To estimate the treatment outcomes among individuals treated for hypertension in the public sector in 89 districts across 15 states in India and to identify the risk factors for uncontrolled blood pressure (BP).

An analysis of a cohort of people with hypertension from 2018 to 2022 from public sector health facilities.

All India Hypertension Control Initiative (IHCI) implementing districts using digital information systems across 15 states of India, namely Andhra Pradesh, Bihar, Goa, Gujarat, Jharkhand, Karnataka, Maharashtra, Nagaland, Puducherry, Punjab, Rajasthan, Sikkim, Tamil Nadu, Uttar Pradesh and West Bengal.

Individuals aged 30 years or older, who were diagnosed with hypertension or on medication at the time of registration between 1 January 2018 and 31 December 2021 were included in the study.

Treatment outcomes were controlled BP, uncontrolled BP and missed visits in the reporting quarter (1 January 2022–31 March 2022). We analysed the risk factors for uncontrolled BP.

Out of 1, 235, 453 hypertensive individuals enrolled in the IHCI project across 15 states, 1, 046, 512 remained under care, with 44% BP control. The control varied from 26% to 57% in various types of facilities. The states of Maharashtra, Punjab and Rajasthan had above 50% control, while Nagaland, Jharkhand and Bihar had below 25%. BP control declined from 68% when defined using a single recent reading to 52% when defined using the two-visit readings. Younger individuals (

We documented the implementation of IHCI strategies at scale and measured treatment outcomes in a large cohort. Overall, BP control improved with variations across states. We need focused strategies to improve control in higher-level facilities, among males and people with diabetes. Using two BP readings may support consistent treatment adherence.

Three-quarters of mental health problems start before the age of 25. However, young people are the least likely to receive mental healthcare. Some young people (such as those from ethnic minorities) are even less likely to receive mental healthcare than others. Long-term impacts of mental health problems include poorer physical health, relationships, education and employment. We aim to elicit the views, experiences and needs of diverse young people (aged 16–24 years), to better understand (1) their experiences of under-representation, mental health and coping, (2) mechanisms that shape mental health trajectories and (3) how online arts and culture might be made engaging and useful for young people’s mental health. We also aim to do this with autistic young people.

Narrative inquiry will be employed as a tool for gathering young people’s perspectives for an iterative analysis. The narrative method proposes that critical insights and knowledge are distributed across social systems and can be discovered in personal stories and that knowledge can be relayed, stored and retrieved through these stories. Data will be transcribed and explored using a combination of thematic and intersectional analysis. Young people will be core members of the research team, shape the research and be involved in the coding of data and interpretation of the findings.

This study (IRAS project ID 340259) has received ethical approval from the HRA and Health and Care Research Wales (REC reference 24/SC/0083). The outputs will identify touch points and refine the logic model of how online arts and culture might support the mental health of those from under-represented backgrounds. We will share knowledge with young people, policy makers, health professionals, carers, teachers, social workers and people who work in arts and culture. We will produce research papers, blogs, newsletters, webinars, videos and podcasts.

This project explores the feasibility of setting up a neuropsychiatric de-identified database (DiD) and a Research Register (RR) to collect, analyse, monitor and systematically report clinical data for people with intellectual disabilities (PwIDs) and epilepsy.

A multicentre project designed to collect de-identified data from clinical records at three adult ID specialist services in England and Wales and to develop an RR of PwID and epilepsy. Patients added to the DiD will be identified from patient clinic lists, clinic letters, in-house databases and electronic systems. Patients to be added to the RR will also be identified through attendance for regular review at clinic appointments. The collected data will be entered into the Research Electronic Data Capture (REDCap) database. Personal details of PwID and their consultees will also be collected from participants who consent to be on the RR. Around 600 PwID and epilepsy (200 per site) will be added to the DiD at the three sites, while around 45–60 participants (15–20 per site) are anticipated to be added to the RR. Data analysis will involve using descriptive statistics to summarise feasibility outcomes, such as screening and recruitment rates, as well as the completeness of the collected data. The characteristics of the participants (demographic, ID classification, clinical, epilepsy history and antiseizure medication) will be summarised descriptively. Progression will be assessed using the Red/Amber/Green stop-go criteria to determine if a national register should be created.

Ethical approval (24/NW/0210) has been obtained from the Northwest-Haydock Research Ethics Committee and the University of Plymouth Faculty Research Ethics and Integrity Committee (reference no. 5284). The project is funded by Jazz Pharmaceuticals as an independent investigator-initiated support grant and, as such, has received independent peer review.

NCT06780501.

Patients who survive admission to intensive care unit (ICU) for critical illness are at high risk of developing muscle atrophy and weakness, commonly diagnosed as ICU-acquired weakness (ICUAW). The development of ICUAW is closely linked to long-term symptoms and impairments known as post-intensive care syndrome (PICS). Despite heightened recognition of impairments, there is limited research supporting effective interventions to improve muscle and physical outcomes after hospital discharge. Prior to developing and testing interventions for ICU survivors, it is imperative to understand the trajectory of muscle and physical function recovery following an ICU stay. The purpose of this study is to longitudinally investigate skeletal muscle health and physical function outcomes after ICU admission.

This protocol describes a single site, prospective, observational study in adult patients who have survived a critical illness (ie, sepsis or acute respiratory failure). Patients will participate in a battery of testing including primary outcomes: muscle power and physical function; and secondary outcomes: muscle strength, muscle size, endurance and physical activity (by accelerometry) at hospital discharge and 3, 6, and 12 months post-discharge. A subset of patients will participate in muscle biopsy and venipuncture. To examine if the trajectory of recovery predicts primary outcomes, we will perform multivariate linear regression models in 150 evaluable patients. To examine differences in molecular and cellular outcomes in plasma and muscle tissue, a control group of community-dwelling adults without history of an ICU stay will be enrolled as a comparator group. Enrolment started on 18 October 2022 with an estimated completion date of 1 August 2027.

This protocol was approved by the University of Kentucky Office of Research Integrity Medical Internal Review Board (# 77407), with patients providing informed written consent. We anticipate our findings to establish recovery trajectories, improving the classification of patients who experience sustained physical disability. Improved identification of recovery trajectories of muscle and physical function enables future studies to employ an individually targeted rehabilitation approach, that is, precision medicine, with the goal of improving patient outcomes. The cellular findings will support the development of novel interventions specifically designed for detecting underlying mechanisms. We intend to disseminate findings to patients, healthcare professionals, the public and other relevant groups via conference presentations and manuscripts without publication restrictions.

NCT05537298.

Social isolation and loneliness are prevalent among older adults and associated with negative health outcomes. Virtual reality (VR) interventions have emerged as a potential approach to address this problem, but their effectiveness remains unclear. This systematic review aims to synthesise evidence on the effects of VR interventions on social isolation and loneliness in adults aged 60 years and older.

We will search PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, PsycINFO and Scopus from inception to February 2025 for randomised controlled trials, quasi-experimental studies and before-after studies that evaluate VR interventions compared with usual care, wait-list, no treatment or other active interventions in older adults. The primary outcomes will be measures of social isolation and loneliness assessed with validated scales. Secondary outcomes will include depression, quality of life, cognitive function, physical function and adverse events. Two reviewers will independently screen, select and extract data from studies. Risk of bias will be evaluated using the Cochrane Risk of Bias Tool 2 for randomised trials and ROBINS-I for non-randomised studies. If feasible, meta-analysis will be performed; otherwise, a narrative synthesis will be conducted. The quality of evidence will be assessed using GRADE.

Ethical approval is not required for this systematic review, as it will only include published data. The review findings will be disseminated through a peer-reviewed publication and conference presentations.

CRD42025637230.

