Trials

Background: Stepped-wedge cluster randomized trials (SW-CRTs) are increasingly used when interventions need to be implemented sequentially across clusters. Despite extensive developments in the design and analysis of superiority SW-CRTs, methods for planning noninferiority SW-CRTs remain limited. Methods: We propose swNIsim, a simulation-based framework for power calculation in noninferiority SW-CRTs using generalized linear mixed-effects models (GLMMs). The proposed approach accommodates both continuous and binary outcomes and supports practical design features, including unequal numbers of clusters across sequences, varying cluster-period sizes, delayed intervention effects, and analyses with or without adjustment for secular time effects. Noninferiority margins can be specified using several commonly applied strategies. Results: Through extensive simulation studies, we examined the impact of key design parameters on statistical power, including the number of periods, the number of clusters per sequence, the number of individuals per cluster-period, and the degree of between-cluster variability. For a fixed total sample size, designs with more time periods consistently achieved higher power. Increasing the number of clusters per sequence produced modest gains in power, whereas greater between-cluster variability reduced power. Type I error rates were well controlled across the scenarios examined. Balanced allocation of clusters across sequences was more efficient than unbalanced allocation schemes. Two real-world SW-CRT examples were used to illustrate application of the method. Conclusions: The proposed swNIsim provides a flexible and practical approach for power calculation in noninferiority SW-CRTs. By accommodating a wide range of design configurations and outcome types, and through implementation as a freely available R package, swNIsim may facilitate the planning and design of noninferiority stepped-wedge trials.

Introduction: Clinical deterioration in patients admitted to hospital wards is a major cause of preventable morbidity and mortality and is frequently preceded by abnormalities in vital signs that occur hours before serious adverse events occur. Early identification of patients at risk provides an opportunity for timely intervention before irreversible organ dysfunction develops. The objective of this trial is to evaluate whether implementing a wireless patient monitoring system reduces mortality and cardiopulmonary failure in patients admitted to hospital wards. Methods and analysis: The i-PROTECT trial is designed as a stepped-wedge cluster randomized controlled trial. Hospital wards (total of 28 wards, constituting clusters in this design) are randomized to have wireless monitoring for selected high-risk patients, 7 wards at a time, with every 7 wards constituting a sequence. In the first period, all wards will have no wireless monitoring. After a baseline period of 2 (+1 transition) months, the intervention is implemented in a randomly selected new sequence every 3-month period until the intervention is implemented in all sequences. The control group will receive usual care with standard intermittent monitoring and no wireless monitoring. The calculated sample size is 13160 patients. The primary endpoint is cardiopulmonary failure; a composite endpoint of 30-day in-hospital mortality, cardiac arrest, and need for vasopressor or intubation. The trial started on Feb 1, 2026, and is expected to complete patient follow-up by the end of May 2027. Ethics and dissemination: The trial was approved by the Institutional review board (IRB) of Ministry of National Guard Health Affairs (IRB/2623/23). The results will be presented at relevant national and international critical care conferences and published in international peer-reviewed journals.

Background: Large language models (LLMs) configured as virtual patients may expand structured practice of clinical reasoning in health professions education. Before testing effectiveness, it must be established whether students engage with them and whether the resulting scores are complete, reliable, and related to performance with real patients. Our earlier pilot randomized trial found very low engagement with a less structured LLM-based approach. Objective: This study aimed to assess the feasibility (adherence, acceptability, and data completeness) of a revised, structured LLM-based clinical reasoning laboratory (Laboratorio de Inteligencia Artificial [LIA]) in undergraduate physical therapy education and to explore its measurement properties, including its association with clinical judgment with a real patient assessed with the Lasater Clinical Judgment Rubric (LCJR). Methods: In this single-arm pilot feasibility study, 27 third-year physical therapy students at a Spanish university completed, in 2024-2025, 3 virtual patient cases (lumbar, cervical, and thoracic spine pain) simulated by ChatGPT (GPT-4) over 4 weeks, each twice. ChatGPT scored each attempt from 0 to 4 on the same 10 dimensions of the Lasater Clinical Judgment Rubric (LCJR; 0-40 points) that human assessors applied (1-4 per dimension; 10-40 points) during a real patient encounter. Feasibility outcomes were case completion, data completeness, and satisfaction (0-10). Measurement outcomes were internal consistency and convergent validity (Spearman correlations between model-generated and human LCJR scores). Variability estimates informed the sample size of a future trial. Results: All 27 students were assessed with the LCJR; 22 (81%) completed at least 1 LIA case. Both attempts of the lumbar, cervical, and thoracic cases were completed by 78%, 63%, and 74% of students, respectively. Satisfaction data were available for 15 students (56%; mean 6.0, SD 1.3), and missing secondary data clustered in the third rotation. Internal consistency was excellent for the LCJR (alpha=.96) and ranged from .43 to .90 for model-generated ratings. Model-generated LIA scores clustered near the maximum (mean 36.0, SD 1.4). Among completers, LIA scores correlated weakly with the LCJR (rho=0.25, 95% CI -0.20 to 0.61; rho=0.44, 95% CI 0.05-0.71, when noncompleted attempts were scored as 0). Grade point average correlated almost perfectly with the LCJR (rho=0.96; n=22); after adjustment for it, the LIA-LCJR association disappeared (partial rho=-0.10). A future trial would require approximately 39 students per group (80% power, conservative variance). Conclusions: Delivering the LIA within the curriculum was feasible, but clinical judgment ratings generated by ChatGPT did not reflect those of human assessors with a real patient: they clustered near the maximum and showed no convergent validity once noncompletion was separated from performance. LLM-generated ratings should not be used as outcome or assessment measures without validation against human raters. Case calibration, completion tracking, and clarification of the GPA-LCJR relationship are also needed before a definitive trial. Trial Registration: ClinicalTrials.gov NCT06809634; https://clinicaltrials.gov/study/NCT06809634

Reliable extraction of trial characteristics and outcomes is essential for systematic reviews, yet incorrect values can alter evidence synthesis and are difficult to detect without clear source evidence. We evaluate EviSearch, a clinical evidence-curation system that links extracted values to source passages, independently verifies cited evidence, and prioritizes higher-risk cells for review. Using ten trial publications, a 133-column schema, reference annotations, and consistent scoring across model families, we assess answer quality, inter-reading agreement, evidence reproduction, targeted review, and evidence modality. In the Qwen evaluation, EviSearch achieved 91.70% accuracy, cited 100.0% of admitted values, and reproduced 98.9% independently. Reviewing 15.6% of cells increased accuracy to 95.22%.

Abstract Background Community-based exercise may support physical and cognitive recovery after stroke, but the preferences of stakeholders involved in receiving, supporting and delivering these programmes are poorly understood. This study piloted a discrete choice experiment (DCE) that aimed to evaluate stroke survivors, carers, clinicians, and fitness instructors preferences for community-based exercise programmes for stroke survivors. The pilot aimed to assess the feasibility of conducting and analysing data for a larger-scale study and inform the sample size for a definitive DCE. Methods A DCE design was developed using literature reviews, stakeholder consultations, and evaluations of current services. Six attributes were included in the design: location, price, session frequency, individualisation, carer involvement, and recovery. Sixteen Bayesian D-optimal choice sets were developed, then blocked into two sets of eight to reduce cognitive burden. Main-effects were analysed using a mixed logit model, and stakeholder differences were explored using a conditional logit interaction model. Willingness to pay was also calculated. Results Overall, 161 respondents started the survey and 106 (66%) fully completed it. Stakeholders significantly preferred programmes that were delivered at a leisure centre, lower priced, individualised, had carer-specific sessions and offered greater chances of recovery. The largest willingness-to-pay estimates were {pound}49.41/ month for 80% chance of meaningful recovery vs 20%, and {pound}18.61/ month for leisure centre delivery vs online. Significant preference heterogeneity was identified in the main-effects model. Exploratory stakeholder interactions suggested clinicians were more price sensitive and placed greater importance on recovery and carer-specific sessions than stroke survivors, while fitness instructors placed greater importance on programme location and recovery. Carer interaction estimates were unstable due to the small subgroup sample. Conclusions The pilot supported the feasibility of the DCE design and analytical approach but identified limitations in the recruitment methods and survey completion. Addition of face-to-face recruitment methods are recommended for a larger-scale study. A larger sample size is required to investigate differences in preferences between stakeholder groups.

