Optimize individualized energy delivery for septic patients using predictive deep learning models.

ABSTRACT:

Background and objectives

We aim to establish deep learning models to optimize the individualized energy delivery for septic patients.

Methods and study design

We conducted a study of adult septic patients in ICU, collecting 47 indicators for 14 days. We filtered out nutrition-related features and divided the data into datasets according to the three metabolic phases proposed by ESPEN: acute early, acute late, and rehabilitation. We then established optimal energy target models for each phase using deep learning and conducted external validation.

Results

A total of 179 patients in training dataset and 98 patients in external validation dataset were included in this study, and total data size was 3115 elements. The age, weight and BMI of the patients were 63.05 (95%CI

SUBMITTER: Wang L 

PROVIDER: S-EPMC11389806 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature