Real-world data on the characteristics, interventions, and associated outcomes of patients hospitalized with factor Xa (FXa) inhibitor-associated major bleeds are limited. The REVERXaL study was designed to gain an understanding of patient characteristics, treatment approaches, and associated outcomes for FXa inhibitor-associated bleeds in real-world clinical practice. REVERXaL was designed to include historical and prospective cohorts of patients with FXa inhibitor-associated major bleeds from the United States, Germany, the United Kingdom, and Japan. Results for the historical cohort, which included information from electronic case report forms from admission to discharge for patients hospitalized for FXa inhibitor-related bleeds, are presented here. Evaluated outcomes included patient characteristics, physician-reported hemostatic effectiveness, thromboembolic event occurrence, and mortality. The historical cohort included 2025 patients hospitalized with FXa inhibitor-associated major bleeds (intracranial hemorrhage [ICH], n=1353; gastrointestinal bleeds, n=357; other, n=315) from 74 clinical sites (October 2021-November 2024). The mean (SD) age was 78.5 (10.4) years, and patients had a high comorbidity burden. The Glasgow Coma Scale rating was moderate to severe for 30.1% (407/1353) of patients with ICH. The majority of patients (70.4% [1425/2025]) received reversal/replacement therapy, administered a median (interquartile range) of 134.0 (232.0) min after admission. Among patients receiving reversal/replacement therapy, 71.1% (1013/1425) achieved physician-reported hemostasis. Thromboembolic events were reported in 6.1% (124/2025) of patients. The overall in-hospital mortality rate was 21.9% (443/2025). Given the high mortality rate, these findings suggest a need for improved treatment of FXa inhibitor-associated major bleeds. ClinicalTrials.gov identifier: NCT06147830.

Little is known about 'touch hunger' (longing for physical contact) during the COVID-19 pandemic, particularly for people with pre-existing mental health disorders. We aimed to 1) explore whether touch hunger differs between people with and without depressive, anxiety, or obsessive-compulsive disorders during the COVID-19 pandemic, 2) study the development of touch hunger in relation to loneliness, and 3) examine its predictors during lockdown. Data were aggregated from three Dutch ongoing prospective cohorts with similar methodology for data collection. We included participants with pre-pandemic data gathered during 2006-2016, and who completed up to 9 online questionnaires between October 2020 and February 2022. Touch hunger trajectories were analyzed using linear mixed models. Sociodemographics, personality traits, (chronicity of) mental health disorders, and COVID-19-related factors were analyzed as predictors of touch hunger using multivariate linear regression analyses. We included 1061 participants with (n=811) and without (n=250) mental health disorders. In all chronicity groups, touch hunger increased during lockdown and decreased after lockdown. Extraversion (β=0.256, P<0.001), social distancing due to COVID-19 anxiety (β=0.122, P=0.001), and death of a close contact from COVID-19 (β=0.073, P=0.02) predicted higher touch hunger, while living with a partner (β=-0.109, P=0.004) or with a partner and children (β=-0.147, P<0.001) were protective factors for touch hunger. Remarkably, pre-pandemic psychiatric diagnosis did not predict touch hunger during lockdown. Touch hunger rose during the lockdown and was widespread regardless of mental health conditions, indicating a fundamental human need for physical contact, especially among extroverts.

To evaluate oncological outcomes and potential risk factors for local recurrence (LR) and distant metastasis (DM) after upfront surgery in patients with magnetic resonance imaging (MRI)-defined cT3 rectal cancer, with an uninvolved circumferential resection margin (mrCRM) and no extramural vascular invasion (EMVI), in a Vietnamese cohort. A single-center, retrospective-prospective cohort of 144 patients who met these criteria and underwent upfront curative surgery between January 2018 and April 2022 was analyzed. The cumulative incidences of LR and DM were estimated. Univariate Cox regression and penalized regression models (Ridge and LASSO least absolute shrinkage and selection operator) were applied to explore potential risk factors. With a median follow-up of 56 months, LR occurred in 7 patients (4.9%), with 3-, 5-, and 7-year cumulative rates of 3.6%, 5.3%, and 5.3%, respectively. LR was most consistently associated with mesorectal violation, while anastomotic leakage and involved pathological circumferential resection margin (pCRM) showed less stable associations. DM occurred in 15 patients (10.4%), with cumulative incidences of 8.5%, 11.6%, and 11.6% at 3, 5, and 7 years, respectively. Stage III patients had significantly higher DM rates compared with stage II (p = 0.009). Preoperative carcinoembryonic antigen (CEA) ≥ 5 ng/mL and pathological nodal positivity (pN+) were the most consistent predictors of DM, while mesorectal violation and involved pCRM appeared as secondary contributors. Upfront surgery yielded favorable outcomes in selected low-risk cT3 rectal cancer patients. Mesorectal violation was most consistently associated with LR, though estimates were limited by the small number of events. DM appeared to be primarily driven by tumor biology (CEA and pN), with mesorectal violation and involved pCRM as possible secondary factors. These findings warrant validation in larger prospective cohorts.

Hepatocellular carcinoma (HCC) has a poor prognosis, necessitating better diagnostic tools. Nuclear magnetic resonance (NMR)-based metabolomics has emerged as a powerful tool for cancer biomarker discovery, yet its application in HCC prognosis remains underexplored. This study aimed to identify plasma metabolic biomarkers for the diagnosis and prognosis of HCC, and to develop predictive models for postoperative recurrence and microvascular invasion (MVI) to enhance clinical management. We performed untargeted NMR metabolomic profiling of plasma from 92 HCC patients and 92 matched healthy controls. Differential metabolites were identified, and their diagnostic performance was assessed using receiver operating characteristic curves. Predictive models for postoperative recurrence and MVI were developed and validated using multiple machine learning algorithms, such as random forest, support vector machine, and gradient boosting machine models. Significant metabolic differences were identified, with 67 metabolites and blood-lipid indicators showing marked alterations. Acetic acid, dimethylsulfone, glycerol, glycine, and low-density lipoprotein (LDL)-3 cholesterol exhibited the highest discriminatory power (area under the curve [AUC] ≥0.954). Regarding HCC recurrence prediction, the StepCox[forward] + random survival forest model achieved an AUC of 0.811 and was an independent prognostic indicator (multivariate Cox HR = 1.20, 95% CI: 1.11-1.30, P < 0.001). Regarding MVI prediction, the support vector machine model demonstrated superior performance (AUC = 0.957). Calibration curve, decision curve, and SHapley Additive exPlanations (SHAP) analyses confirmed model robustness and clinical utility. Two online platforms were developed for clinical implementation. This study developed and validated NMR-based prognostic and MVI prediction models for HCC, offering valuable tools for precision management. Their clinical value warrants further validation in larger prospective cohorts.

BackgroundCardiac sarcoidosis (CS) creates complex treatment challenges, especially for patients who fail to respond to immunosuppressive drugs, including second-line tumour necrosis factor inhibitors. These refractory cases frequently lead to serious complications and worse prognosis, prompting exploration of new therapies like Janus kinase (JAK) inhibitors.MethodsThis study included eight patients with refractory CS or probable CS treated with the JAK inhibitor tofacitinib at the University Hospital Zurich from 2020 to 2024. Treatment outcomes were assessed through changes in myocardial as well as nodal and pulmonary inflammation via 18-F-fluorodeoxyglucose positron emission tomography/CT (18F-FDG PET/CT) scans, left ventricular ejection fraction (LVEF), corticosteroid use and blood neopterin levels.ResultsSeven out of eight patients (87.5%) who received tofacitinib achieved inactive or remitting disease as assessed by repeat myocardial 18F-FDG PET/CT, with a decrease in both standardised uptake value (SUVmax and cardiac metabolic activity. In the treated patients, LVEF stabilised or improved, and the corticosteroid dose was substantially reduced, with the average daily prednisone dose dropping from 5.94 mg to 2.5 mg. Blood neopterin levels, indicative of macrophage activation, as well as extra cardiac SUVmax (nodal and pulmonal) as assessed by repeat 18F-FDG PET/CT also decreased in a majority of the treated patients.ConclusionTofacitinib shows promising results in managing treatment-refractory CS, with seven out of eight patients achieving significant reduction in myocardial inflammation and corticosteroid dependency. However, further studies with larger prospective cohorts are essential to solidify these findings and assess the drug’s efficacy and safety profile in this complex patient group.

Mental health in the elderly has emerged as a major public health issue, with late-life depression attracting widespread societal attention. This study retrieved and analyzed 19 English-language publications published between 2016 and 2025 to review the prevalence, determinants, and intervention strategies related to depression among older adults. The findings indicated that the prevalence of depression among older adults had shown an upward trend in recent years in both Western and Asian countries. Female sex, low income, exposure to famine during childhood, comorbidity with chronic diseases, and insufficient social support were identified as significant risk factors for late-life depression. Mindfulness-based cognitive therapy, psychoeducation, and combined exercise programs integrating aerobic exercise, resistance training, or balance training have been shown to significantly alleviate depressive symptoms. The review also revealed that existing evidence was largely derived from urban populations, with insufficient representation of rural and disabled older adults. Longitudinal cohort studies remained scarce in low-income countries, and intervention trials frequently exclude the oldest-old and individuals with multiple comorbidities. In light of these limitations, three actionable recommendations were proposed: first, to incorporate brief screening tools for late-life depression into national primary healthcare programs to reduce underdiagnosis; second, to strengthen cohort studies on late-life depression, to identify key risk factors, to prioritize follow-up of high-risk older populations, and to enhance causal inference; and third, to expand intervention research tailored to older adults with diverse characteristics in order to provide stronger evidence for depression management in later life.

The non-medical use of anabolic-androgenic steroids (AAS) has progressively shifted from elite sport into the general population, particularly among men seeking increases in muscularity, leanness, and physical attractiveness rather than competitive advantage. Contemporary surveys and epidemiologic syntheses suggest that this behavior is no longer restricted to professional athletes and should be approached as a relevant public health issue with endocrine, metabolic, cardiovascular, hepatic, reproductive, and psychiatric implications. This review summarizes the long-term consequences of supraphysiological AAS exposure, with special emphasis on the hypothalamic-pituitary-gonadal axis, lipid metabolism, cardiovascular remodeling, liver injury, and the neurobehavioral correlates that sustain recurrent use. A narrative review methodology was structured around studies indexed in PubMed/MEDLINE, Embase, Cochrane Library, and SciELO, prioritizing clinical trials, prospective cohorts, cross-sectional studies with objective phenotyping, and clinically informative case series. The evidence indicates that AAS use can cause profound suppression of gonadotropin secretion, secondary hypogonadism after cessation, delayed spermatogenic recovery, marked reductions in high-density lipoprotein cholesterol, elevations in low-density lipoprotein cholesterol, hypertension, left ventricular hypertrophy, and liver injury that is especially relevant with orally active 17α-alkylated compounds. Recovery after discontinuation is possible in many users, but it is heterogeneous, incomplete in a subset, and insufficiently guided by standardized protocols. The transient aesthetic gains obtained with AAS therefore contrast sharply with the potential for prolonged endocrine morbidity, cardiometabolic injury, and recurrent behavioral dependence, supporting the need for long-term follow-up and better evidence regarding post-cycle interventions.

ObjectiveChronic pain and depression are common in older adults, yet pain is dynamic and may follow distinct longitudinal courses. This study examined whether chronic pain trajectories are associated with incident depressive symptoms among adults aged 50 years and older.MethodsAnalyzed were two prospective cohorts of community-dwelling adults: the English Longitudinal Study of Ageing (ELSA) and the US Health and Retirement Study (HRS). Biennial self-reported pain (yes/no) across four waves was used to classify five mutually exclusive pain trajectories: no pain, decreasing pain, fluctuating pain, increasing pain, and consistent pain. Participants with depressive symptoms at baseline were excluded. Incident depressive symptoms were defined as a Center for Epidemiologic Studies Depression scale (CESD-8) score ≥3. Cox proportional hazards models estimated hazard ratios (HRs) adjusted for sociodemographic characteristics, health behaviors, and chronic conditions.ResultsThe analytic samples included 2476 participants in ELSA and 6238 in HRS, with a mean follow-up of 6.3 years and 6.1 years, respectively; incident depressive symptoms occurred in 19.7% and 18.3%, respectively. Compared with the no-pain trajectory, fluctuating, increasing, and consistent pain were associated with higher risk of depressive symptoms in ELSA (HRs, 1.70 [95% CI, 1.37-2.10], 1.76 [95% CI, 1.27-2.45], and 2.60 [95% CI, 1.98-3.43], respectively) and HRS (HRs, 1.48 [95% CI, 1.29-1.71], 1.84 [95% CI, 1.47-2.29], and 2.15 [95% CI, 1.78-2.59], respectively). Decreasing pain was not significantly associated with risk in either cohort.ConclusionsPersistent or worsening pain trajectories were consistently predicted subsequent depressive symptoms in older adults, whereas improving pain was not. Longitudinal pain monitoring may help identify high-risk individuals through earlier depression screening, along with integrated pain-mental health care.

Atrial fibrillation (AF) is a common arrythmia in post-myocardial infarction (MI) cardiac rehabilitation (CR) cohorts, and beta-adrenergic signaling remodeling and rate-control pharmacotherapy may influence functional capacity. We retrospectively studied 117 consecutive male post-MI patients referred to outpatient CR. Functional capacity was assessed with a 6 min walk test (6MWT). AF was identified from clinical records, and beta-blocker exposure was unified as carvedilol-equivalent daily dose. Beta-blockers were used in 94.1% of patients and AF was present in 10.3%. Patients with AF were older (72.7 ± 6.6 vs 58.1 ± 9.3 years) and walked shorter distances (430.0 [375.0-497.5] vs. 540.0 [480.0-570.0] m). In the prespecified interaction model, age remained independently associated with lower 6MWT (-4.29 m/year; p < 0.001), AF was associated with lower 6MWT (-137.21 m; p = 0.01), and the beta-blocker dose × AF interaction was positive (+6.78; p = 0.02; R2 = 0.44). Importantly, the beta-blocker dose was not associated with 6MWT in patients without AF, whereas a positive association was observed in AF (B = 7.55, p = 0.04). In this exploratory analysis, AF identified a subgroup with markedly reduced functional capacity in early post-MI CR, supporting the potential of phenotype-informed assessment. Additionally, the association between beta-blocker dose and 6MWT distance differed by rhythm status. These preliminary findings require confirmation in larger prospective cohorts.

Secondary primary malignancies (SPMs), new histologically distinct cancers that develop in patients with a history of primary tumors, represent a critical long-term adverse event in cancer survivorship. Although epidemiological studies have suggested associations between certain primary tumors and SPMs, systematic validation of their causal relationships is lacking. A Mendelian randomization analysis was employed to investigate the causal links between primary tumors and SPMs. This study systematically examined cancers spanning eight major human organ systems using data from two large European prospective cohorts: UK Biobank (31 cancer types) and FinnGen (28 cancer types). A meta-analysis of the two cohorts revealed that gastric cancer (GC) had a significant causal relationship with an increased risk of secondary esophageal cancer (odds ratio [OR] = 1.29, 95% confidence interval [95% CI]: 1.13-1.46, P < 0.001) and rectal cancer (OR = 1.13, 95% CI: 1.07-1.21, P < 0.001). Further, a single-cell sequencing analysis identified PLK1+ cancer stem cells as potential drivers of this causal relationship. Our findings provide important genetic evidence of the causal links between GC and specific SPMs, which may inform the optimization of precise follow-up strategies for GC survivors.

