Demonstration and Performance Evaluation of Two Novel Algorithms for Removing Artifacts From Automated Intraoperative Temperature Data Sets: Multicenter, Observational, Retrospective Study.

ABSTRACT:

Background

The automated acquisition of intraoperative patient temperature data via temperature probes leads to the possibility of producing a number of artifacts related to probe positioning that may impact these probes' utility for observational research.

Objective

We sought to compare the performance of two de novo algorithms for filtering such artifacts.

Methods

In this observational retrospective study, the intraoperative temperature data of adults who received general anesthesia for noncardiac surgery were extracted from the Multicenter Perioperative Outcomes Group registry. Two algorithms were developed and then compared to the reference standard-anesthesiologists' manual artifact detection process. Algorithm 1 (a slope-based algorithm) was based on the linear

SUBMITTER: Bardia A 

PROVIDER: S-EPMC9591708 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature