ArticleCureus2025
Diagnostic Accuracy of Neutrophil-Creatinine Index for Predicting Severe Acute Pancreatitis Using the Revised Atlanta Classification As Gold Standard.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionEarly prediction of severity is important to guide treatment and triage. Many scoring systems and biomarkers are available, but none are both simple and highly accurate at admission. The aim of our study was therefore to determine the diagnostic accuracy of the neutrophil-creatinine index (NCI) in diagnosing severe acute biliary pancreatitis, using the revised Atlanta classification (2012) as the gold standard.
methodsThis cross-sectional validation study was conducted in the department of surgery, Benazir Bhutto Hospital, Rawalpindi, over a period of six months. A total of 217 patients with acute pancreatitis (AP) were included by non-probability consecutive sampling. The diagnosis was based on clinical, biochemical, and imaging criteria. The severity of AP was classified according to the revised Atlanta classification (2012), which served as the gold standard. The NCI was calculated at admission as absolute neutrophil count (× 10³/µL) × serum creatinine (mg/dL). A cut-off value of ≥11.27 was considered positive for severe AP (SAP). Diagnostic accuracy was assessed using sensitivity, specificity, predictive values, and receiver operating characteristic (ROC) curve analysis.
resultsOf 217 patients, 21 (9.7%) developed SAP. At the cut-off of 11.27, the NCI showed sensitivity 95.2%, specificity 91.3%, positive predictive value (PPV) 54.1%, negative predictive value (NPV) 99.4%, and overall accuracy 91.7%. The ROC analysis demonstrated excellent discrimination, with an area under the curve (AUC) of 0.96 (95% confidence interval (CI) 0.92-1.00).
conclusionThe NCI is a simple and inexpensive parameter that can predict SAP with high accuracy at admission. It may serve as a practical adjunct to existing scores and biomarkers, especially in resource-limited settings.
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