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Independent Association of Glucose Variability With Hospital Mortality in Adult Intensive Care Patients: Results From the Australia and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Binational Registry.

ABSTRACT: Wide variations in blood glucose excursions in critically ill patients may influence adverse outcomes such as hospital mortality. However, whether blood glucose variability is independently associated with mortality or merely captures the excess risk attributable to hyperglycemic and hypoglycemic episodes is not established. We investigated whether blood glucose variability independently predicted hospital mortality in nonhyperglycemic critical care patients. Design:Retrospective, registry data analyses of outcomes. Setting:Large, binational registry (Australia and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Adult Patient Database repository) of 176 ICUs across Australia and New Zealand. Patients:We used 10-year data on nonhyperglycemic patients registered in the Australia and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Adult Patient Database repository (n = 290,966). Interventions:None. Measurements and Main Results:Glucose variability was captured using glucose width defined as the difference between highest and lowest blood glucose concentration within first 24 hours of ICU admission. We used hierarchical, mixed effects logistic regression models that accounted for ICU variation and several fixed-effects covariates. Glucose width was specifically and independently associated with hospital mortality. The association of blood glucose variability with mortality remained significant (odds ratio for highest vs lowest quartile of glucose, 1.43; 95% CI, 1.32-1.55; p < 0.001) even after adjusting for the baseline risk of mortality, midpoint blood glucose level, occurrence of hypoglycemia and inter-ICU variation. Mixed effects modeling showed that there was a statistically significant variation in this association across ICUs. Conclusions:Our study demonstrates that glucose variability is independently associated with hospital mortality in critically ill adult patients. Inclusion of correction for glucose variability in glycemic control protocols needs to be investigated in future studies.

SUBMITTER: Kulkarni H

PROVIDER: S-EPMC7063954 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:INTRODUCTION: Older age is associated with higher prevalence of chronic illness and functional impairment, contributing to an increased rate of hospitalization and admission to intensive care. The primary objective was to evaluate the rate, characteristics and outcomes of very old (age >or= 80 years) patients admitted to intensive care units (ICUs). METHODS: Retrospective analysis of prospectively collected data from the Australian New Zealand Intensive Care Society Adult Patient Database. Data were obtained for 120,123 adult admissions for >or= 24 hours across 57 ICUs from 1 January 2000 to 31 December 2005. RESULTS: A total of 15,640 very old patients (13.0%) were admitted during the study. These patients were more likely to be from a chronic care facility, had greater co-morbid illness, greater illness severity, and were less likely to receive mechanical ventilation. Crude ICU and hospital mortalities were higher (ICU: 12% vs. 8.2%, P < 0.001; hospital: 24.0% vs. 13%, P < 0.001). By multivariable analysis, age >/= 80 years was associated with higher ICU and hospital death compared with younger age strata (ICU: odds ratio (OR) = 2.7, 95% confidence interval (CI) = 2.4 to 3.0; hospital: OR = 5.4, 95% CI = 4.9 to 5.9). Factors associated with lower survival included admission from a chronic care facility, co-morbid illness, nonsurgical admission, greater illness severity, mechanical ventilation, and longer stay in the ICU. Those aged >or= 80 years were more likely to be discharged to rehabilitation/long-term care (12.3% vs. 4.9%, OR = 2.7, 95% CI = 2.6 to 2.9). The admission rates of very old patients increased by 5.6% per year. This potentially translates to a 72.4% increase in demand for ICU bed-days by 2015. CONCLUSIONS: The proportion of patients aged >or= 80 years admitted to intensive care in Australia and New Zealand is rapidly increasing. Although these patients have more co-morbid illness, are less likely to be discharged home, and have a greater mortality than younger patients, approximately 80% survive to hospital discharge. These data also imply a potential major increase in demand for ICU bed-days for very old patients within a decade.

Project description:BACKGROUND:Risk adjusted mortality for intensive care units (ICU) is usually estimated via logistic regression. Random effects (RE) or hierarchical models have been advocated to estimate provider risk-adjusted mortality on the basis that standard estimators increase false outlier classification. The utility of fixed effects (FE) estimators (separate ICU-specific intercepts) has not been fully explored. METHODS:Using a cohort from the Australian and New Zealand Intensive Care Society Adult Patient Database, 2009-2010, the model fit of different logistic estimators (FE, random-intercept and random-coefficient) was characterised: Bayesian Information Criterion (BIC; lower values better), receiver-operator characteristic curve area (AUC) and Hosmer-Lemeshow (H-L) statistic. ICU standardised hospital mortality ratios (SMR) and 95%CI were compared between models. ICU site performance (FE), relative to the grand observation-weighted mean (GO-WM) on odds ratio (OR), risk ratio (RR) and probability scales were assessed using model-based average marginal effects (AME). RESULTS:The data set consisted of 145355 patients in 128 ICUs, years 2009 (47.5%) & 2010 (52.5%), with mean(SD) age 60.9(18.8) years, 56% male and ICU and hospital mortalities of 7.0% and 10.9% respectively. The FE model had a BIC = 64058, AUC = 0.90 and an H-L statistic P-value = 0.22. The best-fitting random-intercept model had a BIC = 64457, AUC = 0.90 and H-L statistic P-value = 0.32 and random-coefficient model, BIC = 64556, AUC = 0.90 and H-L statistic P-value = 0.28. Across ICUs and over years no outliers (SMR 95% CI excluding null-value = 1) were identified and no model difference in SMR spread or 95%CI span was demonstrated. Using AME (OR and RR scale), ICU site-specific estimates diverged from the GO-WM, and the effect spread decreased over calendar years. On the probability scale, a majority of ICUs demonstrated calendar year decrease, but in the for-profit sector, this trend was reversed. CONCLUSIONS:The FE estimator had model advantage compared with conventional RE models. Using AME, between and over-year ICU site-effects were easily characterised.

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Independent Association of Glucose Variability With Hospital Mortality in Adult Intensive Care Patients: Results From the Australia and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Binational Registry.

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