Inflammatory bowel disease (IBD) remains a disease burden worldwide requiring multimodal care, diagnostic and treatment approaches. Conventional disease surveillance relies on procedures which are invasive and intermittent clinical assessments which can delay intervention, resulting in suboptimal disease control. There have been several emerging wearable devices proven to be useful in diagnosis and monitoring of patients with IBD. These devices, in real-time, are capable of monitoring physiological and biochemical markers in patients with IBD. Through a narrative synthesis approach, an extensive search was conducted, identifying key studies such as prospective cohorts and observational studies conducted from 2019 to 2025 involving patients diagnosed with either Crohn’s disease or ulcerative colitis. In this review, we discuss the various interventions, primary and secondary outcomes, key findings and limitations of these studies. Several wearable devices that are able to measure key markers such as C-reactive proteins, interleukin-6, calprotectin, tumor necrosis alpha are explored. This paper also highlights the opportunities challenges and limitations. Even with promising advancements, several challenges still exist such as the accuracy of data, patient adherence, regulatory considerations, and integration with electronic health records (EHR). Future research should focus on refining the technology used in these wearable devices. Additionally, its clinical utility requires more validation to ensure its routine use in IBD care.

PurposeTo evaluate antioxidant capacity in aqueous humor (AH), trabecular meshwork (TM), and lens epithelium (LE) from patients with primary open-angle glaucoma and cataract and to assess associations with race and disease severity.MethodsIn this prospective cross-sectional study, two surgical cohorts undergoing cataract with glaucoma surgery provided either AH or paired TM/LE. AH total reactive antioxidant potential and ascorbic acid were measured. In paired TM and LE from the same eye, qPCR assessed nuclear factor erythroid 2–related factor 2 (NRF2), catalase (CAT), and superoxide dismutase 2. For AH, group comparisons used Welch's t tests or Mann–Whitney tests, and severity-stratified analyses used Race × Severity two-way ANOVA with Šídák correction. For qPCR, within-eye differences were calculated as Δ(TM − LE); race comparisons used Welch's t tests for each marker, with Šídák correction across the three markers.ResultsAH was analyzed from 106 eyes (Black n = 37; White n = 69); no race differences remained after Race × Severity modeling with Šídák adjustment. Paired TM/LE qPCR was analyzed from 42 eyes (Black n = 21; White n = 21). In Black eyes, NRF2 and CAT were lower in TM relative to matched LE (both P < 0.0001), whereas no such paired tissue differences were detected in White eyes. The within-eye difference Δ(TM − LE) was more negative in Black than White eyes for NRF2 (P = 0.0001) and CAT (P = 0.0024). Superoxide dismutase 2 showed no race-associated difference.ConclusionsAH antioxidant measures showed limited race-associated differences, whereas paired TM/LE profiling revealed tissue- and marker-specific expression differences most evident in Black patients. These compartment-specific signatures warrant validation in larger prospective cohorts.

Abstract Objectives To assess how often adult spinal deformity (ASD) surgery achieves preoperative sagittal alignment goals, whether corrections are durable, and the impact of planning frameworks and enabling technologies. Methods A PRISMA-guided search of MEDLINE, EMBASE, Web of Science, Cochrane Library, and Scopus through June 2025 identified studies of adults undergoing ASD surgery where alignment targets were defined by numeric thresholds (for example SVA, PI–LL, PT), algorithmic frameworks (for example Roussouly, GAP), or technology-assisted modalities (for example virtual planning, patient-specific rods, robotics, custom implants). Outcomes included plan-to-achieved fidelity, durability, complications, and PROMs. Random-effects meta-analyses were performed when data were sufficiently homogeneous (SVA &amp;lt; 5 cm, PI–LL ≤10°, PT ≤20°). Results Fifteen studies (2006–2025) with ∼1980 patients were included. Cohort sizes ranged 15–608; mean age was 65 years (58–72) and 68% female. Mean follow-up was 20 months (immediate to 5 years). Most patients met early postoperative targets for SVA, PI–LL, and/or PT, though durability attenuated at longer follow-up. Algorithm-driven planning—especially restoration to a Roussouly-consistent profile—was associated with fewer mechanical complications. Technology-assisted approaches improved plan-to-achieved fidelity but showed inconsistent PROM gains. Study quality varied: small single-center series were higher risk, while larger prospective cohorts showed lower but heterogeneous risk. Conclusions ASD surgery often achieves sagittal targets initially, but long-term durability is variable. Algorithmic frameworks predict fewer complications, and enabling technologies improve fidelity without consistent PROM gains. Future studies should standardize goals, assess durability beyond two years, and link alignment fidelity to patient-centered outcomes and cost.

Abstract Background Calcium channel blockers (CCBs) are widely prescribed for older adults at risk of osteoporotic fractures. Despite preclinical data suggesting CCB-mediated effects on bone remodelling, clinical findings on bone mineral density (BMD) &amp; fractures are inconsistent. We systematically evaluated the relationship between CCB use, bone metabolism, &amp; fracture outcomes. Methods PubMed, MEDLINE, &amp; Embase were searched from inception to July 2025 for preclinical &amp; clinical studies reporting fracture risk &amp;/or parameters of bone metabolism. The primary outcome was fracture risk, with secondary outcomes including BMD, bone weight, biochemical markers of bone turnover (calcium, PTH, ALP, CTX, BMP-2, PINP), &amp; biomechanical properties. Screening &amp; data extraction followed PRISMA principles; risk of bias was assessed with appropriate tools (SYRCLE, RoB 2, ROBINS-I). A narrative synthesis was performed. Results 34 studies were included (17 preclinical; 17 clinical). Among clinical studies, 4/17 reported reduced BMD with CCBs; fracture risk increased in 4, decreased in 4, &amp; was unchanged in 4; 1 study additionally reported a protective association with osteoporosis. Preclinical findings across 655 animals were mixed for BMD, calcium, PTH, ALP, &amp; BMP-2. Notably, 5 studies reported lower CTX, 2 reported lower PINP, &amp; 4 reported increased or unchanged bone strength with CCB exposure. Conclusions Evidence indicates CCBs may modulate bone physiology, yet clinical associations with BMD &amp; fractures are heterogeneous. Discrepancies may reflect confounding factors like comorbidities &amp; non-skeletal pathways affecting falls risk (for example CCB-induced orthostatic hypotension or sarcopenia); these mechanisms remain hypothesis-generating. Standardised preclinical endpoints &amp; large, well-adjusted prospective cohorts stratified by dihydropyridine versus non-dihydropyridine agents, dose, &amp; duration are needed to clarify skeletal effects.

Osteoarthritis (OA) is the most prevalent degenerative joint disease worldwide. Beyond structural injury to cartilage, synovium, and subchondral bone, OA is increasingly recognized as an immunometabolic disorder characterized by low-grade inflammation and dysregulated innate and adaptive immune responses. Nutritional biomarkers-derived from macro- and micronutrient status and metabolite signatures-can shape the OA inflammatory microenvironment by modulating macrophage polarization, T-cell subset balance, cytokine networks, and key signaling programs (e.g., NF-kappaB, JAK/STAT, NLRP3 inflammasome, and oxidative stress pathways), thereby influencing tissue catabolism and pain sensitization. This review reorganizes the literature around how clinically measurable nutritional biomarkers map onto immune-cell programs and core OA pathological processes, and critically appraises evidence strength and translational readiness. Most biomarker-OA links are supported primarily by mechanistic rationale and observational associations, while longitudinal and interventional validation remains limited and heterogeneous; key gaps include standardized assays and cutoffs, phenotype- and joint site-stratified prospective cohorts, and externally validated models demonstrating incremental prognostic utility beyond established clinical and imaging predictors.

Abstract Conducting longitudinal cohort studies in war conditions is accompanied by a range of challenges. This article describes the recruitment and implementation process of a large, population-based longitudinal mental health study conducted in Ukraine during the war. We focus on the evolution of the recruitment strategy, 4 categories of challenges encountered—technical, security, personal, and socio-cultural, along with the solutions and key lessons learned, while reporting the number of individuals contacted and reached through different channels to achieve a substantial participation rate in a complex, war-affected setting. Recruitment for the baseline assessment began in April 2024, during an active phase of the war, and was intended to use semi-automated mass mailing via REDCap and Telegram with personal communication. However, even after extensive pilot testing initial outreach for the full study via REDCap proved largely ineffective, with most emails flagged as spam by Ukrainian email providers due to heightened national cybersecurity measures. Telegram outreach was similarly constrained by platform-level security limitations. To address these challenges, the team adopted platforms to those locally trusted, which significantly improved delivery rates. The involvement of local interviewers played a crucial role in enhancing participant trust and engagement. Integrating automated outreach with personalized phone calls by local interviewers significantly enhanced engagement. This adaptive recruitment strategy successfully reached 48.4% of invitees and achieved a 15.5% participation rate. Our experience demonstrates that even when working with randomly selected populations, participation rate can be significantly improved through flexible models that align with local social, cultural, and technological realities.

Data on the presentation of behavioral and emotional problems in early childhood and their evolution over time through large, longitudinal cohort studies remain scarce, which limits the current state of knowledge on how to guide early childhood interventions. This study aimed to develop a better understanding of behavior problems in young children with developmental disabilities, of how these change over time, and of associated child and family characteristics. This longitudinal study on 958 families addressed several shortcomings of the literature by adopting an instrument specifically developed to measure behavioral and emotional problems in children with developmental disabilities, the Developmental Behavior Checklist (Einfeld et al. in Manual for the developmental behaviour checklist: Primary carer version (DBC-P) and teacher version (DBC-T), Monash University, 2002), by employing consistent data collection intervals (i.e., after the diagnosis and at two annual follow-ups), and by sampling a homogeneous age group (i.e., 18-59months at the time of diagnosis). Children's emotional and behavioral problems, adaptive behavior, intellectual functioning, and autism symptoms, as well as parenting stress and family quality of life were assessed. Overall, social and communication problems tended to decrease, while externalizing behavior problems tended to increase and internalizing behaviors remained stable over time. Cluster analysis yielded four subgroups based on behavioral and emotional problems as assessed at the time of diagnosis. These subgroups differed in child's gender and diagnostic labels and on other child and family characteristics. Patterns of change in behavioral and emotional problems significantly differed over time according group membership. Co-occuring conditions, such as emotional and behavioral problems, should be considered in planning interventions.

Transient ischaemic attack (TIA) is a major risk factor for stroke, with up to 15% of patients experiencing an event within 90 days, a large proportion in the first 48 h. Accurate diagnosis and prognostic stratification remain challenging due to transient symptoms, lack of biomarkers, and limitations of traditional clinical scores. Machine learning (ML) holds the potential to enhance diagnostic accuracy, risk prediction, and prognosis by harnessing complex clinical, imaging, and electronic health record data. PubMed was searched from January 2000 to the present. Studies reporting the association between ML models and TIA prognosis and diagnosis were included. Risk of bias was assessed using the PROBAST tool. Data were synthesised narratively due to heterogeneity in outcomes and methodologies. A total of 10 studies were included. ML models demonstrated good discriminatory ability in diagnosing TIA compared with healthy controls. However, performance declined in metabolically complex subgroups and when distinguishing TIAs from stroke mimics. Three studies developed risk prediction models using electronic health records or CTA radiomics, with best-performing models achieving AUCs of 0.82–0.88. Studies that assessed prognostic outcomes consistently outperformed logistic regression, achieving AUCs of 0.77–0.94. ML models show promise in enhancing TIA diagnosis, risk prediction, and prognostication, frequently outperforming traditional clinical scores and statistical methods. However, most studies lacked external validation, used heterogeneous endpoints, and provided limited interpretability. Future work should prioritise larger prospective cohorts, standardised outcome definitions, model explainability, and evaluation of real-world clinical impact. CRD420251123717

To evaluate the clinical-demographic drivers of treatment choice among targeted synthetic (ts-) and biologic (b-) disease-modifying anti-rheumatic drugs (DMARDs) and therapeutic outcomes in a cohort of patients with rheumatoid arthritis (RA) before and after the European Medicines Agency (EMA) pronouncement on Janus Kinase Inhibitors (JAKis) in January 2023. This single-center, ambidirectional study enrolled patients with RA who were initiating a new course of b/tsDMARDs. Retrospective (2019-2022) and prospective cohorts (2023-2024) were compared, and disease activity and treatment response (achievement of remission or low disease activity) were evaluated at 3 and 6-month follow-up. The study analyzed 539 treatment courses (300 retrospective, 239 prospective) in 380 patients. Following the EMA guidelines, tumor necrosis factor-α inhibitors (TNFis) became the predominant bDMARD (from 32% to 41.4%), whilst JAKis prescriptions declined, particularly in the first-line settings (from 18% to 4.1%). The risk factors proposed by the EMA did not significantly prevent treatment with JAKis. However, we observed that a benefit associated with the first-line treatment in terms of target achievement (adjusted OR for non-response retrospective cohort 0.30, 95%CI 0.14-0.62) was mitigated in the prospective phase (OR 0.82, 95%CI 0.33-2.07). The 2023 EMA pronouncement on JAKis led to a shift in prescription patterns, promoting TNFis versus JAKis. The decline in JAKis prescription did not appear to be driven by EMA-identified baseline risk factors, suggesting a generalized, categorical change. This channeling may have compromised the appropriateness of treatment choices, diminishing effectiveness in the prospective cohort, particularly for first-line therapies.

BackgroundOpen health data repositories receive billions in public funding, yet no systematic framework exists to evaluate their downstream scholarly impact, the composition of the research communities they cultivate, or the breadth of disciplines they reach. We introduce a two-degree citation methodology to quantify knowledge diffusion from open data, normalized by funding, and apply it to four major health data repositories.MethodsUsing the OpenAlex bibliometric database (January–February 2026), we identified all first-degree citing publications (n= 30,049) and their second-degree citing publications (n= 485,396), defined as papers citing those first-degree publications, for MIMIC (versions I– IV; retrospective EHR data; $14.4M), UK Biobank (prospective cohort with genomics; $525.5M), OpenSAFELY (federated EHR platform; $53.7M), and All of Us (prospective national cohort with biobanking and community engagement; $2,160M). We extracted author demographics (gender via Genderize.io, institutional country income via World Bank 2024 classifications) and research topics. Chi-square tests with odds ratios assessed demographic differences across repositories.ResultsFunding-normalized first-degree papers per $1M ranged from 689 (MIMIC) to 1 (All of Us), though these figures reflect total program investment, which included community engagement and biobanking for prospective cohorts in addition to data-curation costs. The citation amplification ratio was consistent across these four repositories (9.3–11.5×). Author demographics differed significantly (p <0.001): LMIC authorship ranged from 41.8% (MIMIC) to 4.3% (All of Us), while female authorship showed the opposite pattern, lowest for MIMIC (31.8%) and highest for All of Us (43.2%). Female authors were consistently underrepresented in senior (last-author) compared with first-author positions across all repositories. Differences in scope, design, and what funding covers limit direct comparisons.ConclusionsOpen health data generates a consistent ∼10× indirect citation amplification beyond its direct users, a ratio that held across repositories spanning over two orders of magnitude in funding. The large differences in funding-normalized output partly reflect structural differences between retrospective databases and prospective cohorts. Low-cost access combined with intentional community building attracted globally diverse research communities with LMIC investigators in intellectual leadership positions, while a persistent gender gap in senior authorship across all repositories reflects disciplinary and structural inequities that data access policies alone cannot address. Future evaluations of open data investments should examine who is producing research, from where, in what positions, and whether their participation translates into locally relevant knowledge production.Take-home messageOpen health data shows a consistent ∼10× citation amplification ratio beyond direct users. Low-barrier access and active community-building are associated with globally diverse research communities, including LMIC researchers in leadership positions, yet representational equity in authorship does not guarantee locally relevant knowledge production. A persistent gender gap in senior authorship across all repositories reflects disciplinary and structural inequities that data access policies alone cannot address.