This study confirms that GV was associated with excess mortality. Furthermore, administration of increasing doses of insulin was associated with increased GV. Increased carbohydrate intake was associated with an increased insulin requirement, as well as increased duration of mechanical ventilation and ICU length of stay. These findings provide important context for further prospective trials investigating the effect of carbohydrate provision in mechanically ventilated critically ill patients requiring artificial nutritional support.

Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995–1999.

Purpose The Acute Disease Quality Initiative (ADQI) Workgroup recently released a consensus definition of sepsis-associated acute kidney injury (SA-AKI), combining Sepsis-3 and Kidney Disease Improving Global Outcomes (KDIGO) AKI criteria. This study aims to describe the epidemiology of SA-AKI. Methods This is a retrospective cohort study carried out in 12 intensive care units (ICUs) from 2015 to 2021. We studied the incidence, patient characteristics, timing, trajectory, treatment, and associated outcomes of SA-AKI based on the ADQI definition. Results Out of 84,528 admissions, 13,451 met the SA-AKI criteria with its incidence peaking at 18% in 2021. SA-AKI patients were typically admitted from home via the emergency department (ED) with a median time to SA-AKI diagnosis of 1 day (interquartile range (IQR) 1–1) from ICU admission. At diagnosis, most SA-AKI patients (54%) had a stage 1 AKI, mostly due to the low urinary output (UO) criterion only (65%). Compared to diagnosis by creatinine alone, or by both UO and creatinine criteria, patients diagnosed by UO alone had lower renal replacement therapy (RRT) requirements (2.8% vs 18% vs 50%; p < 0.001), which was consistent across all stages of AKI. SA-AKI hospital mortality was 18% and SA-AKI was independently associated with increased mortality. In SA-AKI, diagnosis by low UO only, compared to creatinine alone or to both UO and creatinine criteria, carried an odds ratio of 0.34 (95% confidence interval (CI) 0.32–0.36) for mortality. Conclusion SA-AKI occurs in 1 in 6 ICU patients, is diagnosed on day 1 and carries significant morbidity and mortality risk with patients mostly admitted from home via the ED. However, most SA-AKI is stage 1 and mostly due to low UO, which carries much lower risk than diagnosis by other criteria. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-023-07138-0.

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Purpose The Acute Disease Quality Initiative (ADQI) Workgroup recently released a consensus definition of sepsis-associated acute kidney injury (SA-AKI), combining Sepsis-3 and Kidney Disease Improving Global Outcomes (KDIGO) AKI criteria. This study aims to described the epidemiology of SA-AKI. Methods Retrospective cohort study in 12 intensive care units (ICU) from 2015 to 2021. We studied the incidence, patient characteristics, timing, trajectory, treatment, and associated outcomes of the ADQI SA-AKI definition. Results Of 84,831 admissions, 15,549 met the SA-AKI criteria with its incidence peaking at > 20% in 2021. SA-AKI patients were typically admitted from home via the emergency department (ED) with median time to SA-AKI diagnosis of one day (IQR 1–1) from ICU admission. At diagnosis, most SA-AKI patients had a stage 1 (55%) AKI, mostly due to the low urinary output (UO) criterion only (67%). Compared to diagnosis by creatinine alone, or both UO and creatinine criteria, patients diagnosed by UO alone had lower RRT requirement (3.3% vs 19% vs 51%; p < 0.001), which was consistent across all stages of AKI. SA-AKI hospital mortality was 19% and SA-AKI was independently associated with increased mortality. However, diagnosis by low UO only carried an odds ratio of 0.37 (95% CI, 0.34–0.39) for mortality. Conclusion SA-AKI occurs in one in five ICU patients, is diagnosed on day one, and carries significant morbidity and mortality risk with patients mostly admitted from home via the ED. However, most SA-AKI is stage 1 and mostly due to low UO, which carries much lower risk than diagnosis by other criteria.