ArticleJournal of orthopaedic surgery and research2025
Combining systemic inflammation biomarkers with traditional prognostic factors to predict surgical site infections in elderly hip fracture patients: a risk factor analysis and dynamic nomogram development.
Article in Journal of orthopaedic surgery and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Systemic Inflammatory Indexes as Predictors of Delirium, Thromboembolic Events, and Mortality After Hip Fracture and Major Orthopedic Surgery: A Meta-Analysis.Journal of Korean medical science · 2026Pooled it
- Risk prediction models for postoperative infections in patients with hip fractures: a systematic review and critical appraisal.Frontiers in medicine · 2026Pooled it
- Perioperative Inflammatory Biomarkers and Surgical Site Infection After Pelvic and Acetabular Fracture Surgery: A Retrospective Cohort Study.Journal of clinical medicine · 2026Article
- Article
- Mechanistic Potentials of Natural Herbal Medicines (NHMs) in Promoting Bone Regeneration: A Comprehensive Review.Current drug metabolism · 2026Review
- Article
- Reply to "Disregarding C-reactive protein in an inflammation-based nomogram?"International journal of colorectal disease · 2025Article
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5 authors.
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Abstract
backgroundSystemic inflammation biomarkers have been widely shown to be associated with infection. This study aimed to construct a nomogram based on systemic inflammation biomarkers and traditional prognostic factors to assess the risk of surgical site infection (SSI) after hip fracture in the elderly.
methodsData were retrospectively collected from patients over 60 with acute hip fractures who underwent surgery and were followed for more than 12 months between June 2017 and June 2022 at a tertiary referral hospital. Biomarkers were calculated from peripheral venous blood collected on admission. The Centers for Disease Control and Prevention (CDC) definition of SSI was applied, with SSI identified through medical and pathogen culture records during hospitalization and routine postoperative telephone follow-ups. Multivariable logistic regression identified independent risk factors for SSI and developed predictive nomograms. Model stability was validated using an external set of patients treated from July 2022 to June 2023.
resultsA total of 1430 patients were included in model development, with 41 cases (2.87%) of superficial SSI and 6 cases (0.42%) of deep SSI. Multivariable analysis identified traditional prognostic factors older age (OR = 1.08, 95% CI 1.04-1.12), ASA class III-IV (OR = 2.46, 95% CI 1.32-4.56), surgical delay ≥ 6 days (OR = 3.59, 95% CI 1.36-9.47), surgical duration > 180 min (OR = 2.72, 95% CI 1.17-6.35), and systemic inflammation biomarkers Platelet-to-lymphocyte ratio (PAR) ≥ 6.6 (OR = 2.25, 95% CI 1.17-4.33) and Systemic Immune-Inflammation Index (SII) ≥ 541.1 (OR = 2.24, 95% CI 1.14-4.40) as independent predictors of SSI. Model's stability was proved by internal validation, and external validation with 307 patients, and an online dynamic nomogram ( https://brooklyn99.shinyapps.io/DynNomapp/ ) was generated.
conclusionsThis study combined systemic inflammatory biomarkers and developed an online dynamic nomogram to predict SSI in elderly hip fracture patients, which could be used to guide early screening of patients with high risk of SSI and provide a reference tool for perioperative management.
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