Kong Niwen, Chang Patrick, Shulman Ira A, Haq Ubayd, Amini Maziar, Nguyen Denis, Khan Farhaad, Narala Rachan, Sharma Nisha, Wang Daniel, Thompson Tiana, Sadik Jonathan, Breze Cameron, Whitcomb David C, Buxbaum James L
Division of Gastroenterology, Department of Medicine, University of Southern California, Los Angeles, California, USA.
Department of Pathology, University of Southern California, Los Angeles, California, USA.
Clin Transl Gastroenterol. 2025 Apr 1;16(4):e00825. doi: 10.14309/ctg.0000000000000825.
Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool using mathematical algorithms to predict severity and manage fluid resuscitation needs based on the physiologic parameters of individual patients. Our aim was to assess whether adherence to ADAPT fluid recommendations vs standard management impacted clinical outcomes in a large prospective cohort.
We analyzed patients consecutively admitted to the Los Angeles General Medical Center between June 2015 and November 2022 whose course was richly characterized by capturing more than 100 clinical variables. We inputted these data into the ADAPT system to generate resuscitation fluid recommendations and compared with the actual fluid resuscitation within the first 24 hours from presentation. The primary outcome was the difference in organ failure in those who were over-resuscitated (>500 mL) vs adequately resuscitated (within 500 mL) with respect to the ADAPT fluid recommendation. Additional outcomes included intensive care unit admission, systemic inflammatory response syndrome (SIRS) at 48 hours, local complications, and pancreatitis severity.
Among the 1,083 patients evaluated using ADAPT, 700 were over-resuscitated, 196 were adequately resuscitated, and 187 were under-resuscitated. Adjusting for pancreatitis etiology, gender, and SIRS at admission, over-resuscitation was associated with increased respiratory failure (odd ratio [OR] 2.73, 95% confidence interval [CI] 1.06-7.03) as well as intensive care unit admission (OR 2.40, 1.41-4.11), more than 48 hours of hospital length of stay (OR 1.87, 95% CI 1.19-2.94), SIRS at 48 hours (OR 1.73, 95% CI 1.08-2.77), and local pancreatitis complications (OR 2.93, 95% CI 1.23-6.96).
Adherence to ADAPT fluid recommendations reduces respiratory failure and other adverse outcomes compared with conventional fluid resuscitation strategies for acute pancreatitis. This validation study demonstrates the potential role of dynamic machine learning tools in acute pancreatitis management.
Ariel动态急性胰腺炎追踪器（ADAPT）是一种人工智能工具，它使用数学算法，根据个体患者的生理参数来预测严重程度并管理液体复苏需求。我们的目的是评估在一个大型前瞻性队列中，遵循ADAPT液体推荐与标准管理相比，是否会影响临床结果。
我们分析了2015年6月至2022年11月期间连续入住洛杉矶综合医疗中心的患者，这些患者的病程通过收集100多个临床变量得到了充分的描述。我们将这些数据输入ADAPT系统以生成复苏液体推荐，并与就诊后前24小时内的实际液体复苏情况进行比较。主要结局是根据ADAPT液体推荐，过度复苏（>500 mL）与充分复苏（在500 mL以内）的患者在器官衰竭方面的差异。其他结局包括重症监护病房入住、48小时时的全身炎症反应综合征（SIRS）、局部并发症和胰腺炎严重程度。
在使用ADAPT评估的1083例患者中，700例过度复苏，196例充分复苏，187例复苏不足。在调整胰腺炎病因、性别和入院时的SIRS后，过度复苏与呼吸衰竭增加（比值比[OR] 2.73，95%置信区间[CI] 1.06 - 7.03）、重症监护病房入住（OR 2.40，1.41 - 4.11）、住院时间超过48小时（OR 1.87，95% CI 1.19 - 2.94）、48小时时的SIRS（OR 1.73，95% CI 1.08 - 2.77）以及局部胰腺炎并发症（OR 2.93，95% CI 1.23 - 6.96）相关。
与急性胰腺炎的传统液体复苏策略相比，遵循ADAPT液体推荐可减少呼吸衰竭和其他不良结局。这项验证研究证明了动态机器学习工具在急性胰腺炎管理中的潜在作用。
