Exploring treatment effects and fluid resuscitation strategies in septic shock: a deep learning-based causal inference approach

Exploring treatment effects and fluid resuscitation strategies in septic shock: a deep learning-based causal inference approach

Abstract Septic shock exhibits diverse etiologies and patient characteristics, necessitating tailored fluid management. We aimed to compare resuscitation strategies using normal saline, Ringer’s lactate, and albumin, and to determine which patient factors are associated with improved outcomes. We an...

Full description

Saved in:
Bibliographic Details
Main Authors: Yoonjin Kang, Shin Young Ahn, Min Woo Kang
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Septic shock
Normal saline
Ringer’s lactate
Albumin
Deep learning
Causal inference
Online Access:https://doi.org/10.1038/s41598-025-03141-1
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-03141-1

Similar Items