Background/Objectives: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are increasingly used for the management of obesity and type 2 diabetes, particularly among women of reproductive age. Emerging evidence suggests potential effects on ovulation, fertility, and pregnancy outcomes. This narrative review aims to synthesize current evidence on the reproductive safety of GLP-1RAs, with a focus on their implications for conception, unintended pregnancy, and maternal–fetal outcomes. Methods: A narrative literature review was conducted using PubMed and relevant bibliographic sources to identify studies published between 2020 and 2025. The search included clinical trials, observational studies, registry data, case reports, and selected preclinical evidence. Studies addressing reproductive outcomes, including ovulation, fertility, pregnancy exposure, and fetal safety, were included. Evidence was synthesized descriptively in accordance with recommended approaches for narrative reviews. Results: Available evidence indicates that GLP-1RAs may improve ovulatory function and menstrual regularity, particularly in women with obesity or polycystic ovary syndrome, potentially increasing the likelihood of conception. However, human data on pregnancy exposure remain limited. While current evidence does not consistently demonstrate a strong teratogenic signal, findings are based on small samples and heterogeneous study designs. Concerns persist regarding unintended pregnancies due to improved fertility and the absence of robust safety data during early gestation. Conclusions: GLP-1RAs present a complex clinical scenario in women of reproductive age, with potential benefits for metabolic and reproductive health but uncertain safety during pregnancy. Clinicians should exercise caution, provide appropriate contraceptive counseling, and carefully weigh the risks and benefits when prescribing these agents. Further large-scale, prospective studies are needed to clarify reproductive safety and inform evidence-based clinical guidelines.

Background/Objectives: Recurrent urinary tract infection (rUTI) is common after menopause, but estrogen deficiency alone does not explain variation in recurrence, symptoms, and microbial profiles. This study aimed to synthesize evidence on the interactions among estrogen deficiency, urogenital microbial ecology, diabetes, obesity, microbial reservoirs, and anatomical, neurological, and functional modifiers of postmenopausal rUTI susceptibility. Methods: PubMed and Scopus were searched for original studies published from 1 January 2021 to 15 June 2026. A structured narrative synthesis included 62 original reports comprising clinical interventions, observational cohorts, microbiome and multi-omic studies, and cellular and animal experiments. Evidence was interpreted according to study design, population relevance, and biological directness. Results: Menopause was associated with reduced Lactobacillus dominance, higher vaginal pH, and altered vaginal or urinary communities, although findings were heterogeneous. Vaginal estrogen reduced recurrence and improved the local urogenital environment, but microbiome restoration is not established as its sole mechanism. Gut, rectal, vaginal, urinary, and bladder-wall reservoirs may contribute to persistence or repeated exposure. Diabetes was linked to dysbiosis and impaired urothelial defence, whereas obesity evidence remained less direct. Pelvic organ prolapse with incomplete emptying, elevated postvoid residual urine, age-related detrusor dysfunction, stroke, immobility, functional dependence, incontinence, and catheter exposure may further modify susceptibility. Conclusions: Postmenopausal rUTI is multifactorial. The urogenital microbiome–metabolic interface is a useful integrative framework, but not a validated causal or diagnostic model. Vaginal estrogen, urine culture, metabolic and bladder-function assessment, and antimicrobial stewardship remain the clinical foundation; microbiome-directed strategies require prospective validation.

Background/Objectives: The optimal dialysate calcium concentration in maintenance hemodialysis remains uncertain because reducing calcium exposure may limit calcium loading but can also stimulate parathyroid hormone secretion and impair intradialytic cardiovascular stability. We evaluated randomized evidence across bone, mineral metabolism, vascular, and acute safety outcomes. Methods: PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), and Scopus were searched from database inception through 10 July 2026, with targeted citation and publication-status updating through 1 August 2026. Randomized parallel, crossover, factorial, and multi-period trials comparing dialysate calcium concentrations in adults receiving hemodialysis or hemodiafiltration were eligible. Acute and chronic outcomes were analyzed separately. Pooled estimates used inverse-variance random-effects models with DerSimonian–Laird estimation and modified Hartung–Knapp confidence intervals. Results: Twenty-four randomized parent trials were included. Lower dialysate calcium reduced end-of-dialysis ionized calcium (paired mean difference, −0.193 mmol/L; 95% CI, −0.258 to −0.128), with substantial heterogeneity. Point estimates for chronic parathyroid hormone and total alkaline phosphatase were higher and serum calcium lower, but all confidence intervals crossed the null. No clear effects were demonstrated for phosphate, calcium–phosphate product, lumbar bone mineral density, coronary artery calcification, or carotid intima–media thickness. Acute parathyroid hormone, blood pressure, calcium-balance, and QTc estimates suggested greater parathyroid stimulation, lower hemodynamic measures, less calcium gain, and longer QTc with lower calcium, but were imprecise. Adverse events were unsuitable for pooling. Conclusions: Lower dialysate calcium consistently lowers postdialysis ionized calcium, but its long-term skeletal and vascular effects remain uncertain. No single concentration appears universally optimal; prescription should be individualized according to mineral metabolism phenotype, cardiovascular tolerance, dialysis modality, and concomitant therapy.

Background: Postoperative sepsis and related infectious complications remain major causes of morbidity after abdominal surgery. Artificial intelligence (AI) and machine learning (ML) models may support earlier risk stratification, but their generalizability and clinical readiness remain uncertain. Methods: We systematically searched PubMed, Scopus, and CENTRAL from inception to 10 August 2026 for studies developing, validating, or evaluating AI/ML models for postoperative sepsis, postoperative infection/surgical-site infection (SSI), anastomotic leakage, or postoperative pancreatic fistula (POPF) after major abdominal or general surgery. SSI, anastomotic leakage, and POPF were analyzed as distinct postoperative endpoints and were not treated as proxy definitions of clinical sepsis. Study selection and data extraction were performed independently by two reviewers, and risk of bias and applicability were assessed using PROBAST + AI. Owing to substantial clinical and methodological heterogeneity, results were synthesized narratively. The review was registered in PROSPERO (CRD420261492111). Results: Forty-five studies were included: 11 addressed sepsis-related outcomes, including six studies with a primary sepsis-related modeled endpoint whose definitions ranged from consensus Sepsis-3 criteria to coded or SIRS-based definitions and a qSOFA-based proxy; 19 evaluated postoperative infection/SSI; eight anastomotic leakage; five POPF; and two broader postoperative complications. Performance varied according to outcome, surgical population, prediction timing, predictor availability, and validation strategy. Fifteen of 45 studies provided strict temporal, geographic/external-center, or independent-investigator evaluation of the principal model, with variable preservation of performance outside development settings. More complex ML methods did not reliably outperform conventional regression. Explicit calibration analysis was reported in 9/45 studies, decision-curve or net-benefit analysis in 7/45, and no study prospectively evaluated the impact of model-guided care on clinical outcomes. Certainty of evidence was very low for primary postoperative sepsis/septic-shock prediction, low for postoperative infection/SSI, and very low for anastomotic leakage and POPF. Conclusions: Although several AI/ML models showed promising predictive performance, the available evidence remains insufficient to support routine use of AI/ML prediction models across major abdominal surgical populations. Future studies should prioritize clearly defined clinical use cases, multicenter external validation, calibration, prospective workflow evaluation, and demonstration of actionable clinical benefit before routine implementation.

Background and Objectives: Surgical-site infection remains a major complication of clean orthopedic surgery, particularly when implants or instrumentation are used. Although shorter perioperative prophylaxis is generally accepted for most clean procedures, prolonged postoperative courses continue to be used in selected high-risk orthopaedic settings. This review evaluated whether comparative evidence supports such extension. Methods: PubMed/MEDLINE, Scopus, and Cochrane CENTRAL were searched from inception to 14 May 2026. Randomized trials and non-randomized comparative studies evaluating systemic prophylaxis duration were eligible for qualitative synthesis. The primary meta-analysis was restricted to randomized controlled trials with extractable surgical-site infection data. Risk ratios were pooled using a random-effects model. Subgroup, sensitivity, and publication-bias analyses were performed. Results: Thirty-six studies were included in the qualitative synthesis, and 11 randomized trials involving 3823 participants contributed to the primary meta-analysis. After incorporating the cluster-adjusted estimate from the cluster-randomized trial, prolonged prophylaxis did not demonstrate a statistically significant additional reduction in any surgical-site infection compared with shorter prophylaxis (RR = 1.07, 95% CI 0.86–1.34; prediction interval 0.83–1.38; I² = 0.0%). A sensitivity analysis excluding the cluster-randomized trial produced a similar result (RR = 1.11, 95% CI 0.88–1.40). Exploratory procedure-based subgroup analyses did not identify a statistically significant interaction, although each subgroup contained few trials. Secondary analyses showed no statistically significant difference for superficial or non-deep infection (RR = 1.19, 95% CI 0.79–1.77) or deep or complicated infection (RR = 0.85, 95% CI 0.55–1.32). Conclusions: Prolonged systemic prophylaxis has not demonstrated a consistent additional surgical-site infection-prevention benefit compared with shorter regimens. However, sparse events, wide confidence intervals, clinical heterogeneity, and low certainty preclude conclusions of equivalence or noninferiority. Further adequately powered trials are needed in higher-risk procedures.