eClinicalMedicine

Background: The C-reactive protein-albumin-lymphocyte (CALLY) index integrates systemic inflammation, nutritional status, and immune function. We evaluated its association with survival in primary lung malignancies. Methods: Embase, PubMed, Scopus, and Web of Science were searched from inception to 18 September 2026. Risk of bias was assessed using the Quality In Prognosis Studies tool. Hazard ratios (HRs) were synthesized using random-effects models with restricted maximum likelihood estimation and Hartung-Knapp adjustment. Sensitivity analyses, subgroup analyses, and meta-regression examined robustness and heterogeneity. Results: Eleven studies contributed 13 cohorts to the overall survival (OS) analysis and 8 cohorts from seven studies to a combined recurrence/progression-free survival (RFS/PFS) analysis. Lower CALLY was associated with poorer OS (HR 1.78, 95% CI 1.49-2.12; I2=71.6%) and poorer RFS/PFS (HR 1.60, 95% CI 1.40-1.84; I2=0%). Associations persisted in leave-one-out analyses. No statistically significant subgroup differences were detected. Funnel-plot asymmetry suggested small-study effects for OS and RFS/PFS. Seven studies had moderate and four had high overall risk of bias. The certainty of evidence was rated as low for both OS and RFS/PFS, primarily due to risk of bias, heterogeneity, and endpoint indirectness. Conclusion: Lower CALLY was associated with adverse survival outcomes in the current synthesis. Methodological limitations and variation in biomarker measurement and endpoint definitions restrict interpretation. Prospective validation using standardized measurements and clinically coherent outcomes is needed to establish incremental prognostic value and clinical utility. Keywords: CALLY index; lung cancer; prognosis; overall survival; systematic review; meta-analysis

Background: TB vaccine development is hampered by the natural history of M. tuberculosis: most infected people rarely progress to disease, so trials must be very large and long to accrue sufficient disease endpoints. Current trials enrol IGRA-positive participants (IGRA: Interferon-Gamma Release Assays), but IGRAs remain positive for many years and cannot distinguish recent from remote infection. Tests for recent infection are now in development, and we argue they could make trials substantially more efficient. Here, we investigate how screening participants prior to enrolment with a test for recent M.tb infection could impact the total number of enrollees required for an adequately-powered TB vaccine trial. Methods: Using a statistical model of vaccine trial recruitment, we estimated the number needed to contact, test, and enrol to achieve an 'effective' trial (defined as 50 disease endpoints), under IGRA-gated enrolment (life-long duration of positivity) vs. enrolment with a test for recent infection. We considered five recruitment strategies: non-test-based enrolment for ages 15-49, ages 12-34, and household contacts of recent cases; and test-based enrolment using IGRA, and a test for recent infection with two-year duration of positivity. The model explored trial recruitment in South Africa, Kenya, and India. Results: Compared with an extended-positivity test, a test for recent infection reduced the median number needed to enrol by 4.2- to 6-fold under favourable conditions. It also outperformed non-test-based strategies, including enrolling household contacts. This comes at the cost of substantially more testing, but crude estimates suggest recency-based enrolment would still be cheaper overall provided the new test does not cost more than roughly 5-10 times an IGRA. Conclusions: Diagnostics for recent M.tb infection have the potential to improve vaccine trial efficiency, but more research is now needed to understand test characteristics and to evaluate their use in this setting. Our Viewpoint sets out the test attributes that would need to be established, such as time to positivity, duration of positivity, sensitivity, and specificity, before such tests could be used in vaccine trials.

Introduction: Lichen sclerosus (LS) is a chronic inflammatory dermatosis predominantly affecting the anogenital region of both women and men. Sexual dysfunction remains among the most debilitating and overlooked consequences of the disease, as available patient-reported outcome measures are either restricted to one sex or capture sexual health only partially. The aim of the present work is to validate the Qualisex questionnaire (in its the Italian version) in patients with LS and to evaluate its psychometric properties, factor structure, convergent, discriminant validity, and sex symmetry. Methods: A cross-sectional study was conducted on 211 patients (167 women, 44 men; mean age 52.9 years) with a confirmed diagnosis of LS. Participants completed the Italian Qualisex, Skindex-29, DASS-21, and sexual-health-specific scales, the Female Sexual Function Index (FSFI) for women, and the International Index of Erectile Function (IIEF) for men. Construct validity was assessed via Principal Component Analysis (PCA), and reliability via Cronbach's alpha. Convergent and discriminant validities were evaluated against standard psychometric batteries. Results: Item 2 was removed due to low communality (0.167). PCA on the remaining 9 items revealed a two-factor structure accounting for 72.5% of total variance: Component 1 (Sexual Functioning and Satisfaction, 59.89%) and Component 2 (Partner Devaluation, 12.66%). Internal consistency was high (alpha= 0.911 overall; alpha= 0.841 in women; alpha= 0.899 in men). Qualisex scores correlated strongly with Skindex-29 Social Functioning (r = 0.582) and Emotions (r = 0.531) subscales, as well as FSFI (r = -0.391) and IIEF (alpha= -0.566). Discriminant validity was supported by low-to-moderate correlations with DASS-21 domains (r < 0.38). While FSFI and IIEF showed significant negative correlations with age (p = 0.002), Qualisex remained age-independent across sexes (p > 0.05). Conclusion. The 9-item Italian Qualisex is a reliable, sex-symmetrical, and age-independent patient-reported outcome measure for assessing sexual health impairment in LS, successfully isolating disease-specific distress from physiological aging and general distress.

Stroke is a leading cause of mortality and disability in Uganda, with a prevalence of approximately 2.5% and a 25-30% 30-day mortality rate, exacerbated by limited access to predictive tools and advanced diagnostics. Machine learning (ML) offers potential for early stroke risk stratification, but its application in resource-constrained settings like Uganda requires tailored models and rigorous performance evaluation, as well as assessment of misclassification patterns. This study aimed to develop and internally validate an ML-based predictive model for stroke using clinical and socio-demographic characteristics among patients at Mulago National Referral Hospital (MNRH) and residents of Wakiso District, Uganda, identify key predictors and assess misclassification patterns to enhance targeted prevention. A retrospective case-control study utilized secondary data from 1,016 participants (254 stroke cases, 762 controls) across three prior studies conducted between 2006 and 2015. Eight ML algorithms were evaluated using 5-fold cross-validation, with performance metrics including accuracy, sensitivity, positive predictive value, F1-score, and area under receiver operator characteristics curve (AU-ROC). McNemars test compared model classification performance of the top 2 models. Feature importance identified key predictors, and misclassification patterns were analyzed using classification matrix and line graphs. The Random Forest (RF) model achieved the highest performance (95.18% accuracy, 90.10% F1-score, 97% AU-ROC). McNemars test confirmed RFs superior classification (p=0.01). Age, systolic blood pressure, total cholesterol, and waist-hip ratio were the top drivers of RF stroke predictions. RF misclassified 8.3% of stroke cases and 3.3% of non-stroke cases, due to overlaps in risk profiles (e.g., lower cholesterol, systolic blood pressure and age in false negatives). The RF model demonstrates strong potential for stroke risk prediction in Uganda, leveraging routine data to prioritize high-risk individuals. Misclassification analysis highlights areas for model refinement, supporting its potential for integration into clinical workflows for early intervention and stroke prevention in resource-limited settings. Future external validation across diverse populations is recommended.

Nicotinamide riboside (NR), a precursor to the essential coenzyme nicotinamide adenine dinucleotide (NAD+), has been extensively studied following oral administration, while the longer-term safety and physiological effects of injectable NR remain less characterized. Following an initial in-clinic phase evaluating repeat intramuscular (IM) and subcutaneous (SC) administration of pharmaceutical-grade NR, participants transitioned to an at-home phase designed to assess the safety, feasibility, and exploratory physiological effects of repeated self-administered SC administration. Participants continued their assigned 50 or 100 mg dose group and self-administered NR subcutaneously 3 times weekly for approximately 90 days. Safety was assessed through adverse event (AE) monitoring, vital signs, and clinical laboratory health measures. Exploratory assessments included markers of mitochondrial bioenergetics, urinary biomarkers of oxidative stress, and participant-reported outcomes related to fatigue, sleep, pain, and quality of life. At-home administration of NR was generally well-tolerated, with no clear dose-dependent safety concerns identified over the study period. Further, participants were able to successfully self-administer repeated SC injections over the study period, demonstrating positive feasibility. Whole-blood NAD+ concentrations remained largely stable over time in both dose groups. MeScreen analysis demonstrated a reduction in GlycoATP at Day 30 and increases in the MitoATP/GlycoATP ratio at Day 30 and Day 90, signifying a preferential shift toward oxidative metabolism. These findings may be indicative of positive metabolic health shifts. Urinary oxidative stress profiling demonstrated heterogeneous temporal responses. Several lipid oxidation markers significantly declined at Day 30 but returned toward baseline at Day 90. Select markers of nucleic acid, nitrative stress, and advanced glycation end-product oxidation demonstrated more sustained reductions. These results for which the majority of measured oxidative stress markers improved suggest that NR injections may exhibit anti-oxidative characteristics. Validated participant-reported sleep and fatigue measures showed improvements. Self-reported facial skin improvement increased descriptively from 11.4% at baseline to 27.8% at Day 30 and 36.8% at Day 90; improvements noticed by others increased from 9.1% to 23.7%, while reported body-skin improvement increased more modestly, from 8.8% to 16.7%. As these outcomes were not designed or powered to establish efficacy or definitive clinical claims, the findings should be considered hypothesis generating and provide preliminary data to inform the selection of outcomes and design considerations for future randomized, placebo-controlled, adequately powered trials of SC NR administration.

Objective Reducing household air pollution exposure during gestation and infancy may have longer-term benefits for child linear growth. We examined whether a liquefied petroleum gas (LPG) cookstove and fuel intervention delivered during gestation and infancy could improve height-for-age Z scores (HAZ) and reduce the risk of stunting at ages 2-5 years in India, Rwanda, and Guatemala. Materials and method The Household Air Pollution Intervention Network (HAPIN) was a randomized controlled trial that enrolled ~3200 pregnant women across Guatemala, India, Peru, and Rwanda. Women in the intervention group received an LPG cookstove and free fuel during pregnancy and until the infant reached 12 months of age. Following the HAPIN trial, we continued following children in Guatemala, India, and Rwanda (N=2169) and measured child height at ages 2, 3, 4, and 5 years (HAPIN 2.0). As prespecified in the study protocol, we used mixed-effects models, as well as linear and log-binomial regression, within the intention to treat (ITT) framework, to evaluate the interventions effect on HAZ and stunting. Subgroup analyses were performed to assess effect modification by child sex, maternal height, and intervention country. Results The intervention reduced gestational exposures to particulate matter (PM2.5: 80.7 vs 117.5 {micro}g/m3), carbon monoxide (CO: 1.3 vs 2.0 ppm), and black carbon (BC: 8.6 vs 12.1 {micro}g/m3) and infancy exposures (PM2.5: 36.9 vs 113.2 {micro}g/m3; CO: 0.60 vs 2.2 ppm). Post-trial PM2.5 exposure were similar between arms: 99.9 vs 98.7 {micro}g/m3. We found no statistically significant effect of the intervention on repeated measures of HAZ ({beta} = -0.06, 95% CI: -0.16, 0.03 p=0.204), annual HAZ, stunting, nor severe stunting at any age during the follow-up. There was no statistically significant effect modification by subgroups. Conclusion Despite substantial reductions in air pollution exposures during the trial, the LPG intervention did not improve growth or reduce stunting risk from ages 2 through 5 years in this multi-country cohort. These findings, consistent with prior results of the lack of effects on growth through 12 months, provide additional evidence that a clean cooking intervention alone may not be sufficient to address childhood stunting in low-resource settings. Future exposure-response analyses will supplement these ITT analyses.

Background: Self-supervised learning may improve segmentation when labelled data are limited, but its benefit may depend on model and initialisation strategy. This study evaluated in-domain masked-reconstruction pretraining across limited annotation budgets. Methods: The International Skin Imaging Collaboration (ISIC) 2016 development set was partitioned into 765 images for self-supervised pretraining, 94 for fine-tuning and 41 for validation. Five nested annotation budgets (12-94 images) and five seeds were evaluated on the 379-image test set. A custom U-Net compared random and in-domain self-supervised initialisation; a ResNet-34 U-Net compared random, ImageNet, in-domain self-supervised and sequential ImageNet-to-self-supervised initialisation. Models trained with 94 labelled images were evaluated without adaptation on ISIC 2017. A separate experiment examined restoration-based pretraining. Results: In the custom U-Net, self-supervised pretraining achieved higher mean Dice than random initialisation at all five budgets, including 0.664 versus 0.615 with 12 labels and 0.811 versus 0.768 with 94 labels. Seed-level 95% confidence intervals for paired differences excluded zero at 47 and 94 labels but not at the other budgets. With 47 labels, the self-supervised model achieved mean Dice of 0.789, compared with 0.768 for random initialisation with 94 labels. In ResNet-34, ImageNet initialisation achieved higher mean Dice than in-domain self-supervised pretraining at all five budgets, and adding self-supervised pretraining after ImageNet reduced mean Dice at four of five budgets. All six 94-label configurations achieved lower mean Dice on ISIC 2017 than ISIC 2016. In the restoration experiment, mean Dice was 0.686 with random initialisation and 0.638-0.642 following pretraining. Conclusions: In-domain masked-reconstruction pretraining improved mean Dice relative to random initialisation in the custom U-Net, but not consistently in the ResNet-34 U-Net, where ImageNet initialisation performed better at every budget. Adding self-supervised pretraining after ImageNet provided no consistent gain. These findings are specific to the dermoscopic lesion-segmentation experiments and do not establish melanoma-specific diagnostic or clinical performance.

BACKGROUND Timely cause-of-death (COD) information guides health policy, yet many deaths in low- and middle-income countries are not medically certified. In Africa, fewer than 10% of deaths are. Verbal autopsy (VA) yields a structured symptom questionnaire and a free-text narrative. Mortality surveillance increasingly records the narrative alongside the questionnaire, but the algorithms used to produce VA-based statistics were designed for structured responses only, so narratives inform physician COD assignment but do not contribute to algorithmic COD assignment. We evaluated whether supervised models could use both modalities to improve COD assignment. METHODS We analyzed 4,999 VA records for deaths at ages 12 years or older from a national sample of registered deaths in South Africa (RSA), using physician-assigned CODs as the reference standard. We trained unimodal and multimodal pipelines on the labelled records: pretrained language models (PLMs) fine-tuned on narratives alone, machine learning (ML) models on structured responses alone, and the two combined at the data, feature, and decision levels. We also prompted a locally deployed generative large language model (LLM) on the same unimodal and multimodal inputs, without parameter updates. All were compared with InSilicoVA, the operational comparator representing current automated practice. We evaluated individual-level assignment, population-level agreement, calibration, and generalization across provinces in RSA, reporting these metrics rather than ranking pipelines on any one of them. RESULTS Every supervised pipeline improved on InSilicoVA by 8.5-15.9 percentage points in top-1 accuracy and 3.5-7.1 points in cause-specific mortality fraction (CSMF) accuracy. The narrative and structured pipelines performed similarly in aggregate but differed by cause: 63.9% of deaths received identical predictions, 11.6% were correct only from the narrative pipeline, and 13.6% only from the questionnaire pipeline, with the narrative pipeline more accurate for noncommunicable causes and the questionnaire pipeline for communicable causes. Against the unimodal approaches, the decision-fusion pipelines added 4.2-5.4 percentage points in top-1 accuracy, concentrated in the most common causes, whereas feature fusion with cross-modal attention improved the less common causes, adding 6.6 points (95% CI, 1.7-11.5) in balanced accuracy and 5.5 points (95% CI, 0.6-10.3) in macro F1. Feature fusion reached the highest CSMF accuracy (95.7%). Paired differences from the better unimodal representative ranged from -0.2 to +3.4 points, with all intervals including zero. The LLM exceeded InSilicoVA on individual-level metrics and reached the highest balanced accuracy of any pipeline (60.6%), while the supervised pipelines retained higher CSMF accuracy. Supervised pipelines had lower expected calibration error than InSilicoVA. Supervised gains held across all nine held-out provinces, including every top-1 comparison and nearly every macro F1 and CSMF comparison. CONCLUSIONS PLMs using narratives alone substantially improved on current best practice and matched ML pipelines using structured responses, while multiple multimodal strategies produced further gains in individual COD assignment. The zero-shot LLM showed particular strength on rare causes, whereas supervised pipelines better recovered the population cause distribution. These findings support incorporating narratives as a core input to automated VA systems and evaluating representative fusion strategies for the intended output. External validation across settings and age groups will support broader implementation.

Background Immune checkpoint blockade (ICB) has become the standard of treatment for metastatic melanoma (MM). However, patients with melanoma brain metastases (MBM) are often excluded from clinical trials. Here we analyse patients within the real-world OxCITE cohort receiving ICB treatment for metastatic melanoma, with a focus on MBM, aiming to discern outcomes, prognostic factors and peripheral biomarkers. Methods Patients eligible for ICB treatment were recruited prospectively. Demographic, clinical and radiological data were collected from electronic patient records. Plasma samples were collected prior to the first cycle of treatment for plasma proteomic analysis. Results 307 patients were included, 81 of whom had MBM on commencing ICB. No difference in overall survival between patients with and without brain metastases was noted on multivariable analysis (HR=1.1, 95% CI 0.73-1.6, p=0.68), whereas hepatic metastases were associated with increased risk of death (HR 1.7, 95% CI 1.2-2.4, p=0.0019). Within the MBM group, steroid treatment (HR=2.5, 95% CI 1.3-5.0, p=0.006) was associated with poor OS, whilst treatment with single agent ICB (HR=1.9, 95% CI 0.86-3.9, p=0.11), symptomatic first presentation of MBM (HR=1.5, 95% CI 0.76-2.8, p=0.25) and anti-seizure drug treatment (HR=1.74, 95% CI 0.89-3.4, p=0.10) were not. Amongst all patients carriage of a BRAF mutation was associated with increased risk of MBM (OR 2.49, 95% CI 1.4-4.4, p=0.0007), and increased propensity to new brain metastases on ICB treatment (OR 2.5, 95% CI 1.1-5.9, p=0.036). Analysis of blood and plasma samples demonstrated that patients with MBM have altered haematological profiles, with raised NLR and increased plasma glial fibrillary acidic protein levels, reinforcing the distinct systemic features of MBM. Conclusions In this real-world cohort of patients receiving ICB for metastatic melanoma, the presence of MBM did not associate with worse OS. Conversely, baseline corticosteroid use was adversely prognostic. Intriguingly, plasma GFAP was significantly elevated in patients with MBM and correlated with the burden of intracranial disease, highlighting a potential role for GFAP as a candidate biomarker for MBM in high-risk surveillance. Our observations indicate the adversely prognostic weight historically attached to M1d disease is no longer applicable in the ICB era.

Background: Girls are more likely than boys to experience psychological distress during adolescence. Drivers of this gender gap remain under-studied, despite its large impact on later life and outcomes, especially for women. Explanatory factors can be gendered in their prevalence (differential exposure) and/or in their impact (differential susceptibility). We developed a multi-domain framework of explanatory factors for distress and applied it in four low- and middle-income countries. Methods: We first proposed a framework of explanatory factors for psychological distress grouped into seven domains (biological, cognitive, psychological, behavioural, social, environmental and broader societal). We applied this framework to identify explanatory variables assessed in childhood and adolescence in the Young Lives longitudinal cohort studies in Ethiopia (N=908), India (N=952), Peru (N=634) and Vietnam (N=887). Distress symptoms at 18-19 years were measured with the Strengths and Difficulties Questionnaire Emotional Symptoms scale. Gendered prevalence of each explanatory factor was tested with Mann-Whitney tests, and gendered impact with country-specific linear regressions including a gender-by-factor interaction term. Exploratory boosted-tree machine-learning models, interpreted with SHAP values and permutation feature importance, examined the contribution of these factors to the gender gap in each country. Results: Distress was higher in girls than boys in every country, the gap ranging from 0.62 points in Ethiopia and Vietnam to 1.76 in India and 2.45 in Peru. Some explanatory factors were consistently gendered in prevalence (e.g. girls experienced greater role overload in each country), while others were gendered only in some countries (e.g. study amount was higher for girls in Peru and Vietnam, but not Ethiopia or India). Gendered impacts on distress displayed more variability across countries. For example, higher self-esteem was more protective for boys than girls in India, Peru and Vietnam, but more protective for girls in Ethiopia. The machine-learning models identified important predictors across all framework domains, though their salience varied by country. Conclusions: Our findings underscore the importance of considering multi-domain explanations for mental-health outcomes and observed inequalities in mental health. Large cross-country differences in the gender gap and in the prevalence and influence of explanatory factors caution against generalising drivers of mental-health outcomes and inequalities across contexts.

Study Objectives: Glucagon-like peptide-1 (GLP-1) receptor agonists raise resting heart rate. We asked whether, after semaglutide initiation, the increase is larger during rapid eye movement (REM) sleep than during non-rapid eye movement (NREM) sleep. Methods: In the Human Phenotype Project, an Israeli cohort of generally healthy adults aged 40 to 70 years, 96 of 494 self-reported semaglutide initiators had a home sleep study (WatchPAT; sleep stages estimated from peripheral arterial tone and actigraphy) before and at least three months after starting. Each was propensity-matched 1:1 to a never-user of GLP-1 drugs measured at the same visits. We estimated the initiators' change minus their controls' change (difference-in-differences). The REM minus NREM contrast was designated primary after an exploratory analysis. Results: Relative to controls (90 to 94 pairs), heart rate rose during nocturnal wake (+3.89 beats per minute [bpm], 95% confidence interval 2.35 to 5.44), NREM sleep (+4.82 bpm, 3.12 to 6.52) and REM sleep (+6.25 bpm, 4.42 to 7.91); the REM increase exceeded the NREM increase by 1.42 bpm (0.98 to 1.89). The excess persisted across matching designs and on a relative scale; the proportion of REM sleep did not change. Never-users with similar weight loss showed no REM sleep heart-rate rise (+0.40 bpm, -0.63 to 1.50). Heart-rate variability decreases disappeared after adjustment for heart rate. Conclusions: Semaglutide initiation was associated with higher heart rate throughout sleep, most during REM sleep, unexplained by weight loss. Clinic measurements may understate this effect. Confirmation with polysomnographic staging is needed.

Background: Age is an important determinant of tuberculosis (TB) risk, but population-level age patterns in TB prevalence have not been systematically quantified across settings. We conducted a systematic review of surveys conducted in low- and middle-income countries to quantify trends in TB prevalence across age groups. Methods: We collated age-stratified TB prevalence data for individuals aged 15+ years, from population-based surveys reported between 1993 and 2025. We analyzed data using Bayesian meta-regression models, estimating trends in bacteriologically confirmed pulmonary TB prevalence across age groups. We extended models to understand how age trends varied with alternative outcome definitions and data subsets, and examined correlations between TB age trends and sociodemographic determinants. We also estimated age-stratified notification-to-prevalence ratios as a measure of diagnostic delays for untreated TB. Findings: We included 82 unique surveys reporting age-stratified TB prevalence, spanning 30 countries and 4.6 million participants. These data demonstrated a pattern of increasing bacteriologically confirmed TB prevalence with older age, with each 10-year increase associated with a 30% (95% credible interval: 22, 38) increase in prevalence. TB prevalence for the oldest age group (75+: 796 per 100,000 [522, 1178]) was 6.4 (4.0, 10.4) times higher than the youngest (15-19: 127 per 100,000 [79, 186]), and positive age gradients were estimated for all countries (interquartile range: 23-40% increase per 10-year increase in age). Age gradients were lower in Africa compared to other regions, and for smear-positive compared to bacteriologically confirmed TB. Countries with HIV prevalence [&ge;]5% had flatter age gradients above 40 years of age. Age gradients declined slowly over the study period. Notification-to-prevalence ratios demonstrated a negative age gradient, declining by 10% (7, 14) per 10-year increase in age. Interpretation: The prevalence of untreated TB disease increases substantially throughout adulthood, and lower notification-to-prevalence ratios suggest poorer case detection among older individuals.

Background Emerging evidence has linked frailty to individual chronic diseases, but whether it predicts a broad disease spectrum and accelerates multimorbidity accumulation over time remains unknown. This study aimed to systematically evaluate the associations of physical frailty with the burden of incident disease across a wide range of chronic conditions, and with the long-term rates of multimorbidity accumulation. Methods In this prospective cohort study of 466,864 UK Biobank participants , frailty status was assessed using the Fried frailty phenotype and categorized as robust, pre-frailty, or frailty. Chronic diseases were defined based on International Classification of Diseases (ICD)-10 codes, and disease patterns were identified using network analysis. Cox proportional hazards models were used to examine the associations of frailty status with incident chronic diseases, and linear mixed models were used to assess the annual rate of chronic disease accumulation. Results During a median follow-up of 13.8 years (IQR: 13.1-14.5), 536 incident chronic diseases across multiple systems were recorded. Physical frailty was associated with a significantly increased risk of 458 incident diseases (Bonferroni-corrected P < 0.05/536). In the overall cohort, compared with robust participants, those with pre-frailty ({beta} = 0.266, 95% confidence interval [CI]: 0.264-0.267) and frailty ({beta} = 0.941, 95% CI: 0.936-0.946) exhibited significantly faster rates of multimorbidity accumulation. This accelerated multimorbidity accumulation was consistently observed across strata of baseline disease burden, including participant with 0 ({beta} = 0.644, 95% CI: 0.635-0.653), 1 ({beta} =0.748, 95% CI: 0.727-0.768), [&ge;] 2 ({beta} =0.940, 95% CI: 0.933-0.947) chronic conditions at baseline. Similar associations were also found across distinct disease patterns, including neurodegenerative, metabolic, and psychiatric patterns. Conclusions Physical frailty predicts a broad range of incident diseases and is associated with accelerated multimorbidity accumulation. Incorporating frailty assessment into prevention strategies may help mitigate the growing burden of multimorbidity.

Objective. Temperature readings are routinely stratified by race and ethnicity, though significant group differences may reflect physiology, instrument noise, or categorization rather than biology. This study tests whether these categories partition facial infrared thermography measurements beyond individual variation and baseline device noise. Approach. A secondary analysis of thermography data (n = 951 adults) compares inner-canthus maximum (TCEmax) and full-face maximum (Tmax) temperatures across five administrative categories via one-way analysis of variance (ANOVA), mixed-effects modeling, Bland-Altman analysis against oral reference, and Monte Carlo sensitivity analysis. Main results. ANOVA returns significant group differences (p < 0.001; eta-squared = 0.04 for TCEmax, 0.03 for Tmax), but the total spread (0.2 to 0.3 degrees Celsius) is comparable to device accuracy and within-subject variability. Individual variation accounts for 95% of TCEmax variance, and adding simulated Gaussian noise to participant-level temperatures (sigma = 0.10 to 0.30 degrees Celsius) preserves the complete group-mean rank order in as few as 37.5% of iterations. Significance. Testing whether a group difference survives perturbation at the scale of instrument accuracy offers a check against treating significance alone as evidence of physiology. Here, observed group differences are small relative to measurement variability, and their physiological interpretation remains uncertain, with implications for clinical tools that treat administrative categories as biologically meaningful.

Importance. Plasma phosphorylated tau 217 (p-tau217) is entering clinical use with fixed diagnostic threshold that do not account for kidney function. Chronic kidney disease (defined as estimated glomerular filtration rate (eGFR) below 60 mL/min/1.73 m2), raises plasma p-tau217 concentrations and can produce false positive results. It remains unclear whether milder reductions in kidney function, above the CKD threshold, have the same effect. Objective. To determine whether plasma p-tau217 is elevated with mildly reduced kidney function, above the chronic kidney disease threshold, in adults without neurological disease. Design. Cross-sectional analysis of a cohort enrolled between 2023 and 2025 and biomarker analysis blinded to clinical data. Setting. Two private psychiatric inpatient facilities in Australia. Participants. Adults admitted with psychiatric disorders and free of neurological disease. Exposures. eGFR calculated from serum creatinine using the CKD-EPI 2021 equation. Main Outcomes and Measures. Plasma p-tau217, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP), measured on the Simoa platform. Multivariable linear regression compared eGFR groups (< 60, 60 to 90, and [&ge;] 90 mL/min/1.73 m2), adjusted for age, BMI, and sex. Results. Among 180 participants (median age, 50.5 years [IQR, 38.0-61.5]; 94 [52%] female), eGFR was [&ge;] 90 mL/min/1.73 m2 in 106 (59%), 60 to 90 in 61 (34%), and < 60 in 13 (7.2%). Compared with an eGFR [&ge;] 90, plasma p-tau217 was 36% higher in both the 60 to < 90 group ({beta} = 0.42 [95% CI: 0.11, 0.74]; P = .008) and 116% higher in the < 60 group ({beta} = 1.05 [95% CI: 0.43, 1.72]; P = .002). Plasma NfL and GFAP were elevated in the < 60 group but differences in the 60 to < 90 group did not reach significance. Modelled continuously, plasma p-tau217 was 9.5% lower per 10 mL/min/1.73 m2 higher eGFR (95% CI: 3.3%, 15.4%). Conclusions and Relevance. Plasma p-tau217 was elevated in adults with mildly reduced kidney function, above the CKD threshold, in a cohort free of neurological disease. Kidney function across its full range should be incorporated into plasma p-tau217 reference ranges and clinical interpretation to reduce false positive and false negative results.

Background. In people with type 2 diabetes (T2D), postprandial glucose weighs on glycaemic control, and carbohydrate counting is difficult. Patients can describe their meal but rarely quantify it. Objective. To assess (1) whether a small open large language model (LLM), fine-tuned on public data, estimates the carbohydrate content of a meal described in words, and (2) what this carbohydrate adds to the prediction of the postprandial glucose rise in two public cohorts. Methods. Step 1: the Qwen3-4B LLM was fine-tuned with QLoRA on Nutrition5k dishes and compared with an automatically matched USDA food composition table and with Qwen3-4B and Qwen3-8B used without training, on test dishes (internal control) and on 100 real meals of ShanghaiT2DM patients, whose reference carbohydrate was computed from the recorded quantities. Step 2: the maximum glucose rise between 0 and 120 minutes ({Delta}Gmax) was predicted by personalised gradient boosting (M2), compared with a spline linear regression and with the Chronos-2 foundation model, using only information available at meal start and person-level cross-validation, in ShanghaiT2DM (people with T2D recruited in two Shanghai hospitals; carbohydrate estimated by the LLM) and CGMacros (free-living adults in Santa Barbara, California; carbohydrate entered in the dataset, no text). Step 3: the model was transferred between datasets. 95% confidence intervals (CI) were obtained by cluster BCa bootstrap (2,000 resamples). Results. On the 100 real meals, the carbohydrate mean absolute error (MAE) of the fine-tuned model was 12.2 [9.9, 15.2] g, almost half that of the table (22.6 g; paired difference -10.5 [-16.8, -6.0] g) and nearly a third of that of the same model without fine-tuning (34.3 g), with a bias of -10.3 g; on test dishes it was 2.2 [2.0, 2.5] g. Personalised gradient boosting (M2) reached a correlation between predicted and observed rises of r = 0.63 [0.55, 0.69] in CGMacros (1,286 meals, 45 adults) and 0.49 [0.42, 0.54] in ShanghaiT2DM (2,339 meals, 99 people with T2D), about twice the linear reference (r = 0.32 and 0.23); for a rise above 50 mg/dL, its area under the ROC curve (AUROC) was 0.80 and 0.74, versus 0.64 and 0.68 with pre-meal glucose alone. Adding carbohydrate to pre-meal glucose changed r by 0.095 [0.068, 0.128] in CGMacros and by 0.004 [-0.010, 0.017] in ShanghaiT2DM; difference between datasets: 0.091 [0.060, 0.126]. Applied from one dataset to the other, the model lost correlation ({Delta}r = -0.11 [-0.17, -0.05] towards ShanghaiT2DM and -0.12 [-0.19, -0.04] towards CGMacros). The full "text [-&gt;] LLM [-&gt;] glucose" chain was evaluated in ShanghaiT2DM only. Conclusion. An open 4-billion-parameter LLM, fine-tuned with QLoRA on public data and usable offline, almost halves the error of carbohydrate counting for real meals described in words compared with an automatically matched table, with an underestimation of large meals. Personalised gradient boosting, based on pre-meal glucose and the person's usual response, doubles the correlation of a linear reference for predicting the glucose rise in both cohorts. Carbohydrate improved this prediction in CGMacros but not in ShanghaiT2DM; the two datasets differ in many respects, and the cause of this gap is not established.

Background: The organization of pancreatic cancer care may be associated with survival. Using health administrative claims data, we reconstructed the pathway from diagnosis to first-line therapy and examined associations of multidisciplinary team review and treatment at specialized centers with overall survival. Methods: Longitudinal historical cohort study using anonymized health administrative claims data from six Czech health insurance funds, covering approximately 17% of patients diagnosed with pancreatic cancer nationally between 2018 and 2020. Adults with an incident ICD-10 C25 record confirmed by imaging and histopathology were followed from the index date (the date of the first qualifying imaging or histopathological examination) until death, censoring, or 31 December 2021. Overall survival was analyzed using Kaplan-Meier methods and Cox regression adjusted for age and first-line therapy type. Results: Of 1,255 patients, 920 (73.3%) received first-line therapy and 266 (21.2%) died untreated. Among treated patients, 436 (47.4%) underwent multidisciplinary team review, 335 (36.4%) underwent surgery, and 667 (72.5%) were treated at a complex oncological center. Surgery was associated with longer overall survival than chemotherapy (age-adjusted hazard ratio [HR] 0.32, P < 0.001). Treatment at a complex oncological center was associated with longer overall survival (adjusted HR 0.77, 95% confidence interval [CI] 0.64-0.92, P = 0.004; crude median 532 versus 394 days). Multidisciplinary team review was not significantly associated with overall survival (adjusted HR 0.86, 95% CI 0.73-1.01, P = 0.073). Conclusions: Treatment at a complex oncological center was associated with longer survival, while fewer than half of patients had a recorded multidisciplinary team review. How care is organized, not only which therapy is delivered, is associated with outcome. The observational design and absence of key clinical covariates limit causal interpretation.

