover of this issue. Tabulations of numbers and rates may also be displayed and printed. Incorporation of population projections for 5-year intervals, from 2005 to 2050,23 allows GLOBOCAN 2000 to be used to prepare projections of future burden, assuming current rates of incidence and mortality, or incorporating age/sex-specific rates of change in the rates. Table I shows the most basic summary data of all—the global numbers of cases, deaths and prevalent cancers (within 5 years of diagnosis) by cancer site in males, females and both sexes. There are an estimated 10.1 million new cases, 6.2 million deaths and 22.4 million persons living with cancer in the year 2000. No attempt has been made to estimate incidence or mortality of nonmelanoma skin cancer because of the difficulties of measurement and consequent lack of data. The total “All Cancer” therefore excludes such tumours. The 2000 estimate represents an increase of around 22% in incidence and mortality since our most recent comprehensive estimates (for 1990). Lung cancer is the main cancer in the world today, whether considered in terms of numbers of cases (1.2 million) or deaths (1.1 million), because of the high case fatality (ratio of mortality:incidence = 0.9). However, breast cancer, although it is the second most common cancer overall (1.05 million new cases) ranks much less highly (5th) as a cause of death because of the relatively favourable prognosis (ratio of mortality:incidence = 0.4). Colon plus rectum is third in importance in terms of new cases (945,000 cases, 492,000 deaths), and stomach cancer (876,000 cases, 647,000 deaths) fourth. In terms of prevalence, the most common cancers are breast (3.9 million breast cancer cases), colorectal cancers (2.4 million) and prostate (1.6 million). The ratio between prevalence and incidence is an indicator of prognosis. This explains why breast cancer appears as the most prevalent cancer in the world, despite there being fewer new cases than for lung cancer, for which the outlook is considerably poorer. Table II shows incidence rates for all cancers (excluding skin) by world area and sex. Two indices are used, the age standardized rate per 100,000 (standardized to the world standard population) and the cumulative rate (percent), from birth to age 65. Both of these indicators allow comparisons between populations that are not influenced by differences in their age structures. Age standardized rates in developed countries are about twice those in developing countries; the differential is less for the cumulative rate, which ignores disease rates in the 65 and over age groups. On average, worldwide, there is about a 10% chance of getting a cancer before age 65. Incidence (and mortality) rates are highest in North America, Australia/New Zealand and Western Europe, and lowest in parts of Africa. This overall risk is, of course, dependent upon the contributions of different types of cancer. For example, in West Africa, incidence of almost all cancers is low (except for cervix cancer in women and liver cancer in men). This contrasts with Southern Africa, which has, in addition, high rates of lung and oesophagus cancer, and with East Africa, with high rates of AIDS-related tumours, notably Kaposi's sarcoma. The statistics used to assess the importance (burden) of cancer and of different types of cancer in the population either quantify the disease itself (the “need” for services) or the demand that it places upon them.24 Incidence rates provide a measure of the risk of developing specific cancers in different populations. Changes in incidence are the appropriate indicator of the impact of primary prevention strategies. Mortality rates are sometimes used as a convenient proxy measure of the risk of acquiring the disease (incidence) when comparing different groups, since they may be more generally available. However, this use assumes equal survival in the populations being compared, and this assumption may well be incorrect, for example, there are well-documented differences between countries. Mortality does provide an unambiguous measure of the outcome or impact of cancer and, used in conjunction with data on incidence, is the index of choice for the evaluation of the effects of early diagnosis or treatment. Prevalence, as the number of persons ever diagnosed with cancer (lifetime prevalence), does not have much apparent utility. The data can be derived from cancer registries that have very long-term registration of cases and complete follow-up for vital status over many years.25, 26 Population surveys are another approach, although they underestimate true prevalence.27 In the absence of complete data, an estimate can be prepared using models that incorporate longtime series of incidence and survival.28, 29 Other workers have attempted to define the proportion and timing of “cure” for different cancers, so that only patients not cured are considered prevalent.30 The data needed for such calculations are rarely available, however, and, for international comparisons, a simpler approach is needed. Partial prevalence, as estimated in GLOBOCAN, as well as approximating the numbers of patients under treatment or follow-up, does not require long time series of incidence or survival data (or a further set of assumptions required to estimate them). Compound indicators, which use information on the duration or severity of disease, have a genuine utility in setting priorities within health-care systems. They include person-years of life lost (how many years of normal life span are lost due to deaths from cancer)31 and disability or quality-adjusted life-years lost.32, 33 The latter measures require that a numerical score is given to the years lived with a reduced quality of life between diagnosis and death (where quality = 0) or cure (quality = 1). The problem with such indicators, however, is that there is simply insufficient quantitative information on quality or disability following a cancer diagnosis in different cultures (or countries) worldwide to permit calculation of valid comparative statistics. The GLOBOCAN estimates of incidence, mortality and (5-year) prevalence help to define priorities for cancer control program (prevention and treatment, aided by early detection, if appropriate). For countries with well-established sources of data, changes in the estimates over time indicate progress against cancer. Incidence trends can monitor the success of prevention and the success of treatment (resulting from earlier diagnosis or more effective therapies). In addition, the geographic patterns of cancer internationally serve one of the classic roles of descriptive epidemiology: observing whether the distribution of specific cancers follows the patterns expected from the distribution of known risk factors between populations or whether there are apparent anomalies that merit further investigation. GLOBOCAN 2000 incorporates the best currently available national statistics, but as information systems extend to all countries of the world and improve their coverage and accuracy, we expect that our knowledge of the world cancer burden will improve and so too will our ability to mount effective strategies against it.
Medical educators attempt to create reliable and valid tests and questionnaires in order to enhance the accuracy of their assessment and evaluations. Validity and reliability are two fundamental elements in the evaluation of a measurement instrument. Instruments can be conventional knowledge, skill or attitude tests, clinical simulations or survey questionnaires. Instruments can measure concepts, psychomotor skills or affective values. Validity is concerned with the extent to which an instrument measures what it is intended to measure. Reliability is concerned with the ability of an instrument to measure consistently.1 It should be noted that the reliability of an instrument is closely associated with its validity. An instrument cannot be valid unless it is reliable. However, the reliability of an instrument does not depend on its validity.2 It is possible to objectively measure the reliability of an instrument and in this paper we explain the meaning of Cronbach’s alpha, the most widely used objective measure of reliability. Calculating alpha has become common practice in medical education research when multiple-item measures of a concept or construct are employed. This is because it is easier to use in comparison to other estimates (e.g. test-retest reliability estimates)3 as it only requires one test administration. However, in spite of the widespread use of alpha in the literature the meaning, proper use and interpretation of alpha is not clearly understood. 2, 4, 5 We feel it is important, therefore, to further explain the underlying assumptions behind alpha in order to promote its more effective use. It should be emphasised that the purpose of this brief overview is just to focus on Cronbach’s alpha as an index of reliability. Alternative methods of measuring reliability based on other psychometric methods, such as generalisability theory or item-response theory, can be used for monitoring and improving the quality of OSCE examinations 6-10, but will not be discussed here. What is Cronbach alpha? Alpha was developed by Lee Cronbach in 195111 to provide a measure of the internal consistency of a test or scale; it is expressed as a number between 0 and 1. Internal consistency describes the extent to which all the items in a test measure the same concept or construct and hence it is connected to the inter-relatedness of the items within the test. Internal consistency should be determined before a test can be employed for research or examination purposes to ensure validity. In addition, reliability estimates show the amount of measurement error in a test. Put simply, this interpretation of reliability is the correlation of test with itself. Squaring this correlation and subtracting from 1.00 produces the index of measurement error. For example, if a test has a reliability of 0.80, there is 0.36 error variance (random error) in the scores (0.80×0.80 = 0.64; 1.00 – 0.64 = 0.36).12 As the estimate of reliability increases, the fraction of a test score that is attributable to error will decrease.2 It is of note that the reliability of a test reveals the effect of measurement error on the observed score of a student cohort rather than on an individual student. To calculate the effect of measurement error on the observed score of an individual student, the standard error of measurement must be calculated (SEM).13 If the items in a test are correlated to each other, the value of alpha is increased. However, a high coefficient alpha does not always mean a high degree of internal consistency. This is because alpha is also affected by the length of the test. If the test length is too short, the value of alpha is reduced.2, 14 Thus, to increase alpha, more related items testing the same concept should be added to the test. It is also important to note that alpha is a property of the scores on a test from a specific sample of testees. Therefore investigators should not rely on published alpha estimates and should measure alpha each time the test is administered.14 Use of Cronbach’s alpha Improper use of alpha can lead to situations in which either a test or scale is wrongly discarded or the test is criticised for not generating trustworthy results. To avoid this situation an understanding of the associated concepts of internal consistency, homogeneity or unidimensionality can help to improve the use of alpha. Internal consistency is concerned with the interrelatedness of a sample of test items, whereas homogeneity refers to unidimensionality. A measure is said to be unidimensional if its items measure a single latent trait or construct. Internal consistency is a necessary but not sufficient condition for measuring homogeneity or unidimensionality in a sample of test items. 5, 15 Fundamentally, the concept of reliability assumes that unidimensionality exists in a sample of test items16 and if this assumption is violated it does cause a major underestimate of reliability. It has been well documented that a multidimensional test does not necessary have a lower alpha than a unidimensional test. Thus a more rigorous view of alpha is that it cannot simply be interpreted as an index for the internal consistency of a test. 5, 15, 17 Factor Analysis can be used to identify the dimensions of a test.18 Other reliable techniques have been used and we encourage the reader to consult the paper “Applied Dimensionality and Test Structure Assessment with the START-M Mathematics Test” and to compare methods for assessing the dimensionality and underlying structure of a test.19 Alpha, therefore, does not simply measure the unidimensionality of a set of items, but can be used to confirm whether or not a sample of items is actually unidimensional.5 On the other hand if a test has more than one concept or construct, it may not make sense to report alpha for the test as a whole as the larger number of questions will inevitable inflate the value of alpha. In principle therefore, alpha should be calculated for each of the concepts rather than for the entire test or scale. 2, 3 The implication for a summative examination containing heterogeneous, case-based questions is that alpha should be calculated for each case. More importantly, alpha is grounded in the ‘tau equivalent model’ which assumes that each test item measures the same latent trait on the same scale. Therefore, if multiple factors/traits underlie the items on a scale, as revealed by Factor Analysis, this assumption is violated and alpha underestimates the reliability of the test.17 If the number of test items is too small it will also violate the assumption of tau-equivalence and will underestimate reliability.20 When test items meet the assumptions of the tau-equivalent model, alpha approaches a better estimate of reliability. In practice, Cronbach’s alpha is a lower-bound estimate of reliability because heterogeneous test items would violate the assumptions of the tau-equivalent model.5 If the calculation of “standardised item alpha” in SPSS is higher than “Cronbach’s alpha”, a further examination of the tau-equivalent measurement in the data may be essential. Numerical values of alpha As pointed out earlier, the number of test items, item inter-relatedness and dimensionality affect the value of alpha.5 There are different reports about the acceptable values of alpha, ranging from 0.70 to 0.95. 2, 21, 22 A low value of alpha could be due to a low number of questions, poor inter-relatedness between items or heterogeneous constructs. For example if a low alpha is due to poor correlation between items then some should be revised or discarded. The easiest method to find them is to compute the correlation of each test item with the total score test; items with low correlations (approaching zero) are deleted. If alpha is too high it may suggest that some items are redundant as they are testing the same question but in a different guise. A maximum alpha value of 0.90 has been recommended.14 Summary High quality tests are important to evaluate the reliability of data supplied in an examination or a research study. Alpha is a commonly employed index of test reliability. Alpha is affected by the test length and dimensionality. Alpha as an index of reliability should follow the assumptions of the essentially tau-equivalent approach. A low alpha appears if these assumptions are not meet. Alpha does not simply measure test homogeneity or unidimensionality as test reliability is a function of test length. A longer test increases the reliability of a test regardless of whether the test is homogenous or not. A high value of alpha (> 0.90) may suggest redundancies and show that the test length should be shortened.
The current period of medicine using digital technology for patient care presents a new level of integration of monitoring devices with the cloud computing environment that enables the collection, storage and access to data in ways that were never possible earlier. As the obvious part of this development, it is worth noting that the objective of such innovation is mostly on the integrity of data, provenance and security. Data integrity from as well as security of the Internet connected healthcare devices should be assured in the first place to keep patient safety and protect data privacy along with improve data-based decision-making. The centralized system and crowded nature of the current equipment are susceptible to single point of failure, data breach and potential manipulations of data, which raise questions and create doubts with regards data management processes pertaining to medical device systems. This work is addressed to the analysis of a novel security system based on blockchain that guarantees the implementation of a high performance with the solution of two medical device integrity and provenance safety issues in the cloud ecosystem. Fundamentally differentiating from the centralized systems that exist today, blockchain technology that is based on distributed database architectures, immutable logs, and consensus mechanisms provides for a new way to bring reliability and traceability to the entire medical device data chain. The suggested procedure is based on properties of blockchain technology. Such a solution can help to provide a clear and secure audit trail for medical devices. Storing, securing and accessing the device data can be carried out credibly, maintaining these data’s integrity and provenance. Ultimately, the solution, rely on the implementation of smart contracts, cryptocurrency processes, and the confidentiality and privacy of data, can be the answer which make up the practice of secure data sharing, data accessing and complying with regulations. The journal creates a modular system combining Medical devices, a cloud platform, and Blockchain solution. The architecture is intended to display the blockchain network's essential components, data validation and access control, and secure data storage mechanisms. Furthermore, the recommended solution implies state-of- the-art security tools, such as data encryption, access control, and abidance by regulatory systems, including HIPAA and GDPR. Implementation of an actual scenario of the proof-of-concept and performance evaluation are done to show the efficiency and performance of the blockchain-based solution provided. The results suggest that the proposed solution can establish the data reliability level, record all the various versions of modifications, and strengthen the security and transparency of medical device data processing in cloud computing. Through the exploration of the applications of blockchain for medical data management that this study proposes, we are laying the foundations of a future healthcare environment, which is expected to be more secure and trustworthy, where the sensor data of medical devices can be reliably controlled and accessed without jeopardizing the patient's safety or data privacy. To a great extent, the suggested solution can contribute to building trust in the digital tools utilized in health care, leading to more well-informed clinical decisions and ultimately improving the patients' results.
Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users.Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement--a reporting guideline published in 1999--there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions.The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.
This is a literature review paper covering state-of-the-art sleep technologies to measure sleep and clinical sleep disorders. This paper addresses an interdisciplinary audience from a variety of subdomains in engineering and medicine. We reviewed 120 scientific papers, 15 commercial mobile apps, and 4 commercial devices. We selected the papers from scientific publishers including Institute of Electrical and Electronics Engineers (IEEE), Nature, Association for Computing Machinery (ACM), Proceedings of Machine Learning Research, Journal of Informatics in Health and Biomedicine, Plos One, PubMed, and Elsevier and Nature digital libraries. We used Google Scholar with keywords including “sleep monitoring”, “sleep monitoring technologies”, “non-contact sleep monitoring”, “mobile apps for sleep monitoring”, “AI in sleep technologies”, and “automated sleep staging.” The manuscript reviews sleep technologies, including sleep lab technologies such as polysomnography and consumer sleep technologies categorized as ambient room sensors, wearable sensors, bed sensors, mobile apps, and artificial intelligence. We primarily focused on validation and comparison studies of the reviewed technologies. The manuscript also provides an overview of several clinical datasets for sleep staging and taxonomizes the different learning methods. Finally, the manuscript offers our insights and recommendations about the application of the reviewed sleep technologies.
BACKGROUND: Traditional approaches to mechanical ventilation use tidal volumes of 10 to 15 ml per kilogram of body weight and may cause stretch-induced lung injury in patients with acute lung injury and the acute respiratory distress syndrome. We therefore conducted a trial to determine whether ventilation with lower tidal volumes would improve the clinical outcomes in these patients. METHODS: Patients with acute lung injury and the acute respiratory distress syndrome were enrolled in a multicenter, randomized trial. The trial compared traditional ventilation treatment, which involved an initial tidal volume of 12 ml per kilogram of predicted body weight and an airway pressure measured after a 0.5-second pause at the end of inspiration (plateau pressure) of 50 cm of water or less, with ventilation with a lower tidal volume, which involved an initial tidal volume of 6 ml per kilogram of predicted body weight and a plateau pressure of 30 cm of water or less. The primary outcomes were death before a patient was discharged home and was breathing without assistance and the number of days without ventilator use from day 1 to day 28. RESULTS: The trial was stopped after the enrollment of 861 patients because mortality was lower in the group treated with lower tidal volumes than in the group treated with traditional tidal volumes (31.0 percent vs. 39.8 percent, P=0.007), and the number of days without ventilator use during the first 28 days after randomization was greater in this group (mean [+/-SD], 12+/-11 vs. 10+/-11; P=0.007). The mean tidal volumes on days 1 to 3 were 6.2+/-0.8 and 11.8+/-0.8 ml per kilogram of predicted body weight (P<0.001), respectively, and the mean plateau pressures were 25+/-6 and 33+/-8 cm of water (P<0.001), respectively. CONCLUSIONS: In patients with acute lung injury and the acute respiratory distress syndrome, mechanical ventilation with a lower tidal volume than is traditionally used results in decreased mortality and increases the number of days without ventilator use.
The ESC Guidelines represent the views of the ESC and were produced after careful consideration of the scientific and medical knowledge and the evidence available at the time of their publication.The ESC is not responsible in the event of any contradiction, discrepancy and/or ambiguity between the ESC Guidelines and any other official recommendations or guidelines issued by the relevant public health authorities, in particular in relation to good use of healthcare or therapeutic strategies.Health professionals are encouraged to take the ESC Guidelines fully into account when exercising their clinical judgment, as well as in the determination and the implementation of preventive, diagnostic or therapeutic medical strategies; however, the ESC Guidelines do not override, in any way whatsoever, the individual responsibility of health professionals to make appropriate and accurate decisions in consideration of each patient's health condition and in consultation with that patient and, where appropriate and/or necessary, the patient's caregiver.Nor do the ESC Guidelines exempt health professionals from taking into full and careful consideration the relevant official updated recommendations or guidelines issued by the competent public health authorities, in order to manage each patient's case in light of the scientifically accepted data pursuant to their respective ethical and professional obligations.It is also the health professional's responsibility to verify the applicable rules and regulations relating to drugs and medical devices at the time of prescription.