PeerJ · 2026
Prognostic model of patients with acute pancreatitis based on prothrombin time-international normalized ratio to albumin ratio: a single-center retrospective study.
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Zhou Jun, Jin Yuexinzi, Zhang Litao, Cai Zhenzhen, Liu Jingping
Аннотация
BACKGROUND: The prothrombin time-international normalized ratio to albumin ratio (PTAR) serves as a prognostic biomarker in several diseases, yet its role in predicting the mortality of acute pancreatitis (AP) remains unclear. This study aimed to investigate the association between PTAR and the 30-day outcomes in AP patients.
METHODS: We retrospectively analysed data from 965 patients hospitalized with AP between January 2017 and December 2019, collecting baseline clinical characteristics and laboratory data. Using logistic regression analysis and the least absolute shrinkage and selection operator regression, we developed a prognostic nomogram based on PTAR. The nomogram's predictive performance and calibration were assessed via receiver operating characteristic curve analysis and calibration plots, respectively. Bootstrap technology was used for internal validation.
RESULTS: Among the 965 patients, 43 (4.5%) died within 30 days. Multivariate analysis identified seven risk factors independently associated with 30-day mortality of patients with AP: Age, neutrophil percentage, platelets, fibrinogen, aspartate aminotransferase, blood urea nitrogen, and PTAR. The model incorporating these factors, including PTAR, demonstrated excellent discrimination and calibration ability in assessing 30-day mortality (area under the curve (AUC) = 0.914, 95% confidence interval (CI) [0.877-0.951]). Kaplan-Meier survival curve analysis showed that AP patients with a nomogram value >0.082 had a significantly higher risk of 30-day mortality (P < 0.001).
CONCLUSIONS: PTAR holds clinical value in evaluating the 30-day prognosis of AP patients. The PTAR-based model could be useful independently or as a complement to conventional measures to support clinical decision-making.
METHODS: We retrospectively analysed data from 965 patients hospitalized with AP between January 2017 and December 2019, collecting baseline clinical characteristics and laboratory data. Using logistic regression analysis and the least absolute shrinkage and selection operator regression, we developed a prognostic nomogram based on PTAR. The nomogram's predictive performance and calibration were assessed via receiver operating characteristic curve analysis and calibration plots, respectively. Bootstrap technology was used for internal validation.
RESULTS: Among the 965 patients, 43 (4.5%) died within 30 days. Multivariate analysis identified seven risk factors independently associated with 30-day mortality of patients with AP: Age, neutrophil percentage, platelets, fibrinogen, aspartate aminotransferase, blood urea nitrogen, and PTAR. The model incorporating these factors, including PTAR, demonstrated excellent discrimination and calibration ability in assessing 30-day mortality (area under the curve (AUC) = 0.914, 95% confidence interval (CI) [0.877-0.951]). Kaplan-Meier survival curve analysis showed that AP patients with a nomogram value >0.082 had a significantly higher risk of 30-day mortality (P < 0.001).
CONCLUSIONS: PTAR holds clinical value in evaluating the 30-day prognosis of AP patients. The PTAR-based model could be useful independently or as a complement to conventional measures to support clinical decision-making.