ArticleInternational wound journal2023
A nomogram for accurately predicting the surgical site infection following transforaminal lumbar interbody fusion in type 2 diabetes patients, based on glycemic variability.
Article in International wound journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 17 citations in OpenAlex.
- Modified subcutaneous lumbar spine index (MSLSI): a new predictor for early surgical site infection after transforaminal lumbar interbody fusion.Annals of medicine · 2025Article
- Development of a risk scoring system for surgical site infection after lumbar surgery using Dixon MRI and clinical parameters.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025Article
- Nomogram Development and Feature Selection Strategy Comparison for Predicting Surgical Site Infection After Lower Extremity Fracture Surgery.Medicina (Kaunas, Lithuania) · 2025Article
- Development and validation of a predictive nomogram for surgical site infection among general surgery patients in Amhara region Ethiopia.Scientific reports · 2025Article
- Assessing the predictive value of time-in-range level for the risk of postoperative infection in patients with type 2 diabetes: a cohort study.Frontiers in endocrinology · 2025Article
- A nomogram for accurately predicting the surgical site infection following transforaminal lumbar interbody fusion in type 2 diabetes patients, based on glycemic variability.International wound journal · 2023Article
- Development and validation of a nomogram to predict the risk of surgical site infection within 1 month after transforaminal lumbar interbody fusion.Journal of orthopaedic surgery and research · 2023Article
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8 authors at 2 institutions in 1 country.
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Abstract
Surgical site infection (SSI) is a common and serious complication of transforaminal lumbar interbody fusion (TLIF), and the occurrence of SSI usually leads to prolonged hospitalisation, increased medical costs, poor prognosis, and even death. The objectives of this study were to compare the incidence of SSI in patients with type 2 diabetes, investigate the correlation between perioperative glycemic variability and postoperative SSI, and develop a nomogram model to predict the risk of SSI. This study retrospectively analysed 339 patients with type 2 diabetes who underwent TLIF in the spinal surgery department of the Affiliated Zhongda Hospital of Southeast University from January 2018 to September 2021. The medical records of all patients were collected, and postoperative infection cases were determined according to the diagnostic criteria of surgical site infection. The risk factors for postoperative SSI were analysed by univariate and multivariate logistic regression. And Nomogram prediction model was established and validated. The nomogram incorporated seven independent predictors. Preoperative FPG-CV was the most important independent risk predictor of SSI, followed by preoperative MFBG, duration of drain placement, postoperative FPG-CV, preoperative blood glucose control scheme, duration of diabetes >5 years, and the number of fused vertebrae ≥2. The nomogram showed good diagnostic accuracy for the SS of both the training cohort and the validation cohort (AUC = 0.915 and AUC = 0.890). The calibration curves for the two cohorts both showed optimal agreement between nomogram prediction and actual observation. In conclusion, preoperative and postoperative glycemic variability is closely related to the occurrence of SSI. We developed and validated a nomogram to accurately predict the risk of SSI after TLIF surgery. It's helpful for spinal surgeons to formulate reasonable treatment plans and prevention strategies for type 2 diabetes patients.
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