Puberty is a critical period of development during which nutritional exposures are known to shape long-term health and the risk of chronic diseases. Current dietary assessment methods have limitations for use in large cohorts of adolescent populations. We aimed to evaluate the relative validity of Keenoa (not an acronym), an artificial intelligence-enhanced image-assisted mobile application, against the validated Automated Self-Administered 24 h recall (ASA24)-Canada web-based platform, among adolescents in the CHILD Cohort Study. Using a randomized crossover design, participants aged 11-15 years old completed three days (two weekdays and one weekend day) of both Keenoa food tracking and ASA24 food recalls. Differences in reported intakes were analyzed using paired t-tests or Wilcoxon signed-rank test and deattenuated correlations by Spearman's coefficient. Agreement and bias were determined using Bland-Altman's test, and inter-quartile cross-classification agreement was assessed using weighted Cohen kappa. This study included 141 participants with a mean age of 12.2 ± 0.8 years; of them 74 (52.5 %) males; and 88 (62.4 %) identified as Caucasian/White. Mean ± SD reported energy intakes (kcal/d) were 1976 ± 451 and 1978 ± 425, with ASA24 and Keenoa, respectively (P = 0.95). Mean reported macronutrient, iron, and potassium intakes did not significantly differ between tools. Reported fiber intake was higher, while sodium, calcium and vitamin D intakes were lower with Keenoa compared to ASA24 (P values < 0.001-0.025). Deattenuated correlations between tools ranged from r = 0.77 to 1.00 (all p< 0.01) and weighted Cohen κ scores ranged from 0.22 to 0.42 (all p < 0.001). Among all participants, 121 (85.8 %) and 78 (55.3 %) completed all 3 requested days with Keenoa and ASA24, respectively (P< 0.01). The artificial intelligence-enhanced image-assisted Keenoa mobile application showed strong to moderate relative validity against ASA24 for energy, macronutrient, potassium and iron intakes. Vitamin D, calcium, fiber and sodium showed limited relative agreement based on mean differences. This novel tool may facilitate dietary assessment and reduce attrition bias in cohort studies. Future validation using objective biomarker measures will help establish true validity.
Accurate measurement of resected colorectal polyps is essential for clinical management, research, and the development of artificial intelligence-based size estimation systems. Despite widespread use of caliper-based measurement for specimen sizing, formal validation against a reference standard is lacking. This study aimed to validate caliper-based measurement of resected small and diminutive colorectal polyps against high-resolution digital microscopy, a previously validated reference method. At the Centre hospitalier de l'Université de Montréal, 143 polyps from 92 patients were measured immediately after resection using vernier digital calipers in the endoscopy suite. Independent measurements were subsequently obtained using high-resolution digital microscopy under blinded conditions. Agreement between methods was assessed using bias analysis, Bland-Altman limits of agreement, intraclass correlation coefficient (ICC), and categorical size concordance. Caliper-based measurements demonstrated a mean bias of -0.22 mm (95% CI: -0.34 to -0.11; P < .001) relative to the reference standard. The noninferiority hypothesis with a 0.5-mm margin was not rejected (lower 95% CI > -0.5 mm). Bland-Altman's limits of agreement were -1.57 to 1.12 mm, and the ICC was 0.88 (95% CI: 0.82-0.92). Correct categorical classification occurred in 94.4% of cases (95% CI: 0.89-0.97; κ = 0.81). Caliper-based measurement provides accurate and reproducible estimates of polyp size when compared with digital microscopy, supporting its use for clinical and research applications requiring direct specimen measurement.
In response to the growing number of hospital bankruptcies across the United States, this study sought to develop a predictive and interpretable model tailored specifically to the healthcare industry. Utilizing a longitudinal dataset of 3,091 short-term acute care hospitals from 2008 to 2021, we evaluated and compared traditional bankruptcy prediction models-Altman's Z'', Ohlson's O-score, and Zmijewski's model-against a newly developed hospital-specific logistic regression model (BRKFSST). We incorporated over 30 financial and hospital-level variables, including quality indicators, ownership type, and market characteristics. Unlike prior models, ours lagged all unknowable variables to ensure true out-of-sample prediction. The BRKFSST model achieved strong performance, with an Area Under the Curve (AUC) of 81.8%, balanced accuracy of 72.2%, and a mean recall of 60.6% across multiple test/train splits, outperforming all benchmark models. Importantly, the model retained interpretability, allowing for the identification of key predictors such as labor compensation ratio, adjusted patient days, and quality ratings. These findings provide actionable insights for hospital leaders and policymakers to identify at-risk institutions and implement early interventions to prevent financial collapse and preserve access to care.
This study aimed to investigate the criterion validity of commonly used devices to assess maximal sprinting speed (MSS) in soccer. Thirty elite youth soccer players completed three trials of a 30-m sprint test to assess MSS. All sprints were simultaneously captured via a radar gun (Stalker ATS II), timing gates (Smartspeed Pro, Fusion Sport), a magnetic timing system (Humotion SmarTracks) and a global navigation satellite system (GNSS) (Kinexon Perform GPS Pro). The radar gun and the GNSS recorded sprinting speed continuously, while the fastest 5-m split during the 30-m sprint was used for the timing gates and the magnetic system. The best trial of the radar gun (i.e. criterion measure) and corresponding values of the other devices were analyzed. Equivalence testing was performed to assess the statistical equivalence of MSS between the radar gun and the three other devices against a difference value of ± 0.36 km/h and Bland & Altman's 95% limits of agreement (LoA) were computed to investigate the agreement between MSS results. Differences between GNSS versus radar gun suggested a lack of systematic bias (-0.01 km/h, 95% confidence interval [CI] -0.15 to 0.15 km/h), whereas timing gates-based MSS assessments were prone to larger uncertainty compared to the criterion method (-0.19 km/h, 95% CI: -0.37 to 0.00 km/h) given the pre-defined region of equivalence. The magnetic system (-0.54 km/h; -0.71 to -0.37 km/h) overestimated MSS compared to the radar gun with mean differences being non-equivalent. Based on the practically important difference bounds of ± 0.36 km/h, the width of the 95% LoA was broad enough to suggest a lack of reasonable agreement for MSS assessment regardless of device of interest (GNSS: -0.79 to 0.78 km/h, timing gates: -0.79 to 1.16 km/h, magnetic system: -0.24 to 1.32 km/h). While our results suggested a lack of systematic bias for the investigated GNSS and the timing gates when compared against the radar gun for MSS assessment over 30 m in elite youth soccer players on a team level, the width of the 95% LoAs did not indicate reasonable measurement interchangeability on an individual level. Based on the present results, we do not recommend using the magnetic system for both group and individual analyses in this population.
The iMTA productivity cost questionnaire (iPCQ) has been recommended as a measurement tool for productivity cost, however, its use in routine care is hindered by the length of this questionnaire (18 questions). This study developed and tested a short-form (SF-) iPCQ. A secondary analysis of the Groningen Spine Cohort's baseline data from patients with low back pain referred for tertiary care was performed. Six SFs were evaluated against the comprehensive iPCQ. Spearman correlation (r), intraclass correlation coefficient (ICC, agreement), standard error of measurement (SEM), and Bland-Altman's plot tested the congruence of the SFs with the comprehensive iPCQ. The sample consisted of 1220 patients with low back pain. The SF version with the highest correlation (SF-3; 7 items) with the comprehensive iPCQ had r = 0.99, ICC = 0.99, SEM = 295, while the SF with the least number of items (SF-6; 5 items) had r = 0.84, ICC = 0.91, SEM = 2063. The mean productivity cost estimates of SF-3 and SF-6 were €3414 (95% CI: 3036-3791) and €3333 (95% CI: 2970-3696) respectively while that for the comprehensive iPCQ amounted to €3456 (95% CI: 3189-3720). A SF with seven questions was developed with a high agreement with the comprehensive iPCQ. Initial clinimetric testing was satisfactory. Further assessment is recommended.
The Jamar dynamometer is the gold standard to assess hand grip strength, but is expensive. The Camry dynamometer is relatively cost-effective. There is a dearth of literature on Camry's validation in healthy Indian adults, which is important to establish as hand grip is known to vary with age, gender and race. To establish the reliability and validity of the Camry dynamometer in comparison to the Jamar handheld dynamometer among healthy Indian adults in the age group of 20-59 years. Following basic demographics, occupation and hand dominance, three trials of each dynamometer were performed in standardised positions for the non-dominant and dominant hand of each participant and the best value was recorded. A gap of 10 min was provided between the 2 dynamometers. Data was then recorded and analyzed. 120 participants were recruited, with an equal males and females. The mean isometric hand grip strength for the non-dominant hand was 26.71 ± 9.29 kgf, and for the dominant hand was 27.66 ± 9.12 kgf using the Camry hand-held dynamometer, while it was 26.43 ± 9.07 kgf for the non-dominant and 27.37 ± 9.26 kgf for the dominant side using the Jamar Hand Held dynamometer. Data was further analyzed with age and gender stratification. The Camry hand-held device had excellent reliability (ICC>0.97) and good validity with Pearson's correlation index of 0.97 (p < 0.05) for the dominant hand and 0.99 (p < 0.05) for the nondominant hand, and Bland-Altman's graphics showing more than 90 % of measures within confidence limits. Camry digital dynamometer is a reliable and valid device to measure isometric handgrip strength in healthy Indian adults compared to the Jamar hydraulic handgrip dynamometer.
Hearing loss affects approximately 1.5 billion people globally, with a significant proportion unaware of their condition due to inadequate screening. The current standard for diagnosing hearing loss, pure tone audiometry (PTA), faces limitations in accessibility and cost, especially in low-resource settings. Our study aimed to evaluate mobile audiometry (MA) as a self-assessment screening tool for the general public. The study compared audiograms obtained via PTA in a sound-proof room and MA using a smartphone in a physician's office with ambient noise using relatively inexpensive, readily available generic headsets and earphones. MA was a self-assessment test where patients followed instructions from investigators but conducted the test independently under supervision. Each ear was tested separately without masking. Spearman's correlation assessed the association between MA and PTA, and Bland-Altman's analysis evaluated agreement. Diagnostic accuracy, sensitivity, and specificity were calculated using contingency tables. Kappa statistic measured reliability and test-retest reliability was assessed with Intraclass Correlation Coefficient (ICC). The study consisting of 250 participants (110 males and 140 females), with an average age of 43.5 years revealed strong agreement and correlation between audiograms obtained from PTA and MA. The diagnostic accuracy for classifying the degree of hearing loss was moderate, at 70%. MA exhibited high sensitivity (94.51%) and good specificity (70.96%) for screening hearing loss. The reliability of MA is good with a kappa statistic value of 0.659. The test-retest reliability of MA was assessed using ICC which was found to be 0.843. MA could serve as an effective screening tool for hearing loss. Individuals identified with hearing loss through MA could be referred to a physician's office for further evaluation and timely management. However, limitations such as environmental noise and variability in headset quality may affect the accuracy of the results. Further research is needed to address these challenges and improve the reliability of MA.
Acute Febrile Illness (AFI) like Malaria, Dengue, Chikungunya, and Enteric fever still remain the most common cause of seeking healthcare in low-middle-income countries and need to be constantly monitored for any impending outbreak. Digital epidemiology promises to assist traditional health surveillance. The health data (including AFI) collated by Google using specialised platforms like Google Trends (GT) is known to correlate with actual disease trends. The present study thus aims to assess the potential of GT to support routine surveillance system and forecast AFI outbreaks reported through the Indian Integrated Disease Surveillance Programme (IDSP). We utilised Haryana's IDSP portal to retrieve the weekly data of the most commonly reported infectious diseases causing AFI between 2011 and 2020. Internet search trends were downloaded using GT. Descriptive statistics estimated the burden of the AFI and Bland-Altman's plot depicted statistical agreement between the two. We adopted the Box-Jenkins approach to attain the final SARIMA model and explain the time-dependent weekly incidence of AFI. The time series plot of the reported AFI displayed trends. Martin- Bland plots depicted acceptable agreement between two datasets for all Chikungunya and Dengue. Among the models evaluated, the Malaria model [SARIMA(1,1,1)(1,1,1)] demonstrated the best performance with a balanced fit and reasonable accuracy, while the Enteric Fever model [SARIMA(0,1,0)(1,1,1)] exhibited low prediction error but weak seasonal significance. In contrast, the Dengue [SARIMA(1,1,0)(1,1,0)] and Chikungunya [ARIMA(1,0,0)(0,0,0)] models had high forecast errors, limiting their predictive reliability. Overall, GT supplemented the prediction performance of the SARIMA models with adjusted R2 of 46%, 50%, 50%, and 52% compared to the original 43%, 49%, 20%, and 48%. Our study observed modest improvements in GT-based SARIMA forecasting models compared to routine IDSP mechanisms for predicting AFI outbreaks in Haryana, highlighting the potential for further enhancement. As more granular GT data becomes available, its integration with traditional surveillance systems could significantly enhance forecasting accuracy for AFI and other infectious disease outbreaks. At no additional cost to the health system, GT can serve as a valuable, real-time digital epidemiology tool, strengthening public health preparedness and enabling timely interventions for the early containment of emerging diseases.
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Menarche timing may affect female health. While previous studies evaluated self-reported age at menarche reproducibility, they did not assess types of respondents. This study compared the reproducibility of age at menarche among self-responders and proxy respondents and assessed proxy-respondent reproducibility by relationship and survey age. Data on age at menarche reported in both the 1969 and 1978 mail questionnaires among 9,043 females from the Life Span Study cohort of atomic bomb survivors were analyzed. The reproducibility of menarcheal age was assessed by the type of respondents, by proxy's relationship to participant, and by age at the 1969 survey using Bland-Altman's method and the intraclass correlation coefficient (ICC). Reproducibility was moderate (95% limits of agreement, -2.3 to 2.4 years; ICC 0.72; 95% confidence interval, 0.71-0.73). Both self-respondents (N = 6,664) and the total study population (N = 9,043) maintained moderate reproducibility even at older ages. Groups with proxy reports showed lower reproducibility than self-respondents, with spouse proxy reports showing highest reproducibility and parent proxy reports showing lowest reproducibility among proxy reports, although the comparisons are based on different survey ages in 1969. This is the first study to evaluate menarcheal-age reproducibility between self- and proxy-reports using appropriate measures. Mail questionnaires at 9-year interval showed moderate reproducibility across all ages, including elderly self-respondents. Reproducibility varied by the respondent-target relationship, with spouse proxies showing highest and parent proxies showing lowest reproducibility among proxy reports. Additional data are required to establish appropriate methods for handling specific proxy responses.
Financial distress remains a relatively underexplored area in public healthcare, although such failures occur globally, demonstrating that maintaining public health requires strategies to ensure financial stability and the continuous operation of public healthcare organizations. This study aims to assess financial distress and its relationship with hospital-specific governance attributes by examining the case of Greek public hospitals. To achieve this aim, Altman's Z"-score model was applied to the entire range of public hospitals. The attributes investigated included hospital size, location, specialty, and manager gender. All data were retrieved from published financial statements for 2022. The analysis employed descriptive statistics, normality tests, correlations, and non-parametric tests. The findings indicate strong financial viability, reflected in high Z-scores driven by low financial leverage and ample working capital. In addition, both smaller units and women-led hospitals outperformed others in terms of Z-scores. However, heavy reliance on state subsidies, the slow collection of non-current hospital bills, and the rising levels of indebtedness suggest a financial condition substantially weaker than that implied by Z-scores or any other model based solely on financial statement data. Financial distress requires redefinition in the context of public entities, since their closure is not a core strategy. Existing definitions and prediction models fail to account for the support mechanisms that mask poor financial viability, effectively shifting financial distress to key stakeholders such as suppliers and the state owner.
Evaluating fluid responsiveness (FR) is crucial in managing critically ill patients. Measurement of respiratory variations of blood flow (Vpeak) is physiologically sound, but blood flow sampling through the aortic valve (AV-Vpeak) is not always feasible. We assessed the feasibility of suprasternal Vpeak (SS-Vpeak), at ascending or descending aorta level, as alternative to AV-Vpeak. Observational prospective study in spontaneously breathing healthy volunteers. We report the overall feasibility of AV- and SS-Vpeak, and calculated their interchangeability, the mean bias with limits of agreement (LoA) and percentage error (PE). We defined FR as a 10% increase in cardiac output measured non-invasively with finger-cuff method after passive leg raising. We enrolled 67 volunteers; SS-Vpeak was feasible in 65 volunteers (97%), with sampling in the ascending and descending aorta in 22/65 (33.8%) and 43/65 (66.2%) volunteers, respectively. AV-Vpeak was feasible in 64 volunteers (95.5%). When both Vpeak were obtained (n = 62), interchangeability using a 12% cut-off was 67.7% (poor agreement with kappa coefficient 0.19 [-0.02;0.41]). Clinical concordance at ascending aorta level was non-significantly higher (16/22, 73% vs 26/40, 65%; p = 0.583). Prediction of FR with SS-Vpeak using the 12% cut-off was poor: sensitivity 85%; specificity 9%; positive predictive value 82%; negative predictive value 11%. Bland-Altman's analysis revealed a mean bias -2.6% [-4.3%;-1.0%] with LoA ranging from -15.2% [- 18.1%;- 12.4%] to 10.0% [7.2%;12.8%]. The mean PE was 7.87%. We report excellent feasibility for SS-Vpeak, though with moderate interchangeability and accuracy; however, we found poor precision and poor performances in predicting FR in healthy volunteers.
Prejudice against LGBTQ people during their schooling years can be detrimental due to its long-term consequences. This includes the development of beliefs that the world is unsafe, which can perpetuate mental health struggles later in life. Fostering a school environment where LGBTQ people can express their identity can contribute to greater well-being. This qualitative study drew on interviews with 13 school graduates to examine the environmental factors within Australian schools that influenced LGBTQ students' expression of their identity. Drawing on Altman's conceptualization of oppression and liberation, this study found students typically experienced liberation in the form of acceptance and validation within their micro-environment at school. This micro-environment was composed of those close to the student, such as friends, allies, teachers, and other LGBTQ students who provided acceptance and validation, which enabled the student to express their identity regardless of oppression within the broader school environment. Oppression on the other hand originated from the invisibility of LGBTQ identities; the limited representation in curriculum and access to LGBTQ-specific resources and supports; concerns around gendered, gender-neutral, and safe spaces; and limited support from teachers. Based on the findings, implications are drawn to enhance both the micro and macro environment for LGBTQ school students.
Dust collection is essential for tracing lead sources and determining mitigation measures with accurate sampling and analysis. Two different simulated dust mixtures, Pb-contaminated soil and paint of three different lead concentrations, were used to test the comparability of a modified micro-vacuum sampling method to the currently recommended dust wipe method. The standard dust wipes and a modified micro-vacuum method (20 Lpm flow rate, 2 cm length Nalgene Tygon tube inlet, 2 min per 30 cm × 30 cm area) were used to collect dust and subsequent analysis. Bland-Altman's plots indicated very good agreement between methods, with minimal bias and acceptable variability. For Pb-containing soil dust at 1200 and paint dust at 1000 mg kg-1 concentration of Pb, methods did not differ significantly. For lower lead concentration samples, the dust extraction method from vacuum cassettes was negatively affected, resulting in significantly lower lead loadings than the dust wipe method; in follow-up studies in selected samples, sonication facilitated more complete extraction (76%-91%) from vacuum cassettes. Overall, results suggested potential for developing a standardized micro-vacuum method with additional benefits for house dust collection.
Genioplasty is performed as part of orthognathic surgery to correct jaw deformities. This procedure presents challenges in terms of osteosynthesis accuracy. This study aimed to evaluate the precision of preoperative planning in genioplasty using computer-aided design/computer-aided manufacturing (CAD/CAM) with three-dimensional (3D) printable biomaterials and mixed reality (MR) technology with a head-mounted display (Microsoft® HoloLens 2) and a registration marker. Twenty-six patients underwent genioplasty using either only CAD/CAM devices (control group, n=10) or CAD/CAM with additional MR technology (experimental group, n=16). CAD/CAM devices were created based on virtual surgical planning (VSP), and MR holograms created based on VSP data were projected onto the surgical area using Microsoft HoloLens 2. After surgery, the planned model was compared with the postoperative computed tomography (CT) image, measuring the 3D surface and the differences in position and rotation using the root mean square deviation (RMSD) and Bland-Altman's method. Both analyses are blinded. The average 3D surface analysis errors within 2 mm ranged between 62.20-100.00% (control group) and 99.30-100.00% (experimental group), with mean errors of 92.12% and 99.81%, respectively. Errors within 1 mm ranged between 28.50-98.90% (control group) and 55.10-99.6% (experimental group) with mean errors of 67.36% and 85.60%, respectively. The largest RMSDs were 1.20 mm in the anteroposterior direction and 6.78° in pitch orientation for the experimental group and 1.78 mm in the anteroposterior direction and 6.04° in pitch orientation for the control group. A statistically significant difference between the two groups was observed for errors measured within 1 mm (P=0.047) and for yaw (P=0.003). No postoperative complications were observed in either group. Using CAD/CAM with additional MR technology in genioplasty improved the repositioning accuracy of the chin bone fragment and plate placement, with statistically significant improvements in specific spatial directions. This combination of CAD/CAM and MR technology allows for intraoperative spatial verification of fragment movement according to preoperative VSP, which significantly contributes surgical precision.
We explored the feasibility of utilizing immediate changes in flight time-based vertical countermovement jump height as an on-field measure for fatigue-induced decrements in performance. Comparing Inertial Measurement Units (IMUs) worn at five body locations (feet, shorts for thighs and pelvis, waist strap, and thorax in a standard GPS vest) with a force plate as a reference, we enlisted 19 amateur football players who performed a series of 10 maximal 30 m sprints (initiated every minute). Maximal jumps were executed immediately before and after each sprint, with the latter jumps recorded on a force plate integrated into the field. Bland Altman's bias (-0.49 cm) and limits of agreement (1.01 cm) were minimal for the feet IMUs. The thorax IMU had the highest bias (-6.35 cm), but the limits of agreement (2.73 cm) were similar to the other locations. Repeated measures correlations (rmcorr) between force plate and IMUs were excellent for the feet (rmcorr = 0.98) and good for the thorax (rmcorr = 0.86) and other locations except for the waist strap. In the fatigued state, within-session coefficients of variation ranged from 4.0% (pelvis in shorts) to 6.5% (waist strap). These findings suggest that body-worn IMUs possess the potential for a prompt and straightforward on-field vertical jump assessment to monitor acute fatigue.
This study aims to propose a comprehensive alternative to the Bland-Altman plot method, addressing its limitations and providing a statistical framework for evaluating the equivalences of measurement techniques. This involves introducing an innovative three-step approach for assessing accuracy, precision, and agreement between techniques, which enhances objectivity in equivalence assessment. Additionally, the development of an R package that is easy to use enables researchers to efficiently analyze and interpret technique equivalences. Inferential statistics support for equivalence between measurement techniques was proposed in three nested tests. These were based on structural regressions with the goal to assess the equivalence of structural means (accuracy), the equivalence of structural variances (precision), and concordance with the structural bisector line (agreement in measurements obtained from the same subject), using analytical methods and robust approach by bootstrapping. To promote better understanding, graphical outputs following Bland and Altman's principles were also implemented. The performance of this method was shown and confronted by five data sets from previously published articles that used Bland and Altman's method. One case demonstrated strict equivalence, three cases showed partial equivalence, and one showed poor equivalence. The developed R package containing open codes and data are available for free and with installation instructions at Harvard Dataverse at https://doi.org/10.7910/DVN/AGJPZH. Although easy to communicate, the widely cited and applied Bland and Altman plot method is often misinterpreted, since it lacks suitable inferential statistical support. Common alternatives, such as Pearson's correlation or ordinal least-square linear regression, also fail to locate the weakness of each measurement technique. It may be possible to test whether two techniques have full equivalence by preserving graphical communication, in accordance with Bland and Altman's principles, but also adding robust and suitable inferential statistics. Decomposing equivalence into three features (accuracy, precision, and agreement) helps to locate the sources of the problem when fixing a new technique.
