Assessing Serious Spinal Pathology Using Bayesian Network Decision Support: Development and Validation Study.

ABSTRACT:

Background

Identifying and managing serious spinal pathology (SSP) such as cauda equina syndrome or spinal infection in patients presenting with low back pain is challenging. Traditional red flag questioning is increasingly criticized, and previous studies show that many clinicians lack confidence in managing patients presenting with red flags. Improving decision-making and reducing the variability of care for these patients is a key priority for clinicians and researchers.

Objective

We aimed to improve SSP identification by constructing and validating a decision support tool using a Bayesian network (BN), which is an artificial intelligence technique that combines current evidence and expert knowledge.

Methods

A modified RAND appropriateness procedure was undertaken

SUBMITTER: Hill A 

PROVIDER: S-EPMC10582804 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature