Background & Aims: The aims of this study were to: (1) assess the performance of the Pancreatitis Activity Scoring System (PASS) in a large intercontinental cohort of patients with acute pancreatitis (AP); and (2) investigate whether a modified PASS (mPASS) yields a similar predictive accuracy and produces distinct early trajectories between severity subgroups.
Methods: Data was prospectively collected through the Acute Pancreatitis Patient Registry to Examine Novel Therapies In Clinical Experience (APPRENTICE) consortium (2015-2018) involving 22 centers from 4 continents. AP severity was categorized per the revised Atlanta classification. PASS trajectories were compared between the three severity groups using the generalized estimating equations model. Four mPASS models were generated by modifying the morphine equivalent dose (MED), and their trajectories were compared.
Results: A total of 1393 subjects were enrolled (median age, 49 years; 51% males). The study cohort included 950 mild (68.2%), 315 (22.6%) moderately severe, and 128 (9.2%) severe AP. Mild cases had the lowest PASS at each study time point (all P < .001). A subset of patients with outlier admission PASS values was identified. In the outlier group, 70% of the PASS variation was attributed to the MED, and 66% of these patients were from the United States centers. Among the 4 modified models, the mPASS-1 (excluding MED from PASS) demonstrated high performance in predicting severe AP with an area under the receiver operating characteristic curve of 0.88 (vs area under the receiver operating characteristic of 0.83 in conventional PASS) and produced distinct trajectories with distinct slopes between severity subgroups (all P < .001).
Conclusion: We propose a modified model by removing the MED component, which is easier to calculate, predicts accurately severe AP, and maintains significantly distinct early trajectories.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060638 | PMC |
http://dx.doi.org/10.1016/j.cgh.2021.09.014 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!