Diagnostic value of CAR, HALP, and SII for predicting complicated appendicitis: a reassessment of inflammatory indices

Differentiating complicated from uncomplicated appendicitis remains a clinical challenge despite major advances in diagnostic imaging and evaluation. Inflammatory biomarkers derived from routine blood tests offer a practical and cost-effective tool for early risk stratification. This study aimed to reassess the diagnostic performance of the C-reactive protein-to-albumin ratio (CAR), hemoglobin–albumin–lymphocyte–platelet (HALP) score, and systemic immune-inflammation index (SII) in predicting complicated appendicitis. A retrospective analysis was performed on 1,767 adult patients who underwent appendectomy. Patients were categorized as having complicated or uncomplicated appendicitis based on operative and histopathologic findings. Inflammatory indices were calculated, and diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. Independent predictors were identified through multivariate logistic regression. CAR demonstrated the highest diagnostic performance among the evaluated indices, with an AUC of 0.713, significantly outperforming HALP and SII. Using a cutoff greater than 21.55, CAR achieved a specificity of 94.4% and was strongly associated with complicated appendicitis (odds ratio, 12.58). Multivariate analysis confirmed CAR and patient age as independent predictors. CAR is a reliable and clinically useful diagnostic biomarker compared to other evaluated inflammatory indices for predicting complicated appendicitis. However, its relatively low sensitivity suggests limited utility as a standalone screening tool, and CAR should therefore be interpreted alongside clinical and imaging findings in routine practice.

Publication Details

Journal
BMC Surgery
Published
2026-03-24
DOI
https://doi.org/10.1186/s12893-026-03687-5
Primary Topic
Appendicitis Diagnosis and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Diagnostic value of CAR, HALP, and SII for predicting complicated appendicitis: a reassessment of inflammatory indices

BMC Surgery
Appendicitis Diagnosis and Management
article

Diagnostic value of CAR, HALP, and SII for predicting complicated appendicitis: a reassessment of inflammatory indices

article en

Abstract

Differentiating complicated from uncomplicated appendicitis remains a clinical challenge despite major advances in diagnostic imaging and evaluation. Inflammatory biomarkers derived from routine blood tests offer a practical and cost-effective tool for early risk stratification. This study aimed to reassess the diagnostic performance of the C-reactive protein-to-albumin ratio (CAR), hemoglobin–albumin–lymphocyte–platelet (HALP) score, and systemic immune-inflammation index (SII) in predicting complicated appendicitis. A retrospective analysis was performed on 1,767 adult patients who underwent appendectomy. Patients were categorized as having complicated or uncomplicated appendicitis based on operative and histopathologic findings. Inflammatory indices were calculated, and diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. Independent predictors were identified through multivariate logistic regression. CAR demonstrated the highest diagnostic performance among the evaluated indices, with an AUC of 0.713, significantly outperforming HALP and SII. Using a cutoff greater than 21.55, CAR achieved a specificity of 94.4% and was strongly associated with complicated appendicitis (odds ratio, 12.58). Multivariate analysis confirmed CAR and patient age as independent predictors. CAR is a reliable and clinically useful diagnostic biomarker compared to other evaluated inflammatory indices for predicting complicated appendicitis. However, its relatively low sensitivity suggests limited utility as a standalone screening tool, and CAR should therefore be interpreted alongside clinical and imaging findings in routine practice.

BMC Surgery
Openalex Percentile: Top 11%
Appendicitis Diagnosis and Management
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