Medicine & Health

This article reviews evidence and implementation experience on surgical site infection (SSI) prevention across infection prevention and control (IPC), antimicrobial stewardship (AMS), antimicrobial resistance (AMR), quality improvement, surveillance, safety culture, human factors, and emerging technologies, concluding that multimodal, context-adapted IPC interventions can substantially reduce SSI incidence without major capital investment, that persistent gaps remain in infrastructure, guideline implementation, surveillance, and environmental controls, that AMR further emphasizes the need to integrate AMS into surgical safety frameworks, and that artificial intelligence and objective diagnostic technologies may improve surveillance and early SSI detection, so that SSI prevention is both a

This retrospective diagnostic accuracy study enrolled 539 consecutive patients aged 60 years or older undergoing hip and pelvis radiography at two emergency departments, used a consensus panel of three musculoskeletal radiologists and two senior orthopaedic trauma surgeons blinded to AI output as the reference standard, and evaluated Milvue SmartUrgences, which classified radiographs as "YES," "NO," or "DOUBT"; 487 patients received definitive classifications and entered the primary analysis (mean age 83.4 years, SD 8.4; 66% female; 191 hip fractures identified by the reference standard), yielding sensitivity 97.4% (95% CI 94.0-98.9), specificity 86.5% (95% CI 82.1-89.9), positive predictive value 82.3% (95% CI 76.8-86.7), negative predictive value 98.1% (95% CI 95.6-99.2), accuracy 90.

This retrospective cohort study of 80 treatment-naive neovascular age-related macular degeneration patients followed for at least 4 years estimated retinal age from fellow-eye fundus photographs using the publicly available Japan Ocular Imaging Registry deep learning model and computed raw retinal age gap (retinal age minus chronological age), finding no association between raw or age-corrected retinal age gap and total injection number in the count analysis, while in an exploratory threshold-based analysis the ≥ 24-injection group had higher raw retinal age gap than the < 24-injection group (4.19 vs. 0.66 years, P = 0.039) and each 1-year increase in raw retinal age gap was associated with requiring ≥ 24 injections (OR 1.11; 95% CI, 1.01-1.22; P = 0.

This is a forward-looking article examining the emerging role of personalized medicine in facial plastic surgery, proposing that biologically, anatomically, and psychologically tailored approaches may refine both aesthetic and reconstructive care, and suggesting that genomics, pharmacogenomics, artificial intelligence, tissue engineering, and three-dimensional modelling may improve prediction of healing, treatment response, complication risk, and reconstructive requirements, while emphasizing that ethical challenges relating to privacy, bias, and equitable access must remain central.

Using the search terms 'management of lower limb pain in children with hypermobility-associated conditions', this study collated webpages from Google searches and the corresponding overviews presented by Gemini, assessed webpage quality with the Health Information Website Evaluation Tool and AI overview quality with the Quality Assessment of Medical Artificial Intelligence, and evaluating 20 webpages and four AI-generated overviews found that webpage quality was mostly moderate (14 moderate, three good) while all AI overviews were rated good, with accuracy the lowest-scoring domain for webpages and completeness and provision of resources and references the lowest-scoring domains for AI overviews.

This review article states that pharmacogenomics explains individual drug-response variation at the genetic level while artificial intelligence improves diagnostic accuracy, risk assessment, and treatment strategy through analysis of large and complex clinical, genetic, and imaging datasets, and that combining the two can support more individualized cardiovascular care and better clinical decision-making, though data security, ethical concerns, and insufficient clinical validation still limit widespread adoption.

This single-center prospective pilot study first implemented and evaluated a fully automatic All-in-One radiotherapy workflow on an integrated CT-linac in 20 patients with rectal cancer, sequentially completing CT simulation, AI-based autosegmentation, autoplanning, online verification, and beam delivery on one platform without patient repositioning; the workflow was completed in all patients, mean total treatment time was 37.5 ± 6.9 minutes, Dice similarity coefficients ranged from 0.83 to 0.95, three-dimensional gamma pass rates exceeded 95% in all patients, leukopenia occurred in 55.0%, and at follow-up 19 of 20 patients underwent surgery with 1 clinical complete response, an overall complete response rate of 15.0% and tumor regression grade 0-1 in 68.4% of surgical patients.

This study designed a zero-shot prompted LLM pipeline as a virtual mimic of a human reviewer for the QUIPS framework and applied it to 298 articles from previously published systematic reviews of prognosis studies in neurology across three domains (epilepsy, traumatic brain injury, stroke), finding limited LLM-human agreement (weighted kappa = 0.22, 95% CI 0.12-0.33) while tentatively suggesting, based on a small sample (n=5), that it may not be inferior to human-human agreement (weighted kappa = -0.25, 95% CI -1.04-0.54), with Wilcoxon signed-rank tests statistically significant (p < 0.05) across four bias domains and overall risk scores, and rank-biserial correlations demonstrating human raters' tendency to assign higher risk scores than LLM counterparts.