To evaluate the impact of digital supportive supervision (DiSS) for maternal and child healthcare on utilisation of services in Rajasthan state of India, as well as exploring the perceived enablers and barriers to the implementation of DiSS.

We employed a sequential mixed-method study design. Routine monthly service data from April 2016 to March 2023 were analysed using an interrupted time-series (ITS) analysis with a control group, followed by qualitative in-depth key-informant interviews.

The study is set at the primary healthcare level in Rajasthan state in India, where maternal health, child health and nutrition (MCHN) sessions are conducted at village level to deliver essential maternal and child health services.

Based on the proportion of MCHN sessions supervised digitally, two districts demonstrating high DiSS uptake were selected as intervention districts, and two matched districts were identified as comparator districts, creating a quasi-experimental design. Using routine data extracted from the pregnancy, child tracking and health services database, a segmented regression analysis using ITS was undertaken to assess temporal changes in service utilisation. For the qualitative component, we purposively sampled supervisors in intervention districts (ranked by DiSS supervisory volume) and conducted interviews until thematic saturation (n=18).

The intervention involved digitising the traditional paper-based supportive supervision of MCHN sessions in Rajasthan through a DiSS tool. Supervisors across state, district, block and sector levels used smartphones or tablets to record MCHN session data offline, which was automatically analysed and reported on dashboards on submission.

The study aims to measure the change in the monthly rate of MCHN service uptake following the rollout of DiSS in Rajasthan state.

Pentavalent and inactivated-polio vaccine uptake significantly improved in the intervention group, while no change was observed in the comparator group. Both groups showed significant improvement in the iron and folic acid supplementation among pregnant women and uptake of BCG, Hepatitis B birth dose and Measles vaccines among children, with greater increase in the intervention group. Notably, pneumococcal-conjugate-vaccine uptake declined significantly in the comparator group, whereas no significant change occurred in the intervention group. Limited digital literacy during the initial rollout and compatibility restriction of the digital application to Android devices were chief barriers. Among the enablers, its user-friendly interface, offline functionality, GIS-based monitoring and automated report generation were reported to enhance the timeliness, accountability and efficiency of supportive supervision. This, in turn, strengthened the feedback loop, empowering programme managers to promptly identify and address any shortcomings.

DiSS has the potential to strengthen the healthcare system and significantly improve the utilisation of MCHN services.

To identify enablers and barriers for scaling up non-communicable disease (NCD) interventions across diverse global contexts and to map these factors to the WHO’s health system building blocks.

A multi-method qualitative study applying the Consolidated Framework for Implementation Research to analyse data from multiple projects nearing or completing scale-up.

Global Alliance for Chronic Diseases-funded implementation research projects conducted across 18 low- and middle-income countries and high-income settings.

Data was derived from documents (n=77) including peer-reviewed publications, policy briefs, and reports and interviews with stakeholders (n=18) (eg, principal investigators, medical professionals, public health workers).

Various context-specific interventions targeting sustainable scale-up of NCD (eg, diabetes, hypertension, cardiovascular disease) interventions at the community, primary care or policy levels.

The primary outcome was identifying contextual enablers and barriers to intervention scale-up. Secondary outcomes included exploring how these factors aligned with health system building blocks (eg, leadership/governance, healthcare workforce).

Twenty enablers (eg, intervention adaptability, strong stakeholder engagement, local empowerment) and 25 barriers (eg, resource limitations, intervention complexity, stakeholder burnout) were identified. Contextual alignment, supportive governance and capacity building were critical for sustainability, while cultural misalignment and socio-political instability frequently hampered scaling efforts.

Tailoring interventions to local health systems, ensuring stakeholder co-ownership and incorporating strategies to mitigate stakeholder burn-out are essential to achieving sustainable, scalable NCD solutions. Future research should focus on integrating systematic cultural adaptation, sustainable financing and workforce capacity building into scale-up planning.

Breast cancer is common and women requiring mastectomy will be offered a breast reconstruction if they are surgically suitable candidate. Breast reconstruction can be performed at the same time as the mastectomy (immediate) or delayed to a second operation after cancer treatments. The reconstruction can either use the patients’ own tissue to make the breast (autologous) or use a prosthesis to make the breast in the form of a fixed or expandable volume implant (implant-based breast reconstruction, IBBR). Immediate breast reconstruction on top of the chest wall muscles (prepectoral) is performed worldwide. This operation involves the use of a synthetic or biological mesh placed around the implant under the skin. Increasingly, surgeons are performing this technique without the use of mesh. Both techniques, with and without mesh, have not been compared in a head-to-head randomised controlled trial (RCT); therefore, surgeons and patients do not have high quality data to guide their decision making in this area.

UK-based pragmatic multicentre randomised controlled feasibility trial. The primary aim is to determine the feasibility of a definitive RCT comparing the clinical and cost-effectiveness of no-mesh versus mesh-assisted prepectoral breast reconstruction. Secondary objectives will explore patient understanding of mesh and willingness to be randomised within an RCT; determine if it is possible to collect data to inform a future economic analysis on the use of mesh in breast reconstruction and determine the feasibility of measuring breast biomechanics pre-surgery and post breast reconstruction surgery. Total number of patients to be included: 40 (20 per arm).

This study will be conducted in compliance with the Declaration of Helsinki. Ethical approval has been obtained. Ethics Ref: 23/SC/0302; IRAS Project ID: 301 423. The results of this study will be published in a peer-reviewed medical journal, independent of the results, following the Consolidated Standards of Reporting Trials standards for RCTs.

NCT06112977; ISRCTN17470747.

Traumatic brain injury (TBI) remains a major public health concern in India, with high mortality and long-term disability. Existing prognostic models, mostly developed in high-income countries using traditional methods, lack generalisability to the Indian context and do not use the potential of machine learning or multicentric data. This study primarily aims to develop, compare and validate machine learning methods, including the traditional approach, to predict 30-day mortality and 6-month functional outcomes in patients with moderate or severe TBI. A secondary objective is to describe and compare admission characteristics and outcomes (at discharge, 3 months, 6 months and 1 year) in TBI patients in tertiary care settings using descriptive analyses.

Data from the neurotrauma registry at Jai Prakash Narayan Apex Trauma Centre, department of neurosurgery, All India Institute of Medical Sciences (AIIMS), New Delhi, including patients admitted between 23 March 2022 and 22 September 2024, will be used for model development and internal validation. For external validation, retrospectively collected data from the same centre (May 2010 to August 2013) and prospectively collected data from AIIMS Patna (1 June 2022 to 30 November 2024) and Rajiv Gandhi Government General Hospital, Madras Medical College (MMC), Chennai (1 May 2022 to 31 October 2024) will be included. Prediction models for 30-day mortality and 6-month functional outcomes will be developed using both machine learning and traditional statistical techniques. Model performance will be evaluated based on discrimination, calibration and clinical utility, with the latter assessed through decision curve analysis (DCA). An online risk calculator will be developed based on the best-performing model to estimate outcome probabilities along with 95% CIs.

The institutional Ethics Review Board of respective data collection centres, that is, AIIMS, New Delhi, AIIMS, Patna, and MMC, Chennai, approved the study. Findings will be published in peer-reviewed journals and disseminated at national and international conferences.

This study will develop and validate prognostic models using traditional and machine learning methods tailored to the Indian TBI context. Multicentric, prospectively collected data will enhance generalisability, while clinical utility will be evaluated through DCA. Adherence to Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis + Artificial Intelligence (TRIPOD+AI) guidelines ensures methodological transparency. With external validation, these models may improve clinical decision-making, resource planning and patient-family communication in diverse Indian healthcare settings.

Air pollution is a significant global health concern, with studies from the USA and Europe linking long-term exposure to respiratory issues and poor school attendance in children. While Indian cities experience much higher pollution levels, the impact on lung development in Indian children remains unclear. This study aims to assess the burden of impaired lung function in Indian children and identify key factors contributing to pollution-induced lung injury.

This longitudinal, prospective cohort study is conducted in four cities categorised by particulate matter 2.5 (PM_2.5) levels: ‘very high’ (Delhi), ‘high’ (Mumbai, Bangalore) and ‘moderate’ (Mysore). A total of 4000 participants (1000 from each city) will be included in the study. Participants will complete a structured questionnaire covering sociodemographics, asthma and allergy history (International Study of Asthma and Allergies in Childhood core questionnaire), dietary intake (24-hour recall and Food Frequency Questionnaire), Physical Activity-C Questionnaire and air pollution exposure. Spirometry and Forced Oscillation Technique will be used to assess lung function. Blood samples will be collected for identification of biomarkers to predict lung impairment. After quality checks, data will be compiled, summarising pulmonary function parameters alongside covariates and confounders. Analysis of Variance (ANOVA) will assess between-city and within-city differences in lung function.

We anticipate a higher prevalence of reduced lung function in children residing in cities with very high and high PM_2.5 levels compared with the moderately polluted city. Findings from this study could establish normal age-appropriate lung function reference values for Indian urban children, aiding in clinical diagnosis.If a reliable biomarker for identifying children at risk of lung impairment is available, it could serve as an early predictor of poor lung health in asymptomatic children.

The approval from individual site institutional review board (IRB) is obtained prior to initiation of the study from institutional ethics committee, St. John’s Medical College and Hospital, Bangalore; institutional ethics committee, JSS Medical College, Mysore; institute ethics committee, Indian Institute of Technology Bombay and institute ethics committee, All India Institute of Medical Sciences. Findings from this study will be disseminated through conference presentations, peer-reviewed publications and establishment of normal age-appropriate lung function reference values for children living in urban India.