SHRs, biomarkers for dysregulated stress response, predict prognosis in sepsis patients: a retrospective cohort study from MIMIC-IV database

• Published in: BMC infectious diseases Vol. 25; no. 1; pp. 610 - 12
• Main Authors: Lian, Hui, Wang, Guangjian, Zhang, Hongmin, Wang, Xiaoting, He, Wei
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 26.04.2025; BioMed Central; BMC
• Subjects: Aged; Analysis; Biological markers; Biomarkers; Biomarkers - blood; Blood; Blood glucose; Blood Glucose - analysis; Blood levels; Care and treatment; Cerebrovascular disease; Cohort analysis; Complications and side effects; Databases, Factual; Diabetes mellitus; Diagnosis; Female; Glucose; Heart attacks; Heart failure; Heart rate; Humans; Hyperglycemia; Hyperglycemia - blood; Infections; Insulin; Intensive care; Intensive Care Units; Kaplan-Meier Estimate; Kidney diseases; Liver diseases; Male; Medical prognosis; Middle Aged; MIMIC-IV; Missing data; Mortality; Multivariate analysis; Patients; Prognosis; Regression analysis; Retrospective Studies; ROC Curve; Sensitivity analysis; Sepsis; Sepsis - blood; Sepsis - diagnosis; Sepsis - mortality; SHR; Software; Statistical analysis; Stress hyperglycemia ratio; Stress response; Stress, Physiological; Survival; China; United States > US; Massachusetts; Sepsis; Prognosis; SHR; Stress response; MIMIC-IV; Stress hyperglycemia ratio
• DOI: 10.1186/s12879-025-11011-4
• ISSN: 1471-2334

The dysregulated stress response is a key pathological mechanism underlying sepsis and is strongly associated with poor clinical outcomes. Stress hyperglycemia, a common manifestation of this response, may provide valuable prognostic information in sepsis patients. The stress hyperglycemia ratio (SHR) offers a more accurate reflection of the stress response and may be instrumental in assessing sepsis prognosis. This study aimed to investigate the relationship between SHRs and clinical outcomes in sepsis patients. Data were obtained from the Medical Information Mart for Intensive Care IV database. Demographic information, intensive care unit (ICU) parameters within the first 24 h, laboratory results, insulin administration, survival time, and outcomes were extracted for analysis. Four SHR metrics (SHRfirst, SHRmin, SHRmax, and SHRmean) were calculated based on blood glucose values during the first 24 h of ICU admission (first, minimum, maximum, and mean, respectively). The predictive performance of each SHR metric was compared using the area under the receiver operating characteristic (ROC) curve. Kaplan-Meier survival analysis was performed to assess survival rates across groups defined by ROC curve-generated cut-off values. Associations between SHR and 28-day as well as 1-year mortality were further examined using both univariate and multivariate Cox regression analyses. A total of 5,025 sepsis patients were included, of whom 656 died within 28 days of ICU admission. SHR was significantly higher in the non-survivor group. Among the SHR metrics, SHRmax demonstrated the highest predictive value for both 28-day and 1-year mortality. Higher SHR values were consistently associated with increased mortality (all P < 0.001). For SHRmax, each 1-unit increase was associated with a 77% increase in mortality in univariate analysis and a 71.6% increase in multivariate analysis. Sensitivity analyses indicated that the relationship between SHR and mortality was stronger in patients without diabetes. SHR serves as a robust marker of the dysregulated stress response in sepsis and holds significant prognostic value, particularly SHRmax, in predicting mortality. These findings underscore the potential clinical utility of SHR in guiding therapeutic strategies aimed at modulating the stress response and blood glucose levels in critically ill sepsis patients. Further research is warranted to explore SHR-targeted interventions in sepsis management.