Eosinopenia as a Predictor of Unexpected Re-Admission and Mortality after Intensive Care Unit Discharge

Yip, Bak-Sau; Km, Ho

doi:10.1177/0310057x1304100130

Cited by 21 publications

(21 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The remaining studies [25, 33, 41, 50, 53] had 95% CIs that overlapped the null value, suggesting that there was no statistically significant difference in severity of illness scores between readmitted and non-readmitted patients. Sensitivity analyses revealed similar results.…”

Section: Resultsmentioning

confidence: 99%

Association of severity of illness and intensive care unit readmission: A systematic review

et al. 2016

View full text Add to dashboard Cite

Objectives To determine whether ICU readmission is associated with higher severity of illness scores in adult patients. Background Readmissions to the intensive care unit (ICU) are associated with increased costs, morbidity, and mortality. Methods We performed searches of MEDLINE, EMBASE, and grey literature databases. We selected studies reporting data from adults who were hospitalized in an ICU, received severity of illness scores, and were discharged from the ICU. Characteristics of readmitted and non-readmitted patients were examined. Results We screened 4766 publications and included 31 studies in our analysis. In most studies, severity of illness scores were higher in patients readmitted to the ICU. Readmission was also associated with higher mortality and longer ICU and hospital stays. Excessive heterogeneity precluded the reporting of results in the form of a meta-analysis. Conclusions ICU readmission is associated with higher severity of illness scores during the same hospitalization in adult patients.

show abstract

Section: Resultsmentioning

confidence: 99%

Association of severity of illness and intensive care unit readmission: A systematic review

et al. 2016

View full text Add to dashboard Cite

show abstract

“…We identified 58 studies that satisfied the inclusion criteria and that had data which allowed calculation of the cumulative incidence of readmission to the ICU ( n = 46 studies) or the cumulative incidence of hospital mortality ( n = 49 studies) for patients discharged alive from the ICU (Figure 1 ) [ 2 , 4 , 5 , 8 , 11 , 12 , 19 - 70 ]. The characteristics of the studies are summarized in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care

et al. 2014

View full text Add to dashboard Cite

IntroductionWe sought to derive literature-based summary estimates of readmission to the ICU and hospital mortality among patients discharged alive from the ICU.MethodsWe searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from inception to March 2013, as well as the reference lists in the publications of the included studies. We selected cohort studies of ICU discharge prognostic factors that in which readmission to the ICU or hospital mortality among patients discharged alive from the ICU was reported. Two reviewers independently abstracted the number of patients readmitted to the ICU and hospital deaths among patients discharged alive from the ICU. Fixed effects and random effects models were used to estimate the pooled cumulative incidence of ICU readmission and the pooled cumulative incidence of hospital mortality.ResultsThe analysis included 58 studies (n = 2,073,170 patients). The majority of studies followed patients until hospital discharge (n = 46 studies) and reported readmission to the ICU (n = 46 studies) or hospital mortality (n = 49 studies). The cumulative incidence of ICU readmission was 4.0 readmissions (95% confidence interval (CI), 3.9 to 4.0) per 100 patient discharges using fixed effects pooling and 6.3 readmissions (95% CI, 5.6 to 6.9) per 100 patient discharges using random effects pooling. The cumulative incidence of hospital mortality was 3.3 deaths (95% CI, 3.3 to 3.3) per 100 patient discharges using fixed effects pooling and 6.8 deaths (95% CI, 6.1 to 7.6) per 100 patient discharges using random effects pooling. There was significant heterogeneity for the pooled estimates, which was partially explained by patient, institution and study methodological characteristics.ConclusionsUsing current literature estimates, for every 100 patients discharged alive from the ICU, between 4 and 6 patients on average will be readmitted to the ICU and between 3 and 7 patients on average will die prior to hospital discharge. These estimates can inform the selection of benchmarks for quality metrics of transitions of patient care between the ICU and the hospital ward.

show abstract

“…A retrospective study of 1446 patients demonstrates that an eosinophil count <0.01 K/μL at ICU discharge is associated with an increased risk of readmission (HR 2.50 [95 % CI 1.38 to 4.50], P = 0.002) and hospital mortality (HR 2.65 [95 % CI 1.77 to 3.98], P = 0.001) [11]. Our ROC curve analysis placed that point in 0.031 k/μL.…”

Section: Discussionmentioning

confidence: 99%

Eosinophil count at intensive care unit admission was not predictor of hospital mortality: results of a case control study

et al. 2015

View full text Add to dashboard Cite

BackgroundPredicting mortality in the intensive care unit (ICU) is one of the biggest challenges in critical care medicine. Several studies have linked the presence of eosinopenia with adverse outcomes in different populations.MethodsWe performed a case control study to determine whether the eosinophil count at ICU admission was a predictor of hospital mortality. We included data from patients 18 years or older admitted to the medical or surgical ICU in a university hospital in northern of Mexico. Medical records of 86 non-survivors (cases) and 99 discharged alive patients (controls) were randomly reviewed; clinical records of patients with an ICU stay of less than 24 h and those whose information was incomplete were excluded.ResultsMedian of eosinophil count at ICU admission was 0.013 (interquartile range (IQR) 0.00 to 0.57) K/μL. There was no significant statistical difference in eosinophils at admission between survivors and non-survivors (0.014 [IQR 0.00 to 0.36] vs. 0.010 [IQR 0.00 to 0.57] K/μL, P = 0.35). In the multivariate analysis, APACHE II score at ICU admission and discharge were the only mortality predictors. Survivors had a significantly greater increase in eosinophil count during the first 7 days of ICU stay (0.104 [IQR −0.64 to 0.41] vs. 0.005 [IQR −1.79 to 0.43] K/μL, P = 0.004).ConclusionsIn our study, eosinophil count at ICU admission was not associated with increased hospital mortality. The larger increase in number of eosinophils observed during the first week of ICU stay in surviving patients deserves to be investigated further.

show abstract

Eosinopenia as a Predictor of Unexpected Re-Admission and Mortality after Intensive Care Unit Discharge

Cited by 21 publications

References 34 publications

Association of severity of illness and intensive care unit readmission: A systematic review

Association of severity of illness and intensive care unit readmission: A systematic review

A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care

Eosinophil count at intensive care unit admission was not predictor of hospital mortality: results of a case control study

Contact Info

Product

Resources

About