Association between the stress hyperglycemia ratio and 28-day all-cause mortality in critically ill patients with sepsis: a retrospective cohort study and predictive model establishment based on machine learning
Main finding · 28-day all-cause mortalityResult — go to the resultHazard ratio > 1Authors' conclusion
The SHR exhibited a U-shaped relationship with 28-day all-cause mortality and in-hospital mortality in critically ill patients with sepsis. A high SHR is significantly correlated with an increased risk of adverse events, thus indicating that is a potential predictor of adverse outcomes in patients with sepsis.
Study context
- Population
- Critically ill patients with sepsis, MIMIC-IV (2.2) database; divided into four groups by stress hyperglycemia ratio (SHR) quartiles
- Participants
- 2,312 patients
- Exposure
- Higher vs lower stress hyperglycemia ratio quartiles
- Outcome
- 28-day all-cause mortality
- Follow-up
- 28 days
Methodological detailsMIMIC-IV (2.2) database, machine learning prediction model
- MIMIC-IV (2.2) database
- Machine learning prediction model
Main finding
As reported in the abstract
Hazard ratio
> 1
P < 0.05
Observational data: associations, not effects.
Secondary outcomes
Prediction model performance
- Best-performing model (rsf algorithm) AUC
- 0.8322
- SHR had a higher Z score in Boruta feature selection
Original publication
Association between the stress hyperglycemia ratio and 28-day all-cause mortality in critically ill patients with sepsis: a retrospective cohort study and predictive model establishment based on machine learning. Cardiovasc Diabetol. Published 9 May 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →