Frontiers in Surgery (Oct 2022)

C-reactive protein to lymphocyte ratio as a new biomarker in predicting surgical site infection after posterior lumbar interbody fusion and instrumentation

  • Xiaofei Wu,
  • Xun Ma,
  • Jian Zhu,
  • Jian Zhu,
  • Chen Chen

DOI
https://doi.org/10.3389/fsurg.2022.910222
Journal volume & issue
Vol. 9

Abstract

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PurposeThis study aims to evaluate the potential of C-reactive protein to lymphocyte count ratio (CLR) for the prediction of surgical site infection (SSI) following posterior lumbar interbody fusion (PLIF) and the instrumentation of lumbar degenerative diseases.MethodsIn this retrospective study, we considered patients with a lumbar degenerative disease diagnosis surgically treated by the instrumented PLIF procedure from 2015 to 2021. Patient data, including postoperative early SSI and other perioperative variables, were collected from their respective hospitalization electronic medical records. The receiver operator characteristic curve was constructed to determine the optimal cut-off value for 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 univariate analysis. The independent impact of CLR on predicting SSI was investigated by multivariate logistics regression analysis.ResultsA total of 773 patients were included, with 26 (3.4%) developing an early SSI post-operation. The preoperative CLR was 11.1 ± 26.1 (interquartile range, 0.4–7.5), and the optimal cut-off was 2.1, corresponding to a sensitivity of 0.856, a specificity of 0.643, and an AUC of 0.768 (95% CI, 0.737–0.797). CLR demonstrated a significantly improved prediction ability than did lymphocyte count (P = 0.021) and a similar ability to predict an infection as C-response protein (P = 0.444). Patients with a high CLR had a significantly higher SSI incidence than 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 an 11.16-fold increased risk of SSI, along with other significant variables, i.e., diabetes, preoperative waiting time, and surgical duration.ConclusionA high CLR exhibited an improved ability to predict incident SSI and was associated with a substantially increased risk of SSI following instrumented PLIF. After better-design studies verified this finding, CLR could potentially be a beneficial tool in surgical management.

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