What is the clinical evidence from this study?

Study design: Cohort. Population: ICU survivors (n=704963). Intervention: ICU Discharge Readiness Score (predictive models). Primary outcome: Area under the receiver operator characteristic curves (auROC) for models predicting readmission and death within 48 hours of ICU discharge.

What does this research mean for the field?

Predictive models for death and readmission after ICU discharge demonstrated excellent and good discrimination, with auROCs of 0.92 and 0.71, respectively, in a large validation cohort. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

November 7, 2012PLoS ONEOpen Access

Readmissions and Death after ICU Discharge: Development and Validation of Two Predictive Models

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Key result

Predictive models for death and readmission after ICU discharge demonstrated auