Prospective Validation of a Prediction Model for the Diagnosis of Acute Pancreatitis

David X. Jin, MD, MPH¹; Ronilda Lacson, MD, PhD²; Mahsa Eskian, MD²; et al

Julia McNabb-Baltar, MD, MPH¹; Peter A. Banks, MD¹; Stephanie R. Kayden, MD, MPH³; Ali S. Raja, MD, DBA^2,4; Ramin Khorasani, MD, MPH²

Author Affiliations Article Information

JAMA Netw Open. 2024;7(6):e2419014. doi:10.1001/jamanetworkopen.2024.19014

Key Points

Question  Does a novel prediction model that uses 8 nonimaging parameters diagnose acute pancreatitis in patients presenting to the emergency department with elevated serum lipase levels?

Findings  In this diagnostic study validating a prediction model, the model demonstrated excellent accuracy. At a score of at least 6 points, prediction model accuracy and performance were optimized, serious alternative diagnoses were uncommon, and diagnostic yield of early imaging was low.

Meaning  This prediction model may accurately diagnose acute pancreatitis and obviate the need for confirmatory diagnostic imaging in many patients.

Abstract

Importance  While most patients with acute pancreatitis (AP) fulfill diagnostic criteria with characteristic abdominal pain and serum lipase levels of at least 3 times the upper limit of normal (reference range) at presentation, early imaging is often used for confirmation. A prior prediction model and corresponding point-based score were developed using nonimaging parameters to diagnose AP in patients presenting to the emergency department (ED).

Objective  To evaluate the performance of the prediction model to diagnose AP in a prospective patient cohort.

Design, Setting, and Participants  This prospective diagnostic study included consecutive adult patients presenting to the ED between January 1, 2020, and March 9, 2021, at 2 large academic medical centers in the northeastern US with serum lipase levels at least 3 times the upper limit of normal. Patients transferred from outside institutions or with malignant disease and established intra-abdominal metastases, acute trauma, or altered mentation were excluded. Data were analyzed from October 15 to October 23, 2023.

Exposures  Participants were assigned scores for initial serum lipase level, number of prior AP episodes, prior cholelithiasis, abdominal surgery within 2 months, presence of epigastric pain, pain of worsening severity, duration from pain onset to presentation, and pain level at ED presentation.

Main Outcome and Measures  A final diagnosis of AP, established by expert review of hospitalization records.

Results  Prospective scores in 349 participants (mean [SD] age, 53.0 [18.8] years; 184 women [52.7%]; 66 Black [18.9%]; 199 White [57.0%]) demonstrated an area under the receiver operating characteristics curve of 0.91. A score of at least 6 points achieved highest accuracy (F score, 82.0), corresponding to a sensitivity of 81.5%, specificity of 85.9%, positive predictive value of 82.6%, and negative predictive value of 85.1% for AP diagnosis. Early computed tomography or magnetic resonance imaging was performed more often in participants predicted to have AP (116 of 155 [74.8%] with a score ≥6 vs 111 of 194 [57.2%] with a score <6; P < .001). Early imaging revealed an alternative diagnosis in 8 of 116 participants (6.9%) with scores of at least 6 points, 1 of 93 (1.1%) with scores of at least 7 points, and 1 of 73 (1.4%) with scores of at least 8 points.

Conclusions and Relevance  In this multicenter diagnostic study, the prediction model demonstrated excellent AP diagnostic accuracy. Its application may be used to avoid unnecessary confirmatory imaging.

（附原文预测模型的8个指标评分法）