Glycaemic penalty index as an independent predictor of healthcare‐associated infection in surgical inpatients: A nested cohort study from the <scp>STOIC</scp> ‐D surgery trial

AIMS: To evaluate the utility of the Glycemic Penalty Index (GPI), a validated tool for assessing risk of adversity associated with inpatient dysglycaemia in surgical intensive care patients, in predicting adverse clinical outcomes among surgical inpatients at a quaternary Australian hospital. METHODS: This nested cohort study analysed data from the control arm of the Specialist Treatment of Inpatients: Caring for Diabetes in Surgery (STOIC-D Surgery) randomised controlled trial. The GPI was calculated using blood glucose values to derive patient-day weighted mean GPI (PDWMGPI). Univariable and multivariable analyses assessed associations between GPI and the outcomes of healthcare-associated infection (HAI) and acute kidney injury. RESULTS: 691 surgical inpatients with diabetes receiving standard care were included. On multivariable analysis, increasing PDWMGPI was independently associated with healthcare-associated infection (odds ratio 1.02 per one-unit increase, 95% CI 1.01-1.04, p = 0.008). CONCLUSION: The association between PDWMGPI and HAI suggests that linearised summary glycaemic measures may support clinicians in identifying patients at increased risk of adverse inpatient outcomes related to glycaemic patterns when interpreted alongside clinical factors. The simplicity of GPI as a single score may assist risk stratification and prioritisation of specialist diabetes input in surgical inpatient settings.

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Journal
Diabetic Medicine
Published
2026-06-16
DOI
https://doi.org/10.1111/dme.70385
Primary Topic
Hyperglycemia and glycemic control in critically ill and hospitalized patients
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article
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article

Glycaemic penalty index as an independent predictor of healthcare‐associated infection in surgical inpatients: A nested cohort study from the STOIC ‐D surgery trial

Rahul Barmanray, Spiros Fourlanos, Mervyn Kyi, PETER G. COLMAN et al.
Diabetic Medicine
Hyperglycemia and glycemic control in critically ill and hospitalized patients
article

Glycaemic penalty index as an independent predictor of healthcare‐associated infection in surgical inpatients: A nested cohort study from the STOIC ‐D surgery trial

Rahul Barmanray, Spiros Fourlanos, Mervyn Kyi, PETER G. COLMAN, Emily Sun, Leon J. Worth, Minh V. Le, Gabrielle Blomson
article en

Abstract

AIMS: To evaluate the utility of the Glycemic Penalty Index (GPI), a validated tool for assessing risk of adversity associated with inpatient dysglycaemia in surgical intensive care patients, in predicting adverse clinical outcomes among surgical inpatients at a quaternary Australian hospital. METHODS: This nested cohort study analysed data from the control arm of the Specialist Treatment of Inpatients: Caring for Diabetes in Surgery (STOIC-D Surgery) randomised controlled trial. The GPI was calculated using blood glucose values to derive patient-day weighted mean GPI (PDWMGPI). Univariable and multivariable analyses assessed associations between GPI and the outcomes of healthcare-associated infection (HAI) and acute kidney injury. RESULTS: 691 surgical inpatients with diabetes receiving standard care were included. On multivariable analysis, increasing PDWMGPI was independently associated with healthcare-associated infection (odds ratio 1.02 per one-unit increase, 95% CI 1.01-1.04, p = 0.008). CONCLUSION: The association between PDWMGPI and HAI suggests that linearised summary glycaemic measures may support clinicians in identifying patients at increased risk of adverse inpatient outcomes related to glycaemic patterns when interpreted alongside clinical factors. The simplicity of GPI as a single score may assist risk stratification and prioritisation of specialist diabetes input in surgical inpatient settings.

Diabetic Medicine
The Royal Melbourne Hospital (AU), The University of Melbourne (AU), Peter MacCallum Cancer Centre (AU), Peter Doherty Institute (AU)
Openalex Percentile: Top 6%
Hyperglycemia and glycemic control in critically ill and hospitalized patients
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