搜索结果：Journal of translational internal medicine

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide. Conventional risk prediction models often demonstrate suboptimal calibration and limited generalizability across populations. Artificial intelligence (AI) approaches, including machine learning (ML) and deep learning (DL), enable integration of multimodal clinical and imaging data for individualized cardiovascular risk estimation. To evaluate the applications, predictive performance, and translational limitations of AI models for cardiovascular risk prediction within an umbrella review framework. PubMed, Scopus, and Web of Science were systematically searched for studies published between January 2015 and October 2025 investigating AI-based prediction of cardiovascular outcomes. Eligible designs included randomized controlled trials (RCTs), cohort studies, systematic reviews, and meta-analyses. Predictive performance was the primary outcome, mainly assessed using the area under the receiver operating characteristic curve (AUC). Methodological quality was evaluated using established risk-of-bias tools. From 3500 identified records, 48 studies (8 RCTs, 28 cohort studies, and 12 systematic reviews or meta-analyses) were included in the final analysis. AI models achieved AUC values greater than 0.90 in more than 70% of imaging-based studies. Evidence synthesis showed predominant reliance on internal validation, inconsistent calibration reporting, and limited evaluation of algorithmic fairness. Multimodal data integration improved detection of coronary artery disease (CAD) and heart failure (HF). Wearable monitoring was associated with 18-25% lower hospitalization rates compared with usual care. AI improves predictive accuracy in cardiovascular risk assessment. Despite strong discrimination performance (AUC), methodological heterogeneity, insufficient calibration assessment, algorithmic bias, limited external validation, and regulatory uncertainty remain major barriers to implementation. Clinical translation requires multicenter RCTs, explainable AI frameworks, and standardized reporting guidelines such as Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis Artificial Intelligence (TRIPOD-AI). Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, yet commonly used clinical risk prediction tools do not perform equally well across populations. This umbrella review shows that artificial intelligence (AI) has the potential to improve cardiovascular risk prediction. By analyzing nearly fifty high-quality studies published over the past decade, we found that AI-based prediction models often outperform traditional risk scores in estimating future cardiovascular events. This umbrella review integrated evidence from original research studies and previously published systematic reviews while minimizing duplication of data. In many investigations, particularly those using cardiovascular imaging, AI models demonstrated substantially higher predictive accuracy. Studies combining multiple data sources, including electronic health records, imaging data, genetic information, and wearable device monitoring, demonstrated improved diagnostic performance coronary artery disease (CAD) and heart failure (HF). Continuous monitoring using wearable technologies was associated with a reduction in hospitalization rates in prospective comparisons with usual care. Despite these promising findings, several challenges remain before AI can be routinely implemented in clinical practice. Variation in study design, potential algorithmic bias, and evolving regulatory requirements continue to limit widespread adoption. Overall, AI exhibits strong potential strong potential to support more personalized cardiovascular care; however, large prospective clinical trials and transparent reporting standards are necessary to confirm safety, fairness, and reliability before broad clinical integration.

Up to one-third of people living with psoriasis develop psoriatic arthritis (PsA), and the majority have active psoriasis prior to the development of arthritis. Clinical risk factors, such as nail involvement, in conjunction with novel blood biomarkers, could improve PsA risk monitoring and early diagnosis. The aim of the HIPPOCRATES Prospective Observational Study (HPOS-www.hpos.study) is to follow a cohort living with psoriasis and identify risk factors for the development of PsA. HPOS is a patient-driven online prospective European observational cohort. Adult participants with psoriasis but with no prior diagnosis of PsA are eligible. Participants are invited to provide consent and join the study online. They complete a semi-structured questionnaire to collect data on demographics, psoriasis, comorbidities, risk factors for PsA, and the Psoriasis Epidemiology Screening Tool screening questionnaire. Follow-up is conducted through a questionnaire every 6 months. The primary outcome is the new onset of PsA confirmed by a diagnosis from their doctor. The study will also collect peripheral blood samples from a subset of participants for biomarker identification. This study follows the principles of the Declaration of Helsinki. To date, ethical approval has been granted by independent ethical committees in 10 countries. Studying a cohort of individuals with psoriasis will allow us to identify risk factors for arthritis development and to develop a risk calculator. This can support focused efforts on screening, patient education, and even studies looking to delay or prevent the onset of arthritis. This study, run via remote online data collection, provides an efficient way to recruit a large cohort (25,000) across multiple countries. However, challenges have had to be addressed with some key changes in study design, ethical review, and recruitment strategies required for each individual country. HPOS, Clinicaltrials.gov ID: NCT05858528, IRAS number 325080; https://clinicaltrials.gov/study/NCT05858528?locStr=United%20Kingdom&country=United%20Kingdom&cond=Psoriasis&term=HPOS&aggFilters=status%3Anot%20rec&rank=1. The HIPPOCRATES prospective observational study (HPOS) The HPOS Study, part of the HIPPOCRATES project, aims to find out what signs or factors can show which people with psoriasis might later develop Psoriatic Arthritis (PsA). PsA is a type of inflammatory arthritis that is related to the skin condition psoriasis. It occurs in about 1–2% of the general population but can develop in up to 30% of people who already have skin or nail psoriasis. Diagnosing PsA early can be difficult because symptoms can be vague or inconsistent, which means treatment often starts only after joint damage has already happened. By learning more about how psoriasis develops into PsA, researchers hope to find new ways to treat the disease earlier—or even prevent or delay it. The HPOS Study is an observational study that uses online questionnaires. Adults (aged 18 or older) who have psoriasis but not PsA can take part. Participants fill out a questionnaire every six months for three years. These questionnaires collect information about age, psoriasis details, lifestyle and health factors, early joint symptoms (using the PEST questionnaire), daily function, treatment satisfaction, disease impact, fatigue, and mental health. If early signs of PsA appear, participants are advised to contact a doctor for assessment. The study plans to recruit 25,000 people across 14 European countries (including the UK, Ireland, France, Germany, and others) and expects that around 675 participants will develop PsA each year. A smaller group of 3,000 participants will also provide a small finger-prick blood sample, which will help researchers look for blood markers that might predict PsA development. HPOS is the first large-scale European study to track how psoriasis progresses to PsA. The findings could lead to a “risk calculator” that helps doctors identify people at high risk of developing PsA earlier.

Breast cancer is a leading cause of mortality and morbidity among females worldwide. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, we provided an updated comprehensive assessment of the epidemiological trends, disease burden, and risk factors associated with breast cancer globally, regionally, and nationally from 1990 to 2023. Breast cancer incidence, mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) were estimated by age and sex for 204 countries and territories from 1990 to 2023. Mortality estimates were generated using GBD Cause of Death Ensemble models, leveraging data from population-based cancer registration systems, vital registration systems, and verbal autopsies. Mortality-to-incidence ratios were calculated to derive both mortality and incidence estimates. Prevalence was calculated by combining incidence and modelled survival estimates. YLLs were established by multiplying age-specific deaths with the GBD standard life expectancy at the age of death. YLDs were estimated by applying disability weights to prevalence estimates. The sum of YLLs and YLDs equalled the number of DALYs. Breast cancer burden attributable to seven risk factors was examined through the comparative risk assessment framework. The GBD forecasting framework was used to forecast breast cancer incidence and mortality from 2024 to 2050. Age-standardised rates were calculated for each metric using the GBD 2023 world standard population. In 2023, there were an estimated 2·30 million (95% uncertainty interval [UI] 2·01 to 2·61) breast cancer incident cases, 764 000 deaths (672 000 to 854 000), and 24·1 million (21·3 to 27·5) DALYs among females globally. In the World Bank low-income group, where a low age-standardised incidence rate (ASIR) was estimated (44·2 per 100 000 person-years [31·2 to 58·4]), the age-standardised mortality rate (ASMR) was the highest (24·1 per 100 000 [16·8 to 31·9]). The highest ASIR was in the high-income group (75·7 per 100 000 [67·1 to 84·0]), and the lowest ASMR was in the upper-middle-income group (11·2 per 100 000 [10·2 to 12·3]). Between 1990 and 2023, the ASIR in the low-income group increased by 147·2% (38·1 to 271·7), compared with a 1·2% (-11·5 to 17·2) change in the high-income group. The ASMR decreased in the high-income group, changing by -29·9% (-33·6 to -25·9), but increased by 99·3% (12·5 to 202·9) in the low-income group. The increase in age-standardised DALY rates followed that of ASMRs. Risk factors such as dietary risks, tobacco use, and high fasting plasma glucose contributed to 28·3% (16·6 to 38·9) of breast cancer DALYs in 2023. The risk factors with a decrease in attributable DALYs between 1990 and 2023 were high alcohol use and tobacco. By 2050, the global incident cases of breast cancer among females were forecast to reach 3·56 million (2·29 to 4·83), with 1·37 million (0·841 to 2·02) deaths. The stable incidence and declining mortality rates of female breast cancer in high-income nations reflect success in screening, diagnosis, and treatment. In contrast, the concurrent rise in incidence and mortality in other regions signals health system deficits. Without effective interventions, many countries will fall short of the WHO Global Breast Cancer Initiative's ambitious target of achieving an annual reduction of 2·5% in age-standardised mortality rates by 2040. The mounting breast cancer burden, disproportionately affecting some of the world's most vulnerable populations, will further exacerbate health inequalities across the globe without decisive immediate action. Gates Foundation, St Jude Children's Research Hospital.

Severe hypoxemia after generalized convulsive seizures (GCSs) can trigger neural injury and is a potential biomarker for sudden unexpected death in epilepsy (SUDEP). Some degree of variability in interbreath interval is normal, but increased variability may suggest dysfunctional breathing control and may be associated with severe postictal hypoxemia. We evaluated the relationship between interictal breathing variability and severity and duration of hypoxemia after GCS. We prospectively collected video-EEG, respiratory flow and effort, pulse oximetry (SpO2), and ECG from people with epilepsy (PWE). Measures of interictal interbreath interval variability (coefficient of variation, root mean square of successive differences [RMSSD], and long-term [SD-2] variability from Poincar&#xe9; plots) from interictal asleep and awake periods and other relevant variables were evaluated as covariates for primary outcomes: (1) hypoxemia duration (length of time SpO2 <90%) and (2) severity of hypoxemia (SpO2 nadir), and secondary outcome: occurrence of combined prolonged and pronounced hypoxemia. Univariable and multivariable models were created for primary outcomes, but only univariable analyses were performed for the secondary outcome. Of 2,506 participants enrolled, 257 (141 [&#x223c;54%] female; mean age = 37.9 years) had &#x2265;1 GCS, but only 152 GCS in 123 had evaluable respiratory data. Multivariable model for hypoxemia duration showed that SpO2 nadir (mean ratio [MR] = 0.88, 95% CI 0.81-0.96, p = 0.002) and SD-2 of the awake interbreath interval (MR = 1.06, 95% CI 1.01-1.13, p = 0.04) were significantly associated. RMSSD of the non-REM interbreath interval (mean difference = -5.01, 95% CI -8.10 to -1.93, p = 0.002) was the only variable significantly associated with hypoxemia severity after controlling for duration of postictal generalized EEG suppression, SD-2 of the awake interbreath interval, and body mass index. Univariable analyses for combined prolonged and pronounced hypoxemia showed SD-2 of the awake interbreath interval, temporal lobe epilepsy, ictal central apnea, and a shorter tonic phase duration were significantly associated. Measures of interictal respiratory variability are associated with severe and prolonged hypoxemia after GCS. Increased interictal respiratory variability suggests baseline respiratory dysregulation in some PWE and may be a surrogate for SUDEP risk.

Since the publication of the first European Society for the Study of Coeliac Disease (ESsCD) guidelines in 2019, substantial advances have been made in understanding the management and complex disease courses of coeliac disease (CeD) in adults. These 2025 updated guidelines aim to integrate new evidence, refine management strategies, and promote a personalised and multidisciplinary approach to care. The ESsCD convened a multidisciplinary panel of experts to revise the 2019 guidelines using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) framework. Evidence was appraised and graded according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology. Statements and recommendations were draughted within working groups and finalised through a structured Delphi consensus process. The updated guidelines are presented in two parts. Part 1, which has already been published, addresses the diagnostic approach to CeD in adults, whereas Part 2 focuses on disease management, structured follow-up, and the evaluation and treatment of persistent symptoms despite a gluten-free diet or refractory disease. New or expanded sections include guidance on the safe inclusion of oats, use of low-FODMAP diets in patients with persistent symptoms, management of exocrine pancreatic insufficiency, recognition of functional asplenia and related vaccination recommendations, and stratified bone-health screening. The guidelines also discuss nutritional and psychosocial support, digital models of care, and structured transition from paediatric to adult services. Updated therapeutic strategies for refractory CeD are provided, including immunosuppressive and novel pharmacologic options. These updated guidelines offer a comprehensive, evidence-based framework for the management and follow-up of adults with CeD. By integrating recent scientific advances with pragmatic, patient-centred recommendations, they seek to optimise clinical outcomes, quality of life, and long-term health in individuals with CeD.

BackgroundComprehensive real-world tools for evaluating brain health are increasingly needed to complement established cognitive assessments and to capture multidimensional aspects of functioning relevant to dementia risk. The Integral Brain Health Questionnaire is a brief three-question, self-referenced multidomain self-assessment, not yet validated in clinical populations.ObjectiveAssess feasibility and construct validity of the Integral Brain Health Questionnaire in patients with cognitive impairment and assess its association with severity of cognitive loss and dementia risk factors.MethodsA consecutive series of 169 individuals with subjective memory complaints, mild cognitive impairment, or mild dementia at a tertiary care center in Southern Italy. Participants completed the Integral Brain Health Questionnaire, Mini-Mental State Examination (MMSE), the Clinical Dementia Rating (CDR) scale, and evaluations of dementia risk factors, including depression, social engagement, and sleep health.ResultsThe questionnaire showed good internal consistency (Cronbach's &#x3b1;&#x2009;=&#x2009;0.843). Total scores correlated with MMSE (r&#x2009;=&#x2009;0.322, p&#x2009;<&#x2009;0.001), and CDR Sum of Boxes (r&#x2009;=&#x2009;-0.165, p&#x2009;=&#x2009;0.041). Lower scores were associated with depression, poor sleep, and social isolation, while higher scores correlated with social engagement and sleep health. Women reported lower mental and social health scores. The tool showed moderate discriminative ability between mild cognitive impairment and mild dementia.ConclusionsThe Integral Brain Health Questionnaire is a simple, reliable proxy for assessing multidimensional brain health and cognitive loss severity. Apparent independence from age and education and associations with modifiable risk factors support its potential utility in clinical and population settings.