In the last decades there is a growing interest in the evaluation of human body composition for being an important part of the integral assessment of individuals. Its use has been extended to different disciplines associated with health care (medicine, nutrition, physiotherapy), and to sports and population fields. Specifically, fat percentage can be related to innumerable diseases. However, there are discrepancies in the results of fat percentage measurement measured by different methods. To evaluate the concordance between two low-cost and easily accessible double indirect methods, which have been used indistinctly in different studies where access to more accurate methods is not available, and to determine fat percentage and its relationship with age, sex, body mass index (BMI), waist circumference, level of physical activity and sedentary hours. Twenty-four persons between 18 and 38 years and 28 between 39 and 59 years from a university community were evaluated. Calculations were made: BMI, fat % was estimated by anthropometry with a digital adipometer (Skyndex System I USA) and by Electrical Bioimpedance Analysis - BIA (Biody Expert ZM II FRA), physical activity level and sedentary hours were determined with the short IPAQ questionnaire. Pearson's correlation coefficient, Bland & Altman's graphical method and Lin's concordance correlation index were calculated. The significance level p<0.05 was estimated. The fat percentage by anthropometry was: 30.5% ±8.5 (18-38 years) 35.0% ±6.7 (39-59 years); by BIA 27.0% ±7.3 (18-38 years) and 29.2% ±7.0 (39-59 years). Both techniques showed good correlation, but low degree of concordance (Lin index less than 0.9) except for the group of young persons with moderate level of physical activity (0.95). The doubly indirect methods used in the study showed strong correlation, but low concordance, so their use is not recommended indistinctly for the follow-up of a particular case. According to the study data for this specific population in young people with moderate physical activity, follow-up could be performed with either of the two methods.
Size-specific dose estimates (SSDE) have been introduced into computed tomography (CT) dosimetry to tailor patients' unique sizes to facilitate accurate CT radiation dose quantification and optimization. The purpose of this study was to develop and validate an automated algorithm for the determination of patient size (effective diameter) and SSDE. A MATLAB platform was used to develop software of algorithms based on image segmentation techniques to automate the calculation of patient size and SSDE. The algorithm was used to automatically estimate the individual size and SSDE of four CT dose index phantoms and 80 CT images of pediatric patients comprising head, thorax, and abdomen scans. For validation, the American Association of Physicists in Medicine (AAPM) manual methods were used to determine the patient's size and SSDE for the same subjects. The accuracy of the proposed algorithm in size and SSDE calculation was evaluated for agreement with the AAPM's estimations (manual) using Bland-Altman's agreement and Pearson's correlation coefficient. The normalized error, system bias, and limits of agreement (LOA) between methods were derived. The results demonstrated good agreement and accuracy between the automated and AAPM's patient size estimations with an error rate of 1.9% and 0.27% on the patient and phantoms study, respectively. A 1% percentage difference was found between the automated and manual (AAPM) SSDE estimates. A strong degree of correlation was seen with a narrow LOA between methods for clinical study (r > 0.9771) and phantom study (r > 0.9999). The proposed automated algorithm provides an accurate estimation of patient size and SSDE with negligible error after validation.
Detection of type 1 diabetes (T1D) at the preclinical stage is possible by detecting islet autoantibodies (IAs) years before the appearance of symptomatic diabetes. The Antibody Detection Israeli Research is a general population screening program searching for children with multiple IAs who are at risk of developing T1D. IAs are measured in capillary or venous whole blood (WB) samples using the novel ultrasensitive antibody detection by agglutination-PCR (ADAP) technology. To assess the accuracy and reliability of the ADAP assay in venous and capillary WB. In total, 50 children with T1D and 50 healthy controls participated in the study. Venous and capillary blood samples were drawn from participants with T1D, while only venous blood was drawn from the controls. The ADAP assay in venous and capillary blood was compared to the currently used assays in their ability to detect glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A), and insulin autoantibodies (IAAs). The area under the curve using the receiver operating characteristic curves was comparable between the ADAP assay in WB and standard enzyme-linked immunosorbent assay (ELISA)/radioimmunoassay (RIA) for all three IAs GADA 0.946 (95% CI: 0.900-0.991) vs. 0.949 (0.906-0.992), P=0.873; IA-2A 0.747 (0.649-0.844) vs. 0.666 (0.587-0.744), P=0.106; IAA 1.000 (1.000-1.000) vs. 1.000 (1.000-1.000), P=1.000. The correlation between the levels of IA in venous and capillary WB using ADAP was R 2 = 0.958 (P  < 0.01), R 2 = 0.943 (P  < 0.01), and R 2 = 0.711 (P  < 0.01) for GADA, IA-2A, and IAA, respectively. IA levels in venous and capillary WB using ADAP were comparable without a proportional bias in Bland-Altman's plots of agreement, suggesting the two methods may be used interchangeably. The ADAP assay is reliable in detecting IA in venous and capillary WB samples with comparable performance to standard RIA and ELISA. These findings open avenues for widespread use of the ADAP assay in future general population screening programs to detect children at risk of developing T1D.