Panvascular intervention research requires evidence workflows that preserve source identity, outcome definitions and observation windows. We developed PanVasc Research, an executable research framework, and evaluated a fixed local Qwen3-4B model using two complementary tasks. Fifty ClinicalTrials.gov records from five vascular query strata generated 200 source-fidelity tests with intact evidence or controlled removal of the requested source, primary outcome or timeframe, plus 50 clean controls. A separate 100-statement sample from the official NLI4CT test set assessed clinical-trial entailment and evidence selection against existing expert labels. Generic and checklist prompts used identical evidence and maximum generation budgets; each output was also evaluated with an input-only deterministic contract. Registry exact accuracy was 51/200 (25.5%) with the generic prompt and 77/200 (38.5%) with the checklist; intact-case agreement was 50/50 and 48/50. The rule baseline recovered 200/200 tuples. NLI label accuracy was 48/100 (48.0%) and 50/100 (50.0%), respectively. The source contract retained 35 and 31 incorrect NLI labels in the two arms. Registry references establish fidelity to a registration snapshot, while NLI4CT concerns breast-cancer trials and does not validate vascular expertise. The framework also retains provenance-recorded literature retrieval, structured research planning and local numerical analysis. These experiments support a bounded assessment of source handling and semantic failure, rather than a new foundation model or autonomous scientific discovery. A proposed endpoint representation identifies the additional domain annotation and independent validation required for a panvascular research model.

Background: As musculoskeletal physiotherapy evolves toward advanced practice and direct access, evaluating high levels of clinical competence has become pressing. Quality indicators underpin large-scale audit systems, but indicators discriminating advanced competence remain insufficiently defined. Objective: To identify and characterize indicators capable of discriminating high levels of clinical competence in musculoskeletal physiotherapy. Methods: A modified Delphi comprised an exploratory pre-round and two consensus rounds. Experienced French-speaking musculoskeletal physiotherapists were recruited using an expertise scoring grid. Candidate indicators, generated from open-ended responses and existing quality indicators, were rated on 6-point Likert scales for relevance, formulation, and tool adequacy. Consensus was predefined as [≥]75% of ratings [≥]5. Results: Thirty-two experts completed the pre-round, 29 the first round, and 27 the second (84% retention), generating 49 candidate indicators. Thirteen reached consensus for relevance, and 10 also for formulation. Retained indicators primarily reflected advanced clinical reasoning: real-time adaptation, hypothesis prioritization, decision-making under uncertainty, and error management. Only one outcome indicator reached consensus: clinical performance weighted by case complexity. Conclusion: High levels of clinical competence in musculoskeletal physiotherapy appear characterized less by standardized outcome attainment than by managing complexity, uncertainty, and error through advanced clinical reasoning. These findings may inform competence-oriented audit and feedback systems. Trials registration: Not applicable.

As internet and mobile phone access increases, digital health interventions are increasingly used to support remote and low-resource populations. In many settings, the health impact of digital interventions is constrained by limited or short-lived engagement. We tested if conditional mobile data credit incentives increase digital intervention engagement within a digital intervention trial. This nested cluster randomized controlled trial was conducted with caregivers of children 3-9 months at baseline. Of 72 neighborhood clusters from the treatment arm of the parent trial (evaluating a digital early childhood development intervention), 20 were randomly assigned to treatment and 52 as controls. Eligible participants had a phone provider through which mobile data credits could be most affordably administered. Treated participants received around 250 MB mobile data credits every two weeks, conditional upon using the digital intervention at least once in the same period. Credits were digitally administered via a third-party service. Digital intervention engagement (primary outcome) was monitored continuously until endline data collection approximately 2 years after assignment. Secondary outcomes included caregivers views, behaviors, and early childhood development. We used intent-to-treat analyses to assess all outcomes. This trial was registered as NCT05202106 at clinicaltrials.gov and was completed in 2025. Participants were recruited between September 2021 and March 2023 (N Treatment = 147; N Control = 333). Conditional mobile data credits extended engagement with the digital early childhood development intervention by 6.50 weeks on average (treatment mean = 26.19 weeks, control mean = 19.69; p=0.011). No significant impacts were identified on secondary outcomes. As such, mobile data credits may be a cost-effective way for increasing caregiver engagement with digital health intervention in low resource settings.

Objective: To examine changes in function and pain interference among patients utilizing a digital exercise therapy application (DETA) for knee and shoulder pain. Methods: We conducted a retrospective analysis of data from patients utilizing a DETA for non-operative knee and shoulder pain. Primary outcomes for the study were 8-week changes in physical function, measured using the PROMIS-Physical Function (knee pain) and PROMIS-Upper Extremity Function (shoulder pain); and pain interference, measured using the PROMIS-Pain Interference. Data on patient characteristics was used to examine outcomes among specific patient subgroups. Results: We observed a 3.5 point (SD: 7.8) increase in function and a 3.9 point (SD: 7.5) decrease in pain interference overall (p<0.001), with changes in function and pain interference surpassing the minimal clinically important difference for patients with knee and shoulder pain. Patients with knee pain experienced greater improvements in function than those with shoulder pain (p=0.02), as did patients who report moderate-high levels of exertion during exercise compared to those reporting low levels of exertion (p=0.05). We saw greater reductions in pain interference among those with higher education (p=0.03), those with more acute symptoms (p=0.01) and those reporting moderate-high levels of exercise exertion (p=0.02). Conclusion: We observed a clinically meaningful improvement in pain interference and function among patients utilizing a DETA for knee and shoulder pain. Patients with knee pain, higher levels of education, more acute symptoms, and those who reported higher levels of exertion with exercise experienced the greatest changes in function and pain. Impact Statement: This study indicates that self-guided interventions, such as those delivered through a DETA, may be beneficial for patients with knee and shoulder pain. These results may also inform the development of patient profiles that can be used to identify patients most appropriate to receive care through a mobile application.

Background: School-based implementation of robot-assisted walking may support increased physical and social participation for children with physical disabilities, but evidence from an adequately powered trial is needed. This pilot study evaluated implementation strategies and study procedures to inform a future definitive trial. Methods: Participants were randomized to 12-weeks of robot-assisted walking or control, with subsequent crossover to the other condition. In the intervention arm, targeted dose was 75 minutes of robot-assisted walking, spread across three days/week. Implementation strategies for the child's classroom team included educational materials, centralized technical assistance, school champions, and on-going training. Implementation strategy evaluation focused on intervention protocol feasibility (i.e., weekly device use, troubleshooting) and fidelity (documentation of implementation strategy modifications). Preliminary estimates participation goal changes were obtained using the Canadian Occupational Performance Measure (COPM) 'Performance' scale (/10). Results: Eight children with neurodevelopmental physical disabilities participated (mean age 3.5, SD 0.5 years). Device use varied from 2.1 to 4.3 days/week (median 3.3) with a range of 48 to 96 minutes/week (median 80). Target use of >= 3 days/week was achieved for 66% of weeks and met the >=75-minute target for 33% of weeks. Troubleshooting occurred in 18.5% of sessions. Two implementation strategies were modified to improve feasibility. COPM mean change was 3.56 (SD 1.07) for robot-assisted walking and 2.11 (SD 2.41) for control (dz=0.74). Conclusions: This pilot study provided preliminary evidence regarding both the feasibility of robot-assisted walking implementation in schools and its potential effectiveness for children with physical disabilities. Findings support progression to a definitive trial.

TrialCalibre1 is an agentic system that connects clinical evidence, study design, and executable analyses. It supports reference-trial replication, direct target-trial emulation, and BenchExCal, which combines benchmarking, extension, and cal ibration sensitivity analysis. We evaluated an ASCET-based benchmark and an extension comparing clopidogrel with aspirin among adults aged 81-90 years us ing synthetic PCORnet-style claims. Two reviewers assessed benchmark extrac tion, protocol decisions, and implementation. After discussion, 53/62 and 50/62 assessable SQL checks were rated met; both reviewers rated 12/13 assessable R checks met. Protocol and proxy disagreements remained. A separate ten-question routing development set yielded 10/10 route matches and 7/7 applicable reference trial matches. The agent benchmark and extension included 6,069 and 1,602 pa tients. The extension risk ratio was 0.848 (95% CI 0.569-1.184), with a calibrated sensitivity estimate of 1.274 (0.439-3.700). The human implementation provided descriptive comparisons, not same-data validation. Dose proxies, unpopulated co variates, residual imbalance, implementation deviations, and ignored cross-cohort covariance limited interpretation. This case demonstrates a connected workflow whose protocols, code, and results can be reviewed.

BACKGROUND: Federal policy now requires sponsors to submit diversity action plans for clinical trials, yet the modifiable features of trial design associated with enrolled composition remain poorly characterized. English-language proficiency requirements are written into eligibility criteria and recorded as free text in a public registry, making them visible and, in principle, amenable to revision, but their relationship to enrolled composition has been examined only within single disease areas and in small samples of trials. We examined whether these requirements and documented language accommodation were associated with the racial and ethnic composition of enrolled participants. METHODS AND FINDINGS: We conducted a cross-sectional study of interventional trials registered on ClinicalTrials.gov with at least one US site and posted results, using a registry snapshot retrieved in October 2026. The primary cohort comprised the 44,487 trials with exclusively US sites, of which 21,924 (49.3%) reported baseline race and 17,434 (39.2%) reported baseline ethnicity with counts that reconciled with the posted denominator. Both exposures were classified from free-text eligibility criteria using regular expressions validated against independent physician review of 150 trials. For the English-language requirement classifier, sensitivity was 88.2% and specificity was 99.2%. The outcome was the trial-level proportion of enrolled participants in each category, analyzed using generalized linear models adjusted for intervention class, therapeutic area, sponsor, phase, enrollment, sites, start year, US Census region, and the population composition of the trial's site states. An English-language proficiency requirement appeared in 5,736 trials (12.9%); its prevalence rose from 7.4% of trials starting in 2010 to 26.2% in 2023 (odds ratio [OR] per decade 2.91, P<0.001), whereas documented accommodation, an eligibility statement allowing participation in a language other than English (Spanish in 99.9% of flagged trials), remained rare (788 trials, 1.8%). The requirement was associated with lower enrolled proportions of Asian (OR=0.85, 95% CI 0.77-0.93, P=0.001) and Hispanic/Latinx participants (OR=0.85, 95% CI 0.79-0.91, P<0.001), with no evidence of an association for White participants (OR=0.99, 95% CI 0.95-1.04, P=0.75). Documented accommodation was associated with a higher proportion of Hispanic/Latinx participants (OR=3.23, 95% CI 2.82-3.71, P<0.001). Geographic adjustment did not change the statistical significance of the requirement associations and attenuated the accommodation association. The main limitations were the cross-sectional design, which precludes causal inference; the restriction of enrollment analyses to trials reporting baseline demographics, which were more recent than those without such reporting; and possible misclassification of automatically classified exposures. CONCLUSIONS: English-language proficiency requirements became more than three times as common between 2010 and 2023 and were associated with lower enrolled proportions of Asian and Hispanic/Latinx participants. Less common documented language accommodation was associated with a higher enrolled proportion of Hispanic/Latinx participants. Because these criteria are investigator-written and publicly recorded, they may be a tractable target for improving enrollment equity, although whether revising them changes who enrolls requires prospective evaluation

Background Implantable loop recorders (ILRs) provide continuous rhythm monitoring. Professional society guidelines and expert consensus statements recommend ILR use for patients with recurrent syncope and cryptogenic stroke, but recommendations are weaker for other indications. We assessed ILR use over time and concordance between indication and clinical guidance. Methods We conducted a retrospective cohort study using Epic Cosmos data from 1/1/2020-12/31/2025. Among active patients with at least one of 13 diagnoses potentially eligible for ILR placement, we identified ILR placements and classified them by concordance with professional society guidance: concordant, possibly, or non-addressed. Annual incidence was estimated overall and by indication. We also described the proportion of patients who received longer-term (>7 days) rhythm monitoring in the year prior to placement. Results Of 47,046,706 patients with diagnoses potentially eligible for ILR placement, 201,103 (0.4%) had an ILR placed. ILR placements increased from 3.08 ILRs per 100,000 patient-days in 2020 to 4.13 in 2025 (5.9% annual growth). The most common indications were cryptogenic stroke (28.6%) and atrial fibrillation without prior ablation (21.4%). Overall, 43.9% were guidance concordant, 28.5% possibly concordant, and 24.8% non-addressed. Relative annual growth in ILR placements per 100,000 patient-days was significant across all guidance categories: concordant (1.3%, 95% CI, 0.9%-1.7%), possibly concordant (5.5%, 95% CI, 5.0%-6.0%) and non-addressed (7.4%, 95% CI, 6.8%-8.0%). Among 125,631 outpatient placements, 50,181 (39.9%) had any prior long-term rhythm monitoring. Conclusion ILR placements are uncommon but increasing, with faster annual growth for indications that may not be guidance concordant. More than half of patients lacked long-term rhythm monitoring prior to outpatient ILR placement.

Objective To determine the comparative effectiveness of different digital health interventions for adults with low back pain. Design Systematic review and network meta-analysis of randomised controlled trials. Data sources PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL, APA PsycINFO, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP), from inception to 19 March 2026 (updated to 8 August 2026). Study selection Randomised controlled trials enrolling adults with low back pain. Interventions were classified as telemedicine, web-based applications (Web-App), mobile applications (Mobile-App), virtual reality (VR), exergaming, biofeedback devices, face-to-face care, and control. Paired reviewers independently screened records, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2 tool. Methods Frequentist random-effects network meta-analyses synthesised pain intensity and physical function (primary outcomes), and pain-related fear avoidance, health-related quality of life, self-efficacy, anxiety, and depression (secondary outcomes), assessed at post-intervention (from the end of treatment to < 2 months post-intervention), short-term ([&ge;]2 to <6 months), mid-term ([&ge;]6 to <12 months), and long-term ([&ge;]12 months) follow-up. Effects were reported as standardised mean differences with 95% confidence intervals. Transitivity was examined across potential effect modifiers, and Confidence in Network Meta-Analysis (CINeMA) informed confidence ratings. Results Ninety-two reports representing 84 trials involving 11 649 participants were included. At post-intervention, compared with control, VR showed the largest estimated reduction in pain intensity (SMD -1.43, 95% CI -1.87 to -0.98; moderate confidence) and improvement in physical function (-0.86, -1.45 to -0.26; very low confidence). VR was also associated with lower pain-related fear avoidance (-1.14, -1.68 to -0.61) and better health-related quality of life (0.97, 0.57 to 1.36) (both moderate confidence). Exergaming, Mobile-App, Web-App and telemedicine were also associated with lower pain intensity, while Mobile-App, Web-App, telemedicine, and biofeedback devices were associated with better physical function. For self-efficacy, exergaming (0.77, 0.05 to 1.49) showed favourable post-intervention effects, although confidence in this estimate was very low. No intervention showed a clear effect on anxiety, with confidence ranging from very low to moderate across comparisons, whereas telemedicine was associated with lower depression (-0.22, -0.44 to 0.00; low confidence). Networks became progressively sparse at later follow-up, and evidence of sustained effects was inconsistent across interventions and outcomes. Global inconsistency was detected in the post-intervention pain-intensity network, with local inconsistency identified for selected exergaming comparisons, and substantial heterogeneity was present in several networks. Conclusions Among adults with low back pain, VR showed the largest estimated post-intervention effects versus control for pain intensity, physical function, pain-related fear avoidance, and health-related quality of life, although comparative effects differed across outcomes. Self-efficacy showed favourable estimates for selected interventions, whereas evidence for anxiety and depression was limited. Evidence beyond treatment completion was increasingly sparse, and confidence in many network estimates was low or very low; firm comparative recommendations therefore remain premature. Systematic review registration PROSPERO CRD420261339841

Background Owing to a growing body of evidence, clinical guidelines now recommend exercise for stroke survivors. However, many stroke survivors are physically inactive and may need more support to engage with exercise in the community. There are between 600-800 exercise referral schemes in the United Kingdom, but engagement from stroke survivors is very low. This study aimed to evaluate the accessibility of exercise referral schemes in England to stroke survivors. Methods A cross-sectional, online survey was conducted throughout England. All 317 local authorities in England were invited to participate. Geospatial mapping was used to visualise the accessibility of exercise referral schemes across England. Data on scheme design and delivery parameters were analysed descriptively. Results Data were collected from 147 local authorities. Exercise referral schemes were offered in 134 local authorities, of which, stroke survivors were able to access 128. However, stroke-specific schemes were available in only 17 local authorities. Significant variations in exercise referral scheme design and delivery were identified across the country. Only two consistencies were found between schemes: the involvement of fitness instructors, and the lack of transport provision. The capacity of exercise referral schemes did not correlate with the general population, stroke population, or stroke prevalence within a local authority. Conclusions Exercise referral schemes are widely available across England, and the majority are open to stroke survivors. However, stroke-specific services are very limited and there is substantial variation in scheme eligibility, capacity, costs, and referral pathways. These inconsistencies, paired with the lack of transport provision, may explain the low uptake of exercise referral schemes within the stroke population.

Cardiovascular diseases (CVD) are the leading cause of global mortality, responsible for 17.8 million deaths and 423 million prevalent cases annually. While the etiology of CVD is multifactorial, evidence confirms that multicomponent behavioral interventions regarding diet and lifestyle can substantially reduce risk. This study aimed to evaluate the effectiveness of a 12-month mHealth intervention, i.e., public health practice supported by mobile devices in reducing the 10-year CVD risk among overweight and obese adults aged 35 to 64 in an urban Sri Lankan population. A two-group parallel-arm randomized control trial (RCT) was conducted with 1,200 participants from the Colombo district, assigned either to an intervention arm (n=600) or a usual care control arm (n=600). The intervention group received automated text and voice messages in their native language at a frequency of two of each per week over 12 months. The primary outcome, 10-year CVD risk, was assessed using the WHO CVD risk prediction score. The intervention significantly reduced the proportion of participants with a 10-year CVD risk from 10.0% to 6.2% (p=0.003), whereas no significant change was observed in the control group (11.0% to 9.7%). Participants in the mHealth arm demonstrated substantial behavioral improvements, including increasing daily fruit and vegetable servings from 3.6 to 5.5 and reducing daily salt intake from 7.64g to 5.62g. Physical activity levels also improved, with 89.6% meeting minimum daily requirements compared to 77.4% at baseline. These findings suggest a potentially beneficial effect on predicted cardiovascular risk. The study concludes that an automated mHealth intervention is an effective, feasible, and acceptable approach to reducing cardiovascular risk in an urban South Asian setting. The findings provide a robust evidence base for integrating digital health strategies into national non-communicable disease (NCD) prevention policies. While the 12-month results are promising, further longitudinal research is required to evaluate the long-term sustainability of these behavioral changes and their ultimate impact on mortality rates.

Aims: Our primary aim was to determine the immediate effects of using a supported stepping device on the real-time locomotor behavior of pre-walking infants with Down syndrome (DS). Our secondary aim was to characterize the role of the caregiver in facilitating infant locomotor behavior by quantifying infant-initiated and caregiver-initiated walker movement, and to test whether walker movement encourages stepping behavior. Methods: Pre-walking infants with DS played with their caregiver in two conditions--with and without assistance from a wheeled suspension walker. To examine changes across development, we recorded infants across one to four sessions from 10 to 19 months of age. Results: Across developmental stages, we found that suspension walkers robustly increased infants' locomotor behavior: The walker increased upright time, percent time stepping, stepping rate, upright bout rate, percent time locomoting, and total bout rate. Most walker movement was initiated by caregivers, and infants stepped more while the walker was moving compared to stationary. Conclusions: Even without practice, pre-walking infants with DS were able to take advantage of the suspension walker to increase their locomotor behavior. Caregivers facilitated infants' activity by moving the walker. Future work will examine the potential of overground suspension walkers for home-based intervention.

Aims. It is unknown whether large language models (LLMs) can predict a trial's result at the design stage, from the information available when it is registered. We tested three LLMs prospectively on the Late-Breaking Science programme of the European Society of Cardiology (ESC) Congress 2026. Methods and results. Of 139 trials, 50 were selected by pre-specified criteria, and predictions were locked and registered on the Open Science Framework before the congress. Claude Fable 5, GPT-5.5 and Gemini 3.5 Flash, without web access, received each title and an investigator-compiled summary of the registered design. They gave the probability that the primary endpoint would be met, and a point estimate with an 80% prediction interval for a locked effect measure. Results were adjudicated from publications (19) or presenters' slides (31). Of 48 scorable trials, 28 (58%) were positive. The area under the receiver operating characteristic curve was 0.80 (95% CI 0.66-0.92) for Claude, 0.79 (0.66-0.91) for GPT and 0.74 (0.59-0.87) for Gemini, with accuracies of 73%, 71% and 67%. Among 26 trials whose effect was reported exactly as locked, the direction was correct in 88% of predictions and the median multiplicative error of ratio estimates was about 15%. The 80% prediction intervals contained the observed effect in 73.1% (Claude), 84.6% (GPT) and 57.7% (Gemini). Conclusion. From the registered design alone, LLMs showed statistically significant discrimination between positive and negative trials and usually predicted the direction and approximate size of the effect. Such predictions might help trial design, and further studies are needed.

As digital self-triage becomes more widely used, quality assurance requires evaluation of both emergency recognition and overall agreement with clinical judgement, including how these outcomes differ across generations of large language models. The Benchmark Self-Triage (BeST) project intends to provide a framework to compare systems for digital self-triage against a medical 'gold standard' in Germany. In a first step developing the method and demonstrating its potential we developed a representative set of patient vignettes and compared two regulated medical-device triage systems, SmED and Infermedica, with five structured OpenAI configurations spanning multiple model generations: gpt-4.1, gpt-5.4, gpt-5.6-luna, gpt-5.6-sol, and gpt-6-astra. An LLM-based patient actor covered 480 physician-curated vignettes derived from German routine triage data. A pool of seven physicians provided preliminary reference classifications and consensus for 480 vignettes. Recommendations were mapped to three urgency categories 'emergency', 'acute', and 'not urgent' and evaluated using winsorised weights derived from routine triage frequencies. Weighted emergency sensitivity ranged from 51.3% (95% CI 35.5-66.3%) for gpt-4.1 to 99.9% (99.7-100.0%) for gpt-6-astra. Weighted exact three-category agreement (accuracy) ranged from 54.4% to 68.8%; gpt-4.1 achieved the highest agreement despite the lowest emergency sensitivity. No system performed best across all urgency categories. The later-generation OpenAI configurations showed a more precautionary triage profile resembling SmED, with higher sensitivity for emergency cases; gpt-6-astra showed the strongest shift. This cross-sectional comparison across model generations suggests a shift towards more precautionary triage behaviour, without establishing a longitudinal improvement in accuracy. These findings highlight the limitations of overall agreement for evaluating self-triage and support category-specific assessment. Broader expert consensus and evaluation, as well as further steps to reduce dependence on SmED-derived source data, are needed and planned before drawing conclusions about clinical safety.

Introduction: The TREOCAPA (Prophylactic TREatment Of the duCtus Arteriosus in Preterm infants by Acetaminophen) trial was a pan-European, multi-centre, phase II/III trial investigating the impact of prophylactic paracetamol (also known as acetaminophen) given during the first 5 days of life for children born before 29 weeks' gestational age (GA) on survival to 36 weeks' post-menstrual age without severe neonatal morbidities. However, due to time restrictions, long-term follow-up was not planned as part of the initial trial despite recommendations for neonatal trials to include endpoints measuring efficacy after discharge from the neonatal unit and on-going debate about the long-term effects of paracetamol in the neonatal period. This protocol describes a study to follow-up participants in the TREOCAPA trial at 2 years corrected age initiated after the trial's onset. Methods and analysis: The TREOCAPA Long Term (TREOCAPA-LT) study population consists of all children included in the TREOCAPA phase III trial in centres in countries participating in the follow-up study who are aged between 23.5 and 27.5 months corrected age during the study period. Families are contacted by the clinical teams and a parent or guardian is invited to complete an internet-based (online) questionnaire. The primary outcome is cognition, as measured by the non-verbal Cognitive Scale standard score from the Parent Report of Children's Abilities-Revised (PARCA-R) questionnaire. Secondary outcomes are moderate to severe neurodevelopment, health service use and costs. Data will be analysed according to the study groups to which children were randomised in the original TREOCAPA RCT. Ethics and Dissemination: The TREOCAPA-LT protocol was first approved by ethics' committees in France (the study's sponsor) and subsequently by all participating countries. Results from TREOCAPA-LT will be published in open access journals in accordance with the funder's regulations. Registration: https://clinicaltrials.gov/study/NCT06064825