Nomogram for Predicting Persistent Organ Failure With Acute Pancreatitis in Pregnancy

Frontiers in Endocrinology

关键词: gestation;    acute pancreatitis (AP);    hypertriglyceridemia (HTG);    persistent organ failure;    nomogram model;   

DOI  :  10.3389/fendo.2022.863037

来源: DOAJ

【 摘 要 】

BackgroundAcute pancreatitis in pregnancy (APIP) with persistent organ failure (POF) poses a high risk of death for mother and fetus. This study sought to create a nomogram model for early prediction of POF with APIP patients.MethodsWe conducted a cross-sectional study on APIP patients with organ failure (OF) between January 2012 and March 2021. 131 patients were collected. Their clinical courses and pregnancy outcomes were obtained. Risk factors for POF were identified by univariate and multivariate logistic regression analysis. Prediction models with POF were built and nomogram was plotted. The performance of the nomogram was evaluated by using a bootstrapped-concordance index and calibration plots.ResultsHypertriglyceridemia was the most common etiology in this group of APIP patients, which accounted for 50% of transient organ failure (TOF) and 72.3% of POF. All in-hospital maternal death was in the POF group (P<0.05), which also had a significantly higher perinatal mortality rate than the TOF group (P<0.05). Univariate and multivariate logistic regression analysis determined that lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were independent risk factors for predicting POF in APIP. A nomogram for POF was created by using the four indicators. The area under the curve was 0.875 (95%CI: 0.80–0.95). The nomogram had a bootstrapped-concordance index of 0.85 and was well-calibrated.ConclusionsHypertriglyceridemia was the leading cause of organ failure-related APIP. Lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were the independent risk factors of POF in APIP. Our nomogram model showed an effective prediction of POF with the four indicators in APIP patients.

【 授权许可】

Unknown