JOURNAL ARTICLE
META-ANALYSIS
REVIEW
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Severity of illness and risk of readmission to intensive care: a meta-analysis.

Resuscitation 2009 May
BACKGROUND: Almost one in every 10 patients who survive intensive care will be readmitted to the intensive care unit (ICU) during the same hospitalisation. The association between increasing severity of illness (widely calculated in ICU patients) with risk of readmission to ICU has not been systematically summarized.

OBJECTIVE: The meta-analysis was designed to combine information from published studies to assess the relationship between severity of illness in ICU patients and the risk of readmission to ICU during the same hospitalisation.

DATA SOURCES: Studies were identified by searching MEDLINE (1966 to August 2008), EMBASE (1980-2008), and CINAHL (1982 to August 2008).

REVIEW METHODS: Studies included only adult populations, readmissions to ICU during the same hospitalisation and reports of valid severity of illness index.

RESULTS: Eleven studies (totaling 220000 patients) were included in the meta-analysis. Severity of illness (APACHE II, APACHE III, SAPS and SAPS II) measured at the time of ICU admission or discharge, was higher in patients readmitted to the ICU during the same hospitalisation compared to patients not-readmitted (both p-values<0.001). The risk of readmission to ICU increased by 43% with each standard deviation increase in severity of illness score (regardless if measured on admission to, or discharge from the ICU) (odds ratio (OR)=1.43, 95% confidence interval (CI)=1.3-1.6).

CONCLUSIONS: A relationship between increasing intensive care severity of illness and risk of readmission to ICU was found. The effect was the same regardless of the time of measurement of severity of illness (at admission to ICU or the time of discharge from ICU). However, further research is required to develop more comprehensive tools to identify patients at risk of readmission to ICU to allow the targeted interventions, such as ICU-outreach to follow-up these patients to minimize adverse events.

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