Placental schistosomiasis (PS) is underdiagnosed and may compromise maternal and neonatal health. This study estimated the prevalence of PS in a rural Gabonese population of pregnant women with confirmed S. haematobium infection using light microscopy of macerated placental tissue. This is a cross-sectional, diagnostic proof-of-concept study which applied an improved placenta maceration technique in real-world conditions to diagnose PS. Performing light microscopic assessment of a single sample of 10&#x2009;mL urine, we screened pregnant women for S. haematobium infection who sought antenatal care in Lambar&#xe9;n&#xe9; (Gabon) between January 2022 and January 2023. Women positive for S. haematobium infection were followed up until delivery. Additionally, a subsample of women with negative urine samples was recruited as a non-infected control group (1:1 ratio infected and non-infected groups) and followed up until delivery. Only participants with available macerated placental samples were considered for final analysis. Placental samples were subjected to light-microscopy-based screening for S. haematobium eggs and PS was considered present if a least one S. haematobium egg was detected. Positive light microscopic placental samples were confirmed by qPCR. Among 318 women screened for S. haematobium in urine, we found 40 (12.6%; 95% CI: 9.1-16.7%) to be positive. Together with 40 women in the non-infected control group all women were followed up until delivery. After loss-to-follow-up, 28 (70%; 28/40) women with S. haematobium infection and 20 (50%; 20/40) without infection provided placenta samples at delivery. In the group with S. haematobium infection, 14% (4/28; 95% CI: 4.0-32.7%) of women were positive for S. haematobium eggs in macerated placenta tissue. In the non-infected control group, one woman (5%; 1/20; 95% CI: 0.1-24.9%) had a positive microscopy result for PS. All five women with positive S. haematobium egg microscopy in placental tissue received a concordant qPCR result. 14% of women with S. haematobium infection also had PS. Notably, PS was also observed in 5% of women without detectable S. haematobium eggs in urine. This suggests that PS could be an underestimated phenomenon in highly endemic regions and warrants further investigations of its implications for mother-and-child health.

Information on childhood cancer burden is crucial for effective cancer policy planning. Unfortunately, observed paediatric cancer data are not available in every country, and previous global burden estimates have not discretely reported several common cancers of childhood. We aimed to inform efforts to address childhood cancer burden globally by analysing results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, which now include nine additional cancer causes compared with previous GBD analyses. GBD 2023 data sources for cancer estimation included population-based cancer registries, vital registration systems, and verbal autopsies. For childhood cancers (defined as those occurring at ages 0-19 years), mortality was estimated using cancer-specific ensemble models and incidence was estimated using mortality estimates and modelled mortality-to-incidence ratios (MIRs). Years of life lost (YLLs) were estimated by multiplying age-specific cancer deaths by the standard life expectancy at the age of death. Prevalence was estimated using survival estimates modelled from MIRs and multiplied by sequelae-specific disability weights to estimate years lived with disability (YLDs). Disability-adjusted life-years (DALYs) were estimated as the sum of YLLs and YLDs. Estimates are presented globally and by geographical and resource groupings, and all estimates are presented with 95% uncertainty intervals (UIs). Globally, in 2023, there were an estimated 377&#x2008;000 incident childhood cancer cases (95% UI 288&#x2008;000-489&#x2008;000), 144&#x2008;000 deaths (131&#x2008;000-162&#x2008;000), and 11&#xb7;7 million (10&#xb7;7-13&#xb7;2) DALYs due to childhood cancer. Deaths due to childhood cancer decreased by 27&#xb7;0% (15&#xb7;5-36&#xb7;1) globally, from 197&#x2008;000 (173&#x2008;000-218&#x2008;000) in 1990, but increased in the WHO African region by 55&#xb7;6% (25&#xb7;5-92&#xb7;4), from 31&#x2008;500 (24&#x2008;900-38&#x2008;500) to 49&#x2008;000 (42&#x2008;600-58&#x2008;200) between 1990 and 2023. In 2023, age-standardised YLLs due to childhood cancer were inversely correlated with country-level Socio-demographic Index. Childhood cancer was the eighth-leading cause of childhood deaths and the ninth-leading cause of DALYs among all cancers in 2023. The percentage of DALYs due to uncategorised childhood cancers was reduced from 26&#xb7;5% (26&#xb7;5-26&#xb7;5) in GBD 2017 to 10&#xb7;5% (8&#xb7;1-13&#xb7;1) with the addition of the nine new cancer causes. Target cancers for the WHO Global Initiative for Childhood Cancer (GICC) comprised 47&#xb7;3% (42&#xb7;2-52&#xb7;0) of global childhood cancer deaths in 2023. Global childhood cancer burden remains a substantial contributor to global childhood disease and cancer burden and is disproportionately weighted towards resource-limited settings. The estimation of additional cancer types relevant in childhood provides a step towards alignment with WHO GICC targets. Efforts to decrease global childhood cancer burden should focus on addressing the inequities in burden worldwide and support comprehensive improvements along the childhood cancer diagnosis and care continuum. St Jude Children's Research Hospital, Gates Foundation, and St Baldrick's Foundation.

