Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr 26;25(1):610.
doi: 10.1186/s12879-025-11011-4.

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

Hui Lian #  1 , Guangjian Wang #  2 , Hongmin Zhang  1 , Xiaoting Wang  3 , Wei He  4
Affiliations

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

Hui Lian et al. BMC Infect Dis. .

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: MIMIC-IV; Prognosis; SHR; Sepsis; Stress hyperglycemia ratio; Stress response.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Authors’ information: Not applicable. Financial disclosure statement: There are no financial conflicts of interest to disclose.

Figures

Fig. 1
Fig. 1
Flow chart of the study process. Note: ICU: intensive care unit; MIMIC-IV: Medical Information Mart for Intensive Care IV; HbA1c: glycated hemoglobin
Fig. 2
Fig. 2
ROC curves for 28-day and 1-year mortality. Note: ROC: receiver operating characteristic, SHR: stress hyperglycemia ratio, AUC: areas under the curve
Fig. 3
Fig. 3
Kaplan–Meier survival curves for different SHRs and 28-day mortality, with cut-off values generated from the ROC curves in Fig. 2. Note: ROC: receiver operating characteristic, SHR: stress hyperglycemia ratio. All P < 0.001
Fig. 4
Fig. 4
Kaplan–Meier survival curves for different SHRs and 1-year mortality, with cut-off values generated from the ROC curves in Fig. 2. Note: ROC: receiver operating characteristic, SHR: stress hyperglycemia ratio. All P < 0.001
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, et al. The third international consensus definitions for Sepsis and septic shock (Sepsis-3). JAMA. 2016;315(8):801–10. - PMC - PubMed
    1. Arina P, Singer M. Pathophysiology of sepsis. Curr Opin Anaesthesiol. 2021;34(2):77–84. - PubMed
    1. Martin-Loeches I, Guia MC, Vallecoccia MS, Suarez D, Ibarz M, Irazabal M, Ferrer R, Artigas A. Risk factors for mortality in elderly and very elderly critically ill patients with sepsis: a prospective, observational, multicenter cohort study. Ann Intensive Care. 2019;9(1):26. - PMC - PubMed
    1. Pandolfi F, Brun-Buisson C, Guillemot D, Watier L. One-year hospital readmission for recurrent sepsis: associated risk factors and impact on 1-year mortality-a French nationwide study. Crit Care. 2022;26(1):371. - PMC - PubMed
    1. Marik PE, Bellomo R. Stress hyperglycemia: an essential survival response! Crit Care. 2013;17(2):305. - PMC - PubMed

LinkOut - more resources