Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants.

ABSTRACT:

Background

Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census.

Methods

A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were us

SUBMITTER: Mueller M 

PROVIDER: S-EPMC1413521 | biostudies-literature | 2006 Mar

REPOSITORIES: biostudies-literature