ReviewFrontiers in surgery2026
Risk factors for recurrence and surgical site infection after abdominal wall hernia repair: a systematic review and meta analysis.
Review in Frontiers in surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
Background: Surgical site infection (SSI) and hernia recurrence are among the most common and impactful complications following abdominal wall hernia repair. Identifying patient-related risk factors is essential for improving outcomes and guiding perioperative management. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA 2020 and AMSTAR 2 guidelines. PubMed, Embase, Scopus, CNKI,Wanfang, and VIP were searched up to September 20,2025. Eligible studies included randomized controlled trials, cohort, and case-control studies that reported associations between patient-related variables and SSI or recurrence after hernia repair. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random-effects models. Beyond I Results: A total of 11 studies involving 97,428 patients were included. No significant associations were observed for female sex (OR: 1.05, 95% CI: 0.77-1.42, Conclusions: Contrary to common clinical assumptions, traditional host-related risk factors such as gender, obesity, and diabetes do not consistently predict adverse outcomes after abdominal wall hernia repair when clinical heterogeneity is rigorously accounted for. The wide 95% PIs observed for most factors underscore substantial clinical variance across surgical settings. These findings highlight the limitations of relying on isolated comorbidities for risk assessment and advocate for the development of integrated, individualized risk prediction models. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD420261278753, identifier CRD420261278753.
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