Pain after surgery is of major perioperative concern because it is associated with substantial complications, including chronic post-surgical pain (CPSP) development. The CPSP incidence is high, and its accurate prediction or prevention has been so far unsuccessful. Based on experimental studies in healthy volunteers, we hypothesised that pre-surgical plasma proteome data and multi-feature discriminant modelling can improve the accuracy of predicting susceptibility versus resilience to CPSP. To test this, we conducted a proof-of-concept case-control study: thirty-two female surgical patients undergoing either open hysterectomy or thoracotomy were stratified by CPSP presence three months post-surgery. Preoperative blood samples were analysed by unbiased deep proteomics to identify plasma proteins associated with phenotypes of CPSP susceptibility vs resilience. These were then integrated with pre-surgical psychosocial factors to develop discriminative models. Among 684 identified plasma proteins, 106 turned out to be discriminatory for the CPSP-susceptible and 104 for the CPSP-resilient phenotype. At postoperative month 3, physical dysfunction, anxiety, and depression were significantly higher in CPSP-susceptible patients. The addition of proteomic data to the model improved the accuracy of phenotype discrimination in internal cross-validation when compared to psychosocial and neurocognitive factors alone. Protein network analysis was consistent with the hypothesis that pre-surgical immune and complement activation may be associated with CPSP risk. Furthermore, computational drug repositioning suggested candidate molecular targets potentially relevant to modulating the CPSP risk profile. Overall, our results illustrate the feasibility and potential utility of multimodal datasets to discriminate between CPSP phenotypes. When combined with network&#xa0;based analysis and drug&#xa0;repositioning this approach may open new avenues for identifying drug targets and personalized mitigation of CPSP in the future.

IgG4-related Hashimoto's thyroiditis (IgG4 HT) is characterized by rapid progression and may be associated with an increased risk of papillary thyroid carcinoma (PTC). The diagnosis of IgG4 HT relies primarily on postoperative pathological analysis. Early identification of IgG4 HT is crucial for guiding patient management. This study assessed the possibility of thyroid core needle biopsy (CNB) in diagnosing IgG4 HT. One hundred and twenty HT patients who underwent color Doppler-guided CNB and subsequent thyroid surgery were collected in Peking University First Hospital. Clinical, serological, sonographic, and histopathological features were also collected. The numbers of IgG4 and IgG plasma cells were counted in five high power fields (HPF), then the average numbers of IgG4+ and IgG+ plasma cells per HPF were calculated respectively. Based on the IgG4 and IgG immunohistochemistry results of 120 surgical specimens, cases were subclassified as IgG4 HT (n = 18) and non-IgG4 HT (n = 102) groups by the thyroid-specific diagnostic criteria (IgG4+ plasma cells > 20/HPF and IgG4+/IgG+ plasma cell ratio > 30%). CNB samples from IgG4 HT patients were subsequently subjected to IgG4/IgG immunostaining. However, only eight of the corresponding CNB tissues met the IgG4 HT diagnostic criteria. The remaining ten patients had IgG4+ positivity ranged in 10-20 cells/HPF and an IgG4+/IgG+ plasma cell ratio ranging from 20% to 67%. Histopathological characteristics of thyroid tissue were consistent between the surgical and CNB samples. IgG4/IgG immunostaining of CNB samples derived from thyroid tissue may serve as a valuable tool for supporting the diagnosis of IgG4 HT.

People with traumatic brain injury (TBI) morbidity (impaired cognition and behavioral regulation) and polytrauma comorbidity (depression, posttraumatic stress disorder [PTSD], chronic pain, and sleep disorders) experience health care inequities. Among Veterans and Service Members (V/SMs), TBI morbidity or polytrauma comorbidity may impact access and meaningful engagement in the high-quality health care needed to reduce poor health care outcomes. The National Academy of Science, Engineering, and Medicine Report on Accelerating Progress in TBI highlights a dearth of implementation science research in TBI that may help overcome health care access challenges. Implementation science uses a mixed methods approach to understand, implement, and examine outcomes associated with using evidence-based care in practice. The I-HEAL (Improving Health Care Access and Engagement for Veterans and Service Members with TBI Morbidity) protocol includes 4 synergistic projects with the goal of addressing key knowledge gaps that will improve access and engagement in high-quality, evidence-based health care services for V/SMs with TBI morbidity. Collectively, the 4 projects propose to: (1) adapt existing interventions to promote access and engagement in health care; (2) engage stakeholder communities to maximize uptake and translation; (3) promote research translation that informs policy and practice through knowledge translation products and deliverables targeting key partners (clinicians, V/SMs, caregivers, policymakers, and researchers); (4) facilitate research and implementation to enhance access to high-quality health care for V/SMs with TBI-related morbidity; and (5) foster the development of early/mid-career researchers in advancing implementation science research on access to care for V/SMs with TBI. Project 1 will involve the development of a nudge intervention (electronic health care reminder) for providers to engage health care proxies when interacting with cognitive disability at risk for poor health care engagement. Project 2 will involve the development of a provider toolkit of adaptations of guideline-endorsed behavioral health interventions for common polytrauma comorbidities to meet the needs of cognitively impaired individuals. Project 3 will involve the adaptation and dissemination of evidence-based team interventions for managing maladaptive behaviors after TBI. Project 4 will involve evaluation and recommendations for policy for virtual health modalities among persons with TBI and polytrauma comorbidity. I-HEAL has been funded as an implementation science Focused Program Award by Congressionally Directed Medical Research Programs, and start-up activities began in October 2023. All 4 projects are currently underway with funding through September 2027. Project 1 has enrolled 48 participants, and project 3 has enrolled 34 participants through September 2025. TBI is associated with increased health care utilization, comorbid health conditions, and premature mortality. This study has proposed to utilize strategies from the implementation science field to help overcome barriers to physical and psychological health care in order to reduce health care disparities associated with TBI disability.

To overcome the limitations of single-modality predictors by developing and validating a multimodal model (APNet) that integrates clinical factors and contrast-enhanced CT features to predict recurrence of moderate-to-severe acute pancreatitis (MSAP/SAP). We retrospectively collected clinical data and enhanced CT images from a total of 235 patients with moderate-to-severe AP. To rigorously evaluate model generalizability, the dataset was divided into two distinct cohorts: a Development Cohort (N&#xa0;=&#xa0;184) for model training and internal cross-validation, and an Independent Validation Cohort (N&#xa0;=&#xa0;51) for performance evaluation. Clinical machine learning models were first developed, followed by APNet, a multimodal deep learning model integrating ResNet- and ViT-extracted CT features with clinical risk factors through multiscale fusion. Among single-modality approaches, the LightGBM model using clinical data achieved an AUC of 0.711, while image-based deep learning with ResNet50 reached an AUC of 0.815. The proposed multimodal fusion model, APNet, showed the best predictive performance, achieving an AUC of 0.840 on the independent test set, with corresponding accuracy, precision, recall, and F1 score of 82.35%, 66.67%, 80.00%, and 72.73%. Overall, APNet consistently outperformed all single-modality models, highlighting the complementary value of combining imaging features with clinical risk factors. APNet effectively integrates clinical and imaging data, significantly improving prediction of recurrence in MSAP/SAP patients. This multimodal tool can help identify high-risk MSAP and SAP patients early, supporting targeted interventions and better long-term outcomes.

Meningitis remains the leading infectious cause of neurological disabilities globally, disproportionately affecting children younger than 5 years and populations in the African meningitis belt. Whereas previous global estimates focused on ten pathogen categories, this study presents the most comprehensive analysis to date, assessing the meningitis burden attributable to 17 causative pathogens based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 framework. GBD is a systematic, scientific effort aimed at quantifying the comparative magnitude of health loss caused by diseases, injuries, and risk factors across age groups, sexes, and geographical locations over time. We estimated meningitis mortality using the Cause of Death Ensemble model (CODEm) and morbidity using DisMod-MR 2.1, incorporating data from vital registration, verbal autopsy, surveillance, hospital data, and systematic reviews. Aetiology-specific estimates were generated with pathogen-linked case-fatality ratios and splined binomial regression models. Risk factor attribution was based on established risk-outcome pairs and population attributable fractions. In 2023, there were 259&#x2009;000 (95% uncertainty interval 202&#x2009;000-335&#x2009;000) global deaths and 2&#xb7;54 million (2&#xb7;20-2&#xb7;93) incident cases of meningitis. Children younger than 5 years accounted for more than a third of deaths (86&#x2009;600 [53&#x2009;300-149&#x2009;000]). Streptococcus pneumoniae, Neisseria meningitidis, non-polio enteroviruses, and other viruses were the leading causes of death, while non-polio enteroviruses caused the most cases. The four WHO-defined preventable meningitis pathogens of interest (S pneumoniae, N meningitidis, Haemophilus influenzae, and Group B streptococcus) contributed to 98&#x2009;700 deaths (77&#x2009;000-127&#x2009;000) and 594&#x2009;000 cases (514&#x2009;000-686&#x2009;000). Low birthweight, short gestation, and household air pollution were the top risk factors for meningitis-related mortality. Although mortality and incidence have declined significantly since 1990, progress is insufficient to meet WHO 2030 targets. Despite marked progress in reducing bacterial meningitis via global vaccination campaigns, a substantial meningitis burden persists, attributable both to common pathogens such as S pneumoniae and N meningitidis and to emerging non-bacterial pathogens such as Candida spp and drug-resistant fungi. Achieving WHO goals will require sustained investment in surveillance, vaccination, maternal screening, and health-system strengthening, especially in high-burden settings. Gates Foundation, Wellcome Trust, and UK Department of Health and Social Care.

Dysregulation of the tryptophan (TRP) metabolic pathway is closely linked to the pathophysiology of neuropsychiatric disorders, such as depression. This study aimed to develop and validate a sensitive, rapid, and robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous quantification of TRP and its metabolites, kynurenine (KYN) and kynurenic acid (KYNA), in human serum. Analytes were extracted from 100&#x202f;&#xb5;L of serum via simple protein precipitation with acetonitrile. Chromatographic separation was achieved on an Agilent ZORBAX HILIC Plus column (4.6&#x202f;mm&#xd7;100&#x202f;mm, 3.5&#x202f;&#xb5;m) using isocratic elution with a mobile phase of methanol: acetonitrile containing 5&#x202f;mM ammonium formate. Quantification was performed using an electrospray ionization source in positive ion multiple reaction monitoring (MRM) mode, with a total run time of only 2.0&#x202f;min.The linear ranges were 1-50&#x202f;&#xb5;g/mL for TRP, 0.1-5&#x202f;&#xb5;g/mL for KYN, and 1-50&#x202f;ng/mL for KYNA, covering clinically relevant levels. A weighting factor of 1/x&#xb2; provided the best fit for calibration curves (R&#xb2; > 0.99). Extraction recoveries ranged from 88.23% to 99.39%, and mean internal standard-normalized matrix effects were 81%-100%. Accuracy and precision values met bioanalytical acceptance criteria. Stability assessments confirmed that samples were stable at -20&#xb0;C and -80&#xb0;C for 31 days and through three freeze-thaw cycles. This validated method was successfully applied to analyze serum samples from 103 adolescent patients with first-episode depression.

AS, one of the most common forms of valvular heart disease, requiring intervention in aging populations in Europe and North America, has traditionally been viewed as a passive, degenerative condition. However, growing evidence supports a paradigm shift toward recognizing AS as an active metabolic and inflammatory disorder. This narrative review synthesizes experimental, translational, and clinical evidence published between 2015 and 2025 examining metabolic mechanisms linking valvular calcification and atrial remodeling in AS and discusses their clinical relevance in the context of transcatheter aortic valve replacement (TAVR). We discussed classical pathways involving mineral metabolism and vitamin signaling, alongside emerging roles of lipid oxidation, mitochondrial dysfunction, epigenetic regulation, and gut microbiome-derived metabolites. Further, metabolomic signatures associated with disease severity and post-TAVR outcomes were reviewed, highlighting the predominantly associative nature and current limitations of these data. Although valve replacement remains the only effective therapy for advanced AS, metabolic and multi-omics insights may improve future risk stratification and mechanistic understanding. Metabolomic profiling could be integrated at multiple points in the clinical pathway for aortic stenosis and TAVR-most promisingly for pre-procedural risk stratification. The present paper focuses on an integrative framework in which valvular calcification and atrial remodeling are viewed within a broader context of metabolic dysregulation. Future research should aim to translate molecular biomarkers into real-world diagnostics and targeted interventions.

Despite improvements in survival outcomes for acute myeloid leukemia (AML), limited evidence is available on health-related quality of life (HRQoL) and health problems experienced by long-term survivors. This international, cross-sectional study evaluated HRQoL, comorbidities, and lifestyle behaviors among long-term AML survivors enrolled from 24 centers across 6 countries. Health-related quality of life was assessed using the SF-36 and the EORTC QLQ-C30 questionnaires, while comorbidities were measured with an adapted version of the validated self-administered comorbidity questionnaire. Lifestyle factors, including physical activity, diet, smoking, alcohol consumption, and body mass index, were also assessed. Overall, 225 AML survivors were enrolled, with a median time since diagnosis of 8.8&#x2009;years (IQR 6.4-11.9) and a median age of 58.9&#x2009;years (IQR 49.0-67.0). Compared with the general population, AML survivors exhibited clinically relevant impairments in SF-36 physical functioning (&#x394;&#x2009;=&#x2009;-8.09, P&#x2009;<&#x2009;.001) and role physical scales (&#x394;&#x2009;=&#x2009;-11.09, P&#x2009;<&#x2009;.001), as well as clinically relevant lower physical component summary scores (&#x394;&#x2009;=&#x2009;-3.94, P&#x2009;<&#x2009;.001). Survivors treated with alloSCT reported worse HRQoL profiles compared with those treated with autoSCT or chemotherapy only. Comorbidities were highly prevalent (88.5%), with impaired vision, back pain, and arthrosis/arthritis being the most frequent. Analysis of lifestyle behaviors showed that 66.2% of AML survivors were physically inactive, 80.2% did not meet dietary recommendations, and 55.3% were overweight/obese. Multivariate analysis identified physical inactivity as the only independent factor associated with worse HRQoL (&#x3b2;&#x2009;=&#x2009;-6.3, P&#x2009;<&#x2009;.001). Our study shows that AML survivors experience physical limitations and a high comorbidity burden even many years after diagnosis, and it provides insights to better inform survivorship care programs. Further research examining the relationship between physical activity and HRQoL in long-term AML survivors is warranted.

This study aims to evaluate the global burden of adverse effects of medical treatment (AEMT) using data from the Global Burden of Disease Study (GBD) 2021. Data were extracted from the GBD 2021, covering 204 countries/territories from 1990 to 2021. AEMT was defined using ICD-9 and ICD-10 codes, encompassing complications from medical procedures, treatments, or healthcare exposures. Estimates were categorized into fatal and non-fatal outcomes and stratified by age, sex, year, and covariates, including the Socio-demographic Index (SDI). Mortality-incidence ratios (MIRs), defined as the ratio of mortality calculated by dividing the number of deaths by the total incident cases, were analyzed. In 2021, the global age-standardized prevalence, incidence, disability-adjusted life years (DALYs), and mortality rates of AEMT were 11.48 (95% uncertainty interval [UI], 8.86-14.13), 150.44 (131.19-171.81), 64.19 (51.06-73.11), and 1.53 (1.29-1.68) per 100,000 population, respectively. DALY rates were highest in the early neonatal group (4,789.47 per 100,000 population [95% UI, 3,682.00-5,963.30]), while mortality rates followed a U-shaped pattern across age groups. In 2021, MIRs were highest at both ends of the age range: the early neonatal group (0.58 [95% UI, 0.55-0.58]) and the 95+ age group (0.05 [0.04-0.06]). This pattern was consistent across all SDI quintiles, with higher MIRs observed in lower SDI quintiles. The significantly higher prevalence and incidence rates of AEMT among the older population in high SDI quintiles, compared to lower SDI quintiles, could be attributed to the healthcare overutilization, highlighting the need for policy adjustments.

Guillain-Barr&#xe9; syndrome (GBS) is an acute immune-mediated polyneuropathy with a high disease impact, even after good clinical recovery. The Inflammatory Rasch-built Overall Disability Scale (I-RODS) is a Patient-Reported Outcome Measure (PROM) developed for patients with immune-mediated neuropathies that measures limitations in daily activities and social participation. It consists of 24 items, scored from 0-48. The present study aimed to validate the measurement properties of the I-RODS in patients with GBS included in the prospective International GBS Outcome Study (IGOS). The current study focussed on structural validity, cross-cultural validity, internal consistency, and construct validity of I-RODS using Rasch-based methods. The study was conducted in 1226 patients diagnosed with GBS with a median I-RODS score of 28 (IQR 10-41) 4 weeks after inclusion into IGOS. Rasch analyses revealed adequate internal consistency (PSI&#x2009;=&#x2009;0.95; &#x3b1;&#x2009;=&#x2009;0.98) and sufficient construct validity, indicated by strong correlations (R&#x2009;=&#x2009;-&#xa0;0.91 to -&#xa0;0.77). Targeting was acceptable, although there was a skew towards the floor (10.1%) and ceiling (9.4%). However, the I-RODS showed poor unidimensionality (12.1% CI 10.7-13.5%) and poor overall fit to the Rasch model. Category thresholds were correctly ordered. Misfit was found in two items. Additionally, 15 of 276 item pairs showed local dependency. While no differential item functioning (DIF) was evident for age or sex, significant DIF by geographic region was observed, with the strongest DIF in one item. These results suggest that the current version of I-RODS could be improved or alternative PROMs for patients with GBS could be developed.

The Immunotherapy of the M.D. Anderson Symptom Inventory for Early-Phase Trials module (MDASI-Immunotherapy EPT) was initially developed to assess the severity of symptoms in tumor patients undergoing immunotherapy. However, in the application of this scale, it was observed that the scale did not cover the wide range of symptoms patients reported. Therefore, the scale was revised to reflect such symptoms more comprehensively based on previous studies and expert advice. A comprehensive approach was employed to identify symptoms associated with immunotherapy, encompassing a systematic literature review, semi-structured interviews with clinicians and patients, Delphi methodology, and cognitive interviews. Based on item analysis and assessments of reliability and validity, 15 immunotherapy-specific items were ultimately selected for inclusion in the revised MDASI scale. Through systematic literature review, semi-structured interviews, Delphi consensus, and cognitive interviews, 17 new immunotherapy-specific symptoms were identified. Following item analysis in Study 2.1 (n=396), 9 items were excluded, resulting in a final 34-item scale comprising 13 core symptoms, 15 immunotherapy-specific items, and 6 interference items. Exploratory factor analysis in an independent sample (Study 2.2, n=418) revealed a 6-factor structure (skin symptoms, digestive system symptoms, cardiac symptoms, hepatobiliary system symptoms, extremity edema and musculoskeletal symptoms, pain and fever dimensions) explaining 77.59% of the total variance. The revised MDASI-Immunotherapy EPT demonstrated excellent internal consistency reliability, with Cronbach's alpha values of 0.917 for the core subscale, 0.878 for the immunotherapy module, and 0.910 for the interference subscale. Criterion validity analysis using Spearman's correlations revealed significant associations with FACT-G physical well-being domain (&#x3c1; = 0.551-0.674, p < 0.01). Subgroup analyses confirmed consistent psychometric properties across urban and rural populations and across major cancer types. The modified MDASI-Immunotherapy EPT is a valid, reliable, and sensitive tool for measuring symptomatic toxicity in patients receiving immunotherapy.