Rural patients with heart failure (HF) have poor access to care, worse outcomes, and may benefit from at-home monitoring. We evaluated whether foot temperature measured using a thermographic floor mat was associated with invasively measured cardiac output and whether longitudinal temperature changes preceded HF events. We conducted a two-part prospective, observational single-center study using the SmartMat (Podimetrics, Somerville, MA), which acquires plantar thermograms and ambient temperature. In the acute study, patients undergoing clinically indicated right heart catheterization completed 4 scans on the same day. In the chronic study, patients with a HF hospitalization in the past year and New York Heart Association Class II-III symptoms were instructed to use the device and a scale daily for 6 months. A HF event was defined as receiving at least one dose of intravenous or subcutaneous diuretic. Thirty patients were enrolled in the acute study. Mean right hallux temperature positively correlated with thermodilution cardiac output (r=0.63, p<0.001). 42 patients were enrolled in the chronic study. Among patients experiencing an HF event, ambient-adjusted hallux temperature declined in the 15 days immediately preceding the event compared with days 15-30 before the event. Plantar thermograms are associated with invasively measured cardiac output and may detect subclinical worsening before HF events. Foot temperature may provide complementary information regarding HF decompensation, supporting further evaluation of plantar thermography for remote HF monitoring.

Objective: To determine whether plasma neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) are elevated in hospitalised patients with delirium relative to patients with dementia and primary psychiatric disorders (PPD). Methods and analysis: This was a cross-sectional observational study conducted at the Royal Melbourne Hospital, Melbourne, Australia, between April and October 2024, with comparator samples from a research biobank. In Phase 1 (Delirium Discovery Cohort), we measured plasma NfL and GFAP using the Single molecule array (Simoa) platform in hospitalised patients with delirium and compared them with dementia and PPD groups. Biomarker concentrations were the primary outcome and were compared using general linear models adjusted for age, sex, and estimated glomerular filtration rate, with bootstrapped confidence intervals. Discriminative performance was assessed as a secondary outcome using receiver operating characteristic (ROC) curve analysis. In Phase 2, we applied this threshold to independent dementia and PPD groups. Results: In Phase 1 (n =176), inpatients with delirium showed higher concentrations of both NfL and GFAP than patients with dementia ({beta} = 0.78; 95% CI [0.37, 1.20] and {beta} = 0.39 [0.07, 0.73] respectively) or PPD groups ({beta} = 1.17; [0.69, 1.66] and {beta} = 0.83 [0.51, 1.24] respectively). ROC curve analysis for differentiating delirium from dementia and PPD groups yielded an optimal NfL threshold of 24.1 pg/mL (AUC = 0.89, 96% sensitivity, 70% specificity). In comparison, GFAP showed lower accuracy (AUC = 0.85), and combining NfL with GFAP (AUC = 0.90) did not significantly improve performance. In Phase 2 (n = 154), the NfL threshold of > 24 pg/ml maintained strong performance (AUC = 0.95, 96% sensitivity, and 77% specificity). Conclusions: Plasma NfL shows promise as a biomarker for delirium in hospitalised patients, distinguishing it with high sensitivity from patients with dementia and PPD. Larger multicentre studies are needed to refine cut-offs, evaluate temporal dynamics, and determine integration into acute hospital delirium pathways.

OBJECTIVE: Sepsis-associated encephalopathy (SAE) and sepsis-associated delirium (SAD) lack confirmatory laboratory tests or biomarkers. We evaluated whether the Th17/interleukin (IL)-17 axis or neuroglial-injury biomarkers reflect acute brain dysfunction beyond systemic inflammation and whether biomarker profiles differ between these phenotypes. DATA SOURCES: EMBASE, MEDLINE/PubMed, and the Cochrane Library from inception to August 1, 2026, supplemented by backward and forward citation searching, following PRISMA 2020. STUDY SELECTION: Observational studies of adults with sepsis classified by SAE or SAD status and reporting circulating biomarker concentrations by neurological group or biomarker-outcome associations. Eighteen studies (2,388 participants; 1,863 with sepsis) were included. DATA EXTRACTION: Two reviewers independently extracted study, phenotype, assay, and outcome data. Risk of bias was assessed with the Newcastle-Ottawa Scale and certainty with GRADE. DATA SYNTHESIS: Random-effects models pooled standardized mean differences (SMDs) separately against non-septic and septic controls and odds ratios (ORs) for biomarker-outcome associations. IL-6 was the only mediator elevated in both comparative frameworks and associated with outcomes (non-septic controls: SMD, 0.54 [0.25-0.82]; septic controls: SMD, 1.05 [0.51-1.59]; OR, 1.85 [1.50-2.29]). S100B, neuron-specific enolase, IL-10, tumor necrosis factor; and interferon-gamma; were elevated versus septic controls, whereas IL-17 was modestly elevated only versus non-septic controls (SMD, 0.37 [0.01-0.73]). The IL-6 septic-control effect was concentrated in SAE (p<0.0001) and remained robust in leave-one-out and risk-of-bias sensitivity analyses. Certainty was low to very low, and all 14 computable prediction intervals included the null. CONCLUSIONS: IL-6 emerges as the leading circulating candidate biomarker of sepsis-associated brain dysfunction, while S100B and NSE capture neuroglial injury beyond sepsis. Current evidence does not establish a discriminating role for the Th17 axis. Future studies require standardized neurological phenotyping and appropriately matched septic controls to establish diagnostic value.