Improving postpartum hemorrhage risk prediction using longitudinal electronic medical records.

ABSTRACT:

Objective

Postpartum hemorrhage (PPH) remains a leading cause of preventable maternal mortality in the United States. We sought to develop a novel risk assessment tool and compare its accuracy to tools used in current practice.

Materials and methods

We used a PPH digital phenotype that we developed and validated previously to identify 6639 PPH deliveries from our delivery cohort (N = 70 948). Using a vast array of known and potential risk factors extracted from electronic medical records available prior to delivery, we trained a gradient boosting model in a subset of our cohort. In a held-out test sample, we compared performance of our model with 3 clinical risk-assessment tools and 1 previously published model.

Results

Our 24-feature model achieved an area under the

SUBMITTER: Zheutlin AB 

PROVIDER: S-EPMC8757294 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature