Prediction of acute pancreatitis severity using NLR, procalcitonin, and CT severity score: A retrospective study

This study aims to evaluate the clinical value of the neutrophil-to-lymphocyte ratio (NLR), procalcitonin (PCT), and computed tomography (CT) severity score in predicting the severity of acute pancreatitis (AP). Additionally, we investigate their correlations with clinical, laboratory, and imaging parameters to provide guidance for the early diagnosis and treatment of AP. This retrospective study included 300 patients diagnosed with AP at our hospital between December 2021 and December 2024. According to the Atlanta Classification, patients were categorized into mild AP (MAP) (225 cases), moderately severe AP (MSAP) (60 cases), and severe AP (SAP) (15 cases) groups. Clinical data, laboratory test results (including NLR and PCT), imaging assessments (CT severity scores), and clinical outcomes were retrospectively analyzed to assess the predictive value of these parameters in determining AP severity. With increasing severity of AP, patient age, duration of abdominal pain, incidence of complications, and length of hospital stay significantly increased (P < .01). Laboratory findings indicated that patients with SAP exhibited significantly elevated white blood cell count, C-reactive protein, PCT, blood glucose, bilirubin, and liver function markers. Specifically, PCT levels in MAP, MSAP, and SAP patients were (0.14 ± 0.05), (0.25 ± 0.10), and (0.52 ± 0.16) ng/mL, respectively, while NLR values were (1.23 ± 0.31), (1.55 ± 0.43), and (2.18 ± 0.57) (P < .01). The CT severity scores for MAP, MSAP, and SAP patients were (3.2 ± 0.7), (5.6 ± 1.1), and (8.1 ± 1.3), respectively (P < .01). CT severity score, NLR, PCT levels, age, and a history of diabetes were identified as independent predictors of AP severity. Notably, the combination of CT severity score, NLR, and PCT demonstrated superior predictive performance for AP severity. NLR, PCT, and CT severity score are effective predictive markers for assessing AP severity. Their combined application provides a more accurate prognosis, facilitating early evaluation and aiding clinicians in optimizing early intervention and personalized treatment strategies.