Systemic Inflammatory Response Index as a Predictor of Postoperative Infectious Complications in Elderly Patients Undergoing Posterior Spinal Instrumentation

全身炎症反应指数作为老年患者后路脊柱内固定术后感染并发症的预测指标

阅读:1

Abstract

Objective: To assess the predictive value of systemic inflammatory markers for postoperative complications in older adults undergoing posterior spinal instrumentation for either lumbar spinal stenosis (LSS) or osteoporotic vertebral fractures (OVFs). This study design as a retrospective observational study. Methods: Fifty-four patients aged ≥ 55 years who underwent posterior spinal instrumentation between 2020 and 2023 were retrospectively analyzed. Patients were grouped into LSS (n = 27) and OVF (n = 27) cohorts. Preoperative, early postoperative, and 6-month follow-up systemic inflammatory marker levels, including the Systemic Inflammatory Response Index (SIRI), Systemic Immune-Inflammation Index (SII), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Monocyte-to-Lymphocyte Ratio (MLR), were recorded. The primary outcome was the occurrence of postoperative infectious complications. ROC curve analysis was conducted to evaluate the discriminatory power of each marker. Results: SIRI values were significantly higher in the OVF group than in the LSS group at all time points (p < 0.05). Postoperative complications occurred in 7.4% of patients, equally distributed between groups. ROC analysis showed that preoperative SIRI had the highest predictive value (AUC = 0.743), with a cutoff value of 2.69 yielding 100% sensitivity and 65.3% specificity. Other indices showed poor predictive accuracy (AUC < 0.70). Conclusions: Preoperative SIRI is a promising, easily obtainable biomarker for identifying older patients at higher risk of postoperative complications following posterior spinal instrumentation. Its implementation may improve preoperative risk stratification in spine surgery.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。