Stress Hyperglycaemia Ratio

How it works

Benefits

Risks & contraindications

Comparisons

Evidence quality

Highlighted claims

• SHR measures acute glucose elevation relative to each patient's chronic glycaemic baseline, making it more precise than raw admission glucose alone. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling
• Higher SHR was consistently and significantly associated with increased mortality across all time horizons studied. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling
• RCS analysis confirmed a strictly linear dose-response relationship between SHR and 360-day mortality, with risk increasing monotonically and not plateauing. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling
• Adding SHR to a comprehensive basic clinical model produced a significant and measurable improvement in predictive accuracy for 360-day mortality. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling
• LASSO regression selected SHR as one of 11 independent predictors for 360-day mortality, confirming its independent predictive value. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling
• SHAP analysis confirmed higher SHR was among the most influential features driving increased predicted mortality risk across all three time horizons in the XGBoost model. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling
• SHR is the superior and more actionable index for risk stratification in critically ill patients, and should be prioritised over HGI for acute risk stratification. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling
• The linear SHR-mortality relationship found here contrasts with a prior study reporting a U-shaped relationship, likely due to more comprehensive covariate adjustment in the present analysis. — Predictive value of stress hyperglycaemia ratio and haemoglobin glycation index for mortality risks in critically ill patients: a comparative retrospective analysis of the MIMIC-IV database using machine learning-based predictive modelling