Composite inflammatory, immune, and nutritional indices for predicting surgical site infection following spine...

Surgical site infection (SSI) is an important complication after spine surgery, with a reported incidence of approximately 1%-4% and a substantial associated healthcare burden. Early identification of high-risk patients remains difficult. Composite indices derived from routine laboratory tests that integrate inflammatory, immune, and nutritional parameters may assist perioperative SSI risk stratification.

This systematic review with narrative synthesis was conducted in accordance with the PRISMA 2020 statement and was registered in PROSPERO (registration number blinded for peer review). PubMed, Web of Science, and Embase were searched from database inception to May 28, 2026. Non-randomized clinical studies evaluating composite inflammatory, immune, or nutritional indices for predicting SSI after spine surgery were eligible. Two reviewers independently performed study selection, data extraction, and quality assessment. Observational studies were appraised using the Newcastle-Ottawa Scale (NOS), prediction-model studies using PROBAST, and studies reporting diagnostic or discriminative performance using QUADAS-2 as a supplementary tool. Because the included studies differed in surgical procedures, index definitions, sampling time points, thresholds, and statistical methods, the evidence was synthesized narratively.

Twenty-one retrospective studies comprising 13,853 patients and 763 SSI or SSI-related infectious outcome cases were included. The evaluated indices comprised NLR, PLR, PNI, NRI, AGR, CAR, CLR, SIRI, SII, AISI, CALLY, CONUT, mGPS, and MNA-SF, among others. NLR was the most frequently studied inflammatory index. Postoperative NLR, particularly when measured between postoperative days 3 and 7, showed potential for early SSI detection. Associations with SSI were relatively consistent for CAR and mGPS, whereas findings for PNI and other nutritional indices were more variable. Five studies developed or evaluated prediction models or composite scoring systems. These models often reported higher discrimination than individual markers, but most were derived from retrospective cohorts, with limited external validation and heterogeneous calibration or clinical-utility assessment.

Composite inflammatory, immune, and nutritional indices may assist SSI risk stratification after spine surgery. Postoperative NLR, CAR, mGPS, PNI, and SIRI appear to be clinically relevant adjunctive markers, but current evidence remains limited by retrospective designs, heterogeneous SSI definitions, variable sampling times, and insufficient external validation. Multivariable and machine-learning models have reported high discrimination in some cohorts, but their clinical use remains uncertain without robust calibration, independent validation, and clinical-utility assessment. At present, these measures should support, rather than replace, comprehensive clinical assessment.