5683 papers
This mixed-methods study reveals that achieving inhaler sustainability across the UK respiratory care pathway requires whole-system action addressing interconnected factors like device design, prescribing practices, and recycling infrastructure, rather than focusing solely on device-level carbon emissions.
This study establishes an L1 vertebral CT attenuation threshold of ≤112.2 HU for opportunistic osteoporosis screening in liver cirrhosis patients and demonstrates that integrating liver-specific indicators, such as the MELD-Na score and ascites status, significantly improves risk stratification and reclassification compared to models based solely on age and BMI.
The PASS 4 PD study demonstrates that a newly developed Patient's Attitudinal Suitability Score, assessed by both nurses and nephrologists across seven domains, significantly predicts peritonitis, technique failure, and mortality in peritoneal dialysis patients, serving as a valuable tool for identifying suitable candidates and targeting specific training needs.
This study presents a novel deep learning framework that accurately predicts the daily maximum number of open operating rooms using historical surgical data, enabling healthcare managers to optimize resource allocation and improve patient care by better aligning staff capacity with anticipated demand.
This study presents and validates a rule-based pipeline in 3D Slicer that automatically converts pelvic and proximal femoral CT scans into clinically relevant subregions and landmarks, significantly reducing manual workload while maintaining high anatomical accuracy for normal adult anatomy.
Despite advancements in maternal diabetes management, moderately preterm infants of diabetic mothers continue to experience higher respiratory morbidity, including increased surfactant use and prolonged oxygen requirements, compared to their non-diabetic counterparts.
This retrospective analysis of the 2026 Bundibugyo virus outbreak in the DRC and Uganda demonstrates that source-traced official aggregate data can reveal critical operational signals regarding detected case growth, heterogeneous outcomes, and response bottlenecks, provided these findings are interpreted with explicit data-quality safeguards rather than as definitive causal estimates.
Although machine learning models appear to outperform the Glasgow-Blatchford Score in discrimination, a systematic review and network meta-analysis of 26 studies concludes that current evidence is too limited and of low certainty to support replacing established clinical scores with ML for routine management of non-variceal upper gastrointestinal bleeding.
This scoping review reveals that while person-centred care is recognized as vital for dementia diagnosis, current literature offers limited and conceptually unclear guidance that disproportionately focuses on clinical assessment and disclosure while neglecting longitudinal support, emerging technologies, and the co-production of care with people living with dementia.
This study analyzes passive surveillance data from Mizoram, India (2022–2025) to reveal a high enteric fever burden of 920 per 100,000 person-years, identifying that while cases cluster in urban centers, village-level determinants like poor WASH infrastructure and inadequate healthcare access significantly drive incidence and hospitalization, thereby underscoring the urgent need for strengthened surveillance, vaccination, and WASH investments in the India-Bangladesh-Myanmar border region.