The Journal of emergency medicine · 2025
Prediction of In-Hospital Mortality in Patients with Acute Pancreatitis: Role of Inflammation-Related Biomarkers.
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Saribas Mehmet Seyfettin, Erinmez Muhammet Ali, Ozen Alptug, Akca Ibrahim
Аннотация
BACKGROUND: In patients diagnosed with acute pancreatitis (AP), early determination of severity and tailoring treatment for high-risk patients can lead to a reduction in morbidity and mortality. In the emergency department (ED), markers or indices that are quickly accessible, easily calculable, practical, and inexpensive are needed.
OBJECTIVE: We aimed to investigate the performance of inflammatory biomarkers in predicting the in-hospital mortality in patients with AP.
METHODS: Patients admitted to the ED between 2017 and 2024 and diagnosed with AP were retrospectively analyzed. Patients aged ≥18 years who had undergone abdominal computed tomography were included in the study. The diagnosis of AP was evaluated according to the revised Atlanta criteria.
RESULTS: Multivariate logistic regression analysis revealed that the neutrophil-to-lymphocyte ratio (NLR, adjusted odds ratio [OR]: 1.08), systemic immune-inflammation index (SII, adjusted OR: 1), leuko-glycemic index (LGI, adjusted OR: 2.2), and neutrophil-glycemic index (NGI, adjusted OR: 2.411) were independent variables in predicting in-hospital mortality in patients with AP. According to receiver operating characteristic curve analysis, SII demonstrated the best performance in predicting in-hospital mortality (area under the curve (AUC): 0.857), followed by NGI (AUC: 0.850) and NLR (AUC: 0.857). LGI also showed good performance in predicting in-hospital mortality in patients with AP (AUC: 0.829).
CONCLUSION: The present study demonstrates that NLR, SII, LGI, and NGI can be used as independent factors to predict in-hospital mortality in patients with AP. SII and NGI showed the best performance in predicting in-hospital mortality. LGI had the highest sensitivity and the lowest negative likelihood ratio.
OBJECTIVE: We aimed to investigate the performance of inflammatory biomarkers in predicting the in-hospital mortality in patients with AP.
METHODS: Patients admitted to the ED between 2017 and 2024 and diagnosed with AP were retrospectively analyzed. Patients aged ≥18 years who had undergone abdominal computed tomography were included in the study. The diagnosis of AP was evaluated according to the revised Atlanta criteria.
RESULTS: Multivariate logistic regression analysis revealed that the neutrophil-to-lymphocyte ratio (NLR, adjusted odds ratio [OR]: 1.08), systemic immune-inflammation index (SII, adjusted OR: 1), leuko-glycemic index (LGI, adjusted OR: 2.2), and neutrophil-glycemic index (NGI, adjusted OR: 2.411) were independent variables in predicting in-hospital mortality in patients with AP. According to receiver operating characteristic curve analysis, SII demonstrated the best performance in predicting in-hospital mortality (area under the curve (AUC): 0.857), followed by NGI (AUC: 0.850) and NLR (AUC: 0.857). LGI also showed good performance in predicting in-hospital mortality in patients with AP (AUC: 0.829).
CONCLUSION: The present study demonstrates that NLR, SII, LGI, and NGI can be used as independent factors to predict in-hospital mortality in patients with AP. SII and NGI showed the best performance in predicting in-hospital mortality. LGI had the highest sensitivity and the lowest negative likelihood ratio.