Development and external validation of temporal fusion transformer models for continuous intraoperative blood pressure forecasting.

ABSTRACT:

Background

During surgery, intraoperative hypotension is associated with postoperative morbidity and should therefore be avoided. Predicting the occurrence of hypotension in advance may allow timely interventions to prevent hypotension. Previous prediction models mostly use high-resolution waveform data, which is often not available.

Methods

We utilised a novel temporal fusion transformer (TFT) algorithm to predict intraoperative blood pressure trajectories 7 min in advance. We trained the model with low-resolution data (sampled every 15 s) from 73,009 patients who were undergoing general anaesthesia for non-cardiothoracic surgery between January 1, 2017, and December 30, 2020, at the General Hospital of Vienna, Austria. The data set contained information on patient demograp

SUBMITTER: Kapral L 

PROVIDER: S-EPMC11402414 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature