C-reactive protein to lymphocyte ratio as a new biomarker in predicting surgical site infection after posterior lumbar interbody fusion and instrumentation - Wu, Xiaofei; Ma, Xun; Zhu, Jian; Chen, Chen (Frontiers in Surgery, 2022)
Purpose This study aimed to evaluate the potential of the preoperative C-reactive protein to lymphocyte count ratio (CLR) for prediction of surgical site infection (SSI) following posterior lumbar interbody fusion (PLIF) and instrumentation of lumbar degenerative diseases. Methods: In this retrospective study, we included patients who had a diagnosis with lumbar degenerative disease surgically treated by instrumented PLIF procedure from 2015 and 2021. Patients' data, including postoperative early SSI and other perioperative variables, were collected from their hospitalization electronic medical records. The receiver operator characteristic (ROC) curve was constructed to determine the optimal cut-off value for preoperative CLR and the ability to predict SSI was evaluated by the area under the curve (AUC). According to the cut-off value, patients were dichotomized with high- or low-CLR and between-group differences were compared using the univariate analyses. The independent effect of CLR on predicting SSI was investigated by multivariate logistics regression analysis. Results. There were 773 patients included, with 26 (3.4%) developing an early SSI after operation. The preoperative CLR was 11.1±26.1 (interquartile range, 0.4 to 7.5), and the optimal cut-off was 2.1, corresponding to a sensitivity of 0.856, specificity of 0.643 and AUC of 0.768 (95%CI, 0.737 to 0.797). CLR showed a significantly improved prediction ability than did lymphocyte count (P=0.021), and the similar ability in predicting an infection as did CRP (P=0.444). Patients with a high CLR had a significantly higher SSI incidence than did those with a low CLR (7.6% vs 0.8%, P<0.001). After adjustment for numerous confounding factors, CLR≥2.1 was associated with 11.16-fold increased risk of SSI, together with other significant variables, i.e., diabetes, preoperative waiting time and surgical duration. Conclusion High CLR exhibited improved ability for prediction of incident SSI and was associated with substantially increased risk of SSI following instrumented PLIF. After this finding is verified by better-design studies, CLR could be applied as a useful pool in surgical management.