Evidence map›Paper›PMID 25551448›Full record

SynthesisCritical care (London, England)2014

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

F Shaun Hosein, Derek J Roberts, Tanvir Chowdhury Turin, David Zygun, William A Ghali, Henry T Stelfox

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in Critical care (London, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  20. [Unplanned admission or readmission to the intensive care unit : Avoidable or fateful?]Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

F Shaun HoseinDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Canada. fshosein@ucalgary.ca.
Derek J RobertsDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Canada. derek.roberts01@gmail.com.
Tanvir Chowdhury TurinDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Canada. turin.chowdhury@ucalgary.ca.
David ZygunDivision of Critical Care, University of Alberta, 11220-83 Ave, Edmonton, AB, T6G 2B7, Canada. zygun@ualberta.ca.
William A GhaliDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Canada. wghali@ucalgary.ca.
Henry T StelfoxDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Canada. tstelfox@ucalgary.ca.

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

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.

Indexed as

Hospital MortalityIntensive Care UnitsBenchmarkingCohort StudiesHumansIncidencePatient DischargePatient Readmission

Identifiers

PMID25551448
PMCPMC4312433

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.