Artificial intelligence (AI) has the potential to revolutionise healthcare delivery, particularly in the domain of emergency medicine. With the rise of telemedicine and virtual care, AI-powered tools could assist in triage, diagnosis and treatment recommendations for patients seeking emergency care remotely. This systematic review aims to synthesise the current state of research on AI applications in virtual emergency care, identify key challenges and opportunities and provide recommendations for future research and implementation.

We will conduct a comprehensive search of multiple electronic databases (PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, Scopus) from each database’s inception to March 2025. The search will include terms related to AI, machine learning, deep learning, virtual care, telemedicine and emergency medicine. We will include original research articles, conference proceedings and preprints that describe the development, validation or implementation of AI models for virtual emergency care. Two reviewers will independently screen titles and abstracts, review full texts, extract data and assess risk of bias using the PROBAST (Prediction model Risk Of Bias ASsessment Tool) tool for prediction model studies, Cochrane Risk-of-Bias tool for randomised trials for randomised trials and Risk Of Bias In Non-randomised Studies of Interventions for non-randomised studies. Data synthesis will involve a narrative review of included studies, summarising key findings, methodological approaches and implications for practice and research. The results will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

No ethical approval is required for this systematic review as it will use only published data. The findings will be disseminated through publication in a peer-reviewed journal, presentations at relevant conferences and engagement with clinicians, health system leaders, policymakers and researchers. This review will provide a timely and comprehensive overview of the applications of AI in virtual emergency care to inform evidence-based guidelines, policies and practices for leveraging these technologies to enhance access, quality and efficiency of emergency care delivery.

CRD42025648202.

Virtual reality (VR) technology is increasingly being explored as a medium for delivering mindfulness-based interventions. While studies have investigated the feasibility and efficacy of VR-based mindfulness interventions, there has been limited synthesis of user experiences and perceptions across diverse applications, hindering the iterative refinement of these technologies and limiting evidence-based guidance for effective deployment in real-world settings. This systematic review aims to comprehensively identify, appraise and synthesise qualitative research on end-user experiences and perceptions of VR-based mindfulness interventions. Understanding user experiences is critical for translating research findings into practical design improvements and implementation strategies that enhance intervention effectiveness and user adoption.

A systematic search will be conducted in PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, PsycINFO and Scopus from inception to present. Studies reporting qualitative data on adult participants’ experiences, perceptions, attitudes or opinions related to VR-based mindfulness interventions will be included. Two independent reviewers will screen studies, extract data and assess methodological quality using the Critical Appraisal Skills Programme checklist. Thematic synthesis will be used to analyse the qualitative data. The Grading of Recommendations Assessment, Development and Evaluation-Confidence in the Evidence from Reviews of Qualitative Research approach will be applied to assess confidence in the review findings.

Ethical approval is not required as this review will be based on published studies. The findings will be disseminated through peer-reviewed publication and conference presentations.

CRD42024594330.

This study aimed to evaluate the cost-effectiveness of integrating nutritional support into India’s National Tuberculosis Elimination Programme (NTEP) using the MUKTI initiative.

Economic evaluation.

Primary data on the cost of delivering healthcare services, out-of-pocket expenditure and health-related quality of life among patients with tuberculosis (TB) were collected from Dhar district of Madhya Pradesh, India.

Integration of nutritional support (MUKTI initiative) into the NTEP of India.

Routine standard of care in the NTEP of India.

Incremental cost per quality-adjusted life year (QALY) gained.

A mathematical model, combining a Markov model and a compartmental susceptible–infected–recovered model, was used to simulate outcomes for patients with pulmonary TB under NTEP and MUKTI protocols. Primary data collected from 2615 patients with TB, supplemented with estimates from published literature, were used to model progression of disease, treatment outcomes and community transmission dynamics over a 2-year time horizon. Health-related quality of life was assessed using the EuroQol 5-Dimension 5-Level scale. Costs to the health system and out-of-pocket expenditures were included. A multivariable probabilistic sensitivity analysis was undertaken to estimate the effect of joint parameter uncertainty. A scenario analysis explored outcomes without considering community transmission. Results are presented based on health-system and abridged societal perspectives.

Over 2 years, patients in the NTEP plus MUKTI programme had higher life years (1.693 vs 1.622) and QALYs (1.357 vs 1.294) than those in NTEP alone, with increased health system costs (11 538 vs 6807 (US$139 vs US$82)). Incremental cost per life year gained and QALY gained were 67 164 (US$809) and 76 306 (US$919), respectively. At the per capita gross domestic product threshold of 161 500 (US$1946) for India, the MUKTI programme had a 99.9% probability of being cost-effective but exceeded the threshold when excluding community transmission.

The findings highlight the potential benefits of a cost-effective, holistic approach that addresses socio-economic determinants such as nutrition. Reduction in community transmission is the driver of cost-effectiveness of nutritional interventions in patients with TB.

Artificial intelligence (AI) technologies are increasingly being developed and deployed to support clinical decision-making, care delivery and patient monitoring in healthcare. However, the adoption of AI-driven solutions by nurses, who comprise the largest segment of the healthcare workforce and are central to patient care, has been limited to date. Understanding nurses’ perceptions of barriers and facilitators to AI adoption is critical for successful integration of AI in nursing practice. This systematic review aims to identify, appraise and synthesise qualitative evidence on nurses’ perceived barriers and facilitators to adopting AI-driven solutions in their clinical practice.

We will conduct systematic searches across eight electronic databases (PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, PsycINFO and Scopus) from inception to January 2025, supplemented by hand-searching reference lists and grey literature. Primary qualitative studies and qualitative components of mixed-methods studies exploring licensed/registered nurses’ perceptions of AI adoption in clinical settings will be included. Two independent reviewers will screen studies, extract data using standardised forms and assess methodological quality using the Critical Appraisal Skills Programme checklist. We will employ meta-ethnography to synthesise the qualitative evidence, involving systematic comparison and translation of concepts across studies to develop overarching themes and a theoretical framework. The Grading of Recommendations Assessment, Development and Evaluation Confidence in the Evidence from Reviews of Qualitative Research (GRADE-CERQual) approach will be used to assess confidence in review findings. The protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines and the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) statement.

No ethical approval is required as this systematic review will synthesise data from published studies only. The findings will provide valuable insights to inform the development, implementation and evaluation of nurse-oriented strategies for AI integration in healthcare delivery. Results will be disseminated through peer-reviewed publication, conference presentations and stakeholder engagement activities.

CRD42024602808.

This study conducted a comprehensive probabilistic cost-effectiveness analysis comparing robotic exoskeleton therapy to conventional physiotherapy for stroke rehabilitation in Singapore, focusing on three patient groups categorised by their Functional Ambulation Category (FAC) scores.

A probabilistic cost-effectiveness analysis was conducted alongside a non-randomised controlled study. Costs and Quality-Adjusted Life Years (QALYs) for both interventions were calculated and compared over a 6 month period.

The study was carried out at Alexandra Hospital, Jurong Community Hospital and St Luke’s Hospital in Singapore.

Individuals requiring inpatient gait rehabilitation from acute to subacute stages of stroke recovery, with FAC scores of 0–1, were included in the analysis.

The primary outcome measure was QALYs, a composite measure combining the length and quality of life into a single value.

Robotic exoskeleton therapy was found to be cost-effective compared with conventional physiotherapy across all patient groups, with Group 2 (FAC 0) showing the most favourable cost-effectiveness profile (incremental cost-effectiveness ratio (ICER): US$ 28 259.62 per QALY gained). The probabilistic sensitivity analysis demonstrated the robustness of the results, with QALY gains and the cost of the robotic exoskeleton having the largest impact on the ICER.

The findings suggest that robotic exoskeleton therapy is likely to be cost-effective for stroke rehabilitation in Singapore, particularly for patients with severe mobility impairments (FAC 0). The results have important implications for clinical practice, resource allocation and future research in the field of stroke rehabilitation in Singapore.

NCT05659121.