Machine learning approach to predict postoperative pain after spinal morphine administration during caesarean delivery.

ABSTRACT:

Background

A major barrier to optimal pain management is the difficulty in predicting and assessing patients at high risk for significant pain across multiple locations within the institution in a timely manner. This is compounded by the fragmented display of clinical information on enterprise clinical platform, which further hinders delay the reviews and hence the increased risk of untreated pain. We evaluated and compared the predictive performance of six modelling techniques in predicting significant pain, defined as the maximum pain score of 3 or more on movement at the 13th to 24th hour after spinal morphine administration during caesarean delivery.

Methods

We retrieved medical records from women who underwent caesarean delivery and received postoperative spinal morphin

SUBMITTER: Tan CW 

PROVIDER: S-EPMC11629299 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature