The American journal of gastroenterology · 2025
Clinical Outcomes in a Multicenter Cohort Involving 919 Patients With Hypertriglyceridemia-Associated Acute Pancreatitis.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Deng Hanzhang, Peng Kaixin, Zhang Liang, Lu Jiongdi, Mei Wentong, Shi Xiaolei, Peng Yunpeng, Xu Kedong, Li Haoxuan, Wang Zheng, Lu Guotao, Wang Gang, Lu Zipeng, Cao Feng, Wen Li, Chinese Hypertriglyceridemia-associated Pancreatitis Study Group (CHPSG)
Аннотация
INTRODUCTION: Hypertriglyceridemia-associated acute pancreatitis (HTG-AP) is one of the most common etiologies of acute pancreatitis (AP) worldwide. Compared with other etiologies, patients with HTG-AP may develop more severe AP, but previous studies yielded controversial conclusion due to the lack of adequate adjustment for the confounders. Therefore, the aim of this study was to examine the possibility and risk factors of developing severe AP in HTG-AP.
METHODS: Data from patients with an established diagnosis of AP were collected from January 2013 to December 2023 using a predesigned data collection form and were gathered from 5 tertiary cross-regional centers of China. HTG-AP was defined as serum triglyceride levels >500 mg/dL and excluded other etiologies. The possibility and risk factors of severe AP were assessed by multivariable logistic regressions after adjusting potential confounders. A prediction model was established and validated.
RESULTS: Between 2013 and 2023, we identified a total of 6,996 patients with AP, of whom 4,378 were included in the final analysis. Compared with other etiologies, patients with HTG-AP had a higher risk of developing severe AP (odds ratio: 1.897; 95% confidence interval: 1.380-2.608; P < 0.001) and organ failure. HTG-AP patients showed higher possibility for developing respiratory and circulation failure but renal failure compared with other etiologies. In HTG-AP patients, risk factors of severe AP included age, fasting blood glucose, white blood cell counts, and presence of pleural effusion. TG level was found not significantly associated with severity in HTG-AP patients. A prediction model incorporating these risk factors demonstrated an area under the curve (AUC) of 0.837 in the training and 0.883 in the testing set, with adequate calibration.
DISCUSSION: Using a multicenter cross-regional cohort, we demonstrated that HTG-AP had a higher risk of developing severe AP and organ failure. A risk prediction model for predicting severe AP was developed and effectively stratified patients.
METHODS: Data from patients with an established diagnosis of AP were collected from January 2013 to December 2023 using a predesigned data collection form and were gathered from 5 tertiary cross-regional centers of China. HTG-AP was defined as serum triglyceride levels >500 mg/dL and excluded other etiologies. The possibility and risk factors of severe AP were assessed by multivariable logistic regressions after adjusting potential confounders. A prediction model was established and validated.
RESULTS: Between 2013 and 2023, we identified a total of 6,996 patients with AP, of whom 4,378 were included in the final analysis. Compared with other etiologies, patients with HTG-AP had a higher risk of developing severe AP (odds ratio: 1.897; 95% confidence interval: 1.380-2.608; P < 0.001) and organ failure. HTG-AP patients showed higher possibility for developing respiratory and circulation failure but renal failure compared with other etiologies. In HTG-AP patients, risk factors of severe AP included age, fasting blood glucose, white blood cell counts, and presence of pleural effusion. TG level was found not significantly associated with severity in HTG-AP patients. A prediction model incorporating these risk factors demonstrated an area under the curve (AUC) of 0.837 in the training and 0.883 in the testing set, with adequate calibration.
DISCUSSION: Using a multicenter cross-regional cohort, we demonstrated that HTG-AP had a higher risk of developing severe AP and organ failure. A risk prediction model for predicting severe AP was developed and effectively stratified patients.