Dynamic Nomogram for Predicting Thrombocytopenia in Adults with Acute Pancreatitis

Thrombocytopenia increases the risk of hemorrhage in patients with acute pancreatitis (AP), leading to poor clinical outcomes. Currently, there is no reliable tool for the early assessment of thrombocytopenia in these patients. We aimed to develop a nomogram based on available clinical parameters and validate its efficacy in predicting thrombocytopenia.

This was a retrospective study. All the data were extracted from an electronic database from May 2018 to May 2019. Patients with a diagnosis of AP and staying in the intensive care unit for more than 3 days were retrospectively analyzed. A clinical signature was built based on reproducible features, using the least absolute shrinkage and selection operator method (LASSO), and logistic regression established the model (P < 0.05). Nomogram performance was determined by its discrimination, calibration, and clinical usefulness.

A total of 594 eligible patients were enrolled, of whom 399 were allocated to the training sets and the 195 in the test sets. The clinical features, including blood urea nitrogen (BUN), fibrinogen (FIB), and antithrombase III, were significantly associated with the incidence of thrombocytopenia after acute pancreatitis (p < 0.05) in training sets. The individualized nomogram showed good discrimination in the training sample (area under the receiver operating characteristic curve [AUC], 0.881) and in the validation sample (AUC, 0.883) with good calibration.

The proposed nomogram has good performance for predicting thrombocytopenia in patients with acute pancreatitis and may facilitate clinical decision-making.