Rationale: Survivors of critical illness experience significant morbidity, but the impact of surviving the intensive care unit (ICU) has not been quantified comprehensively at a population level.Objectives: To identify factors associated with increased hospital resource use and to ascertain whether ICU admission was associated with increased mortality and resource use.Methods: Matched cohort study and pre/post-analysis using national linked data registries with complete population coverage. The population consisted of patients admitted to all adult general ICUs during 2005 and surviving to hospital discharge, identified from the Scottish Intensive Care Society Audit Group registry, matched (1:1) with similar hospital control subjects. Five-year outcomes included mortality and hospital resource use. Confounder adjustment was based on multivariable regression and pre/post within-individual analyses.Measurements and Main Results: Of 7,656 ICU patients, 5,259 survived to hospital discharge (5,215 [99.2%] matched to hospital control subjects). Factors present before ICU admission (comorbidities/pre-ICU hospitalizations) were stronger predictors of hospital resource use than acute illness factors. In the 5 years after the initial hospital discharge, compared with hospital control subjects, the ICU cohort had higher mortality (32.3% vs. 22.7%; hazard ratio, 1.33; 95% confidence interval, 1.22-1.46; P , 0.001), used more hospital resources (mean hospital admission rate, 4.8 vs. 3.3/person/5 yr), and had 51% higher mean 5-year hospital costs ($25,608 vs. $16,913/patient). Increased resource use persisted after confounder adjustment (P , 0.001) and using pre/post-analyses (P , 0.001). Excess resource use and mortality were greatest for younger patients without significant comorbidity.Conclusions: This complete, national study demonstrates that ICU survivorship is associated with higher 5-year mortality and hospital resource use than hospital control subjects, representing a substantial burden on individuals, caregivers, and society.
BackgroundRisk prediction models are used in critical care for risk stratification, summarising and communicating risk, supporting clinical decision-making and benchmarking performance. However, they require validation before they can be used with confidence, ideally using independently collected data from a different source to that used to develop the model. The aim of this study was to validate the Intensive Care National Audit & Research Centre (ICNARC) model using independently collected data from critical care units in Scotland.MethodsData were extracted from the Scottish Intensive Care Society Audit Group (SICSAG) database for the years 2007 to 2009. Recoding and mapping of variables was performed, as required, to apply the ICNARC model (2009 recalibration) to the SICSAG data using standard computer algorithms. The performance of the ICNARC model was assessed for discrimination, calibration and overall fit and compared with that of the Acute Physiology And Chronic Health Evaluation (APACHE) II model.ResultsThere were 29,626 admissions to 24 adult, general critical care units in Scotland between 1 January 2007 and 31 December 2009. After exclusions, 23,269 admissions were included in the analysis. The ICNARC model outperformed APACHE II on measures of discrimination (c index 0.848 versus 0.806), calibration (Hosmer-Lemeshow chi-squared statistic 18.8 versus 214) and overall fit (Brier’s score 0.140 versus 0.157; Shapiro’s R 0.652 versus 0.621). Model performance was consistent across the three years studied.ConclusionsThe ICNARC model performed well when validated in an external population to that in which it was developed, using independently collected data.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2253-14-116) contains supplementary material, which is available to authorized users.
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