ArticleFrontiers in surgery2025
Risk factors and predictive model for early surgical site infection following single-level PLIF in diabetic patients.
Article in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Explainable Machine Learning Predictive Models for Surgical Site Infections: Scoping Review.Journal of medical Internet research · 2026Article
- Diabetes mellitus is an independent risk factor for surgical site infection after orthopedic Class I incision surgery: a retrospective cohort study.Frontiers in surgery · 2026Article
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Authors and funding
7 authors.
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Abstract
Objective: This study aims to investigate the predictive value of postoperative serum biomarkers for early surgical site infection (SSI) following single-level posterior lumbar interbody fusion (PLIF) in diabetic patients, and to construct an infection risk prediction model based on key indicators. The goal is to provide a theoretical basis and tool support for precise clinical prevention and control. Methods: A retrospective analysis was conducted on 1,680 diabetic patients who underwent single-level PLIF in our Hospital, from January 2011 to December 2024. Among these, 165 patients developed early SSI. Univariate analysis was performed using-Whitney Results: Univariate analysis revealed that patients in the infection group had significantly higher postoperative day 3 fasting blood glucose (FPG pod3: 17.18 vs. 14.13 mmol/L), C-reactive protein (CRP pod3: 281.70 vs. 111.17 mg/L), white blood cell count (WBC pod3: 41.28 vs. 16.90 × 10 Conclusion: Postoperative day 3 serum inflammatory markers (e.g., CRP, WBC) have high predictive value in identifying early SSI in diabetic patients undergoing single-level PLIF. The prediction model constructed based on these markers performs excellently in terms of accuracy, stability, and clinical utility, making it an effective tool for early identification of high-risk infection patients and providing scientific evidence for individualized postoperative management strategies and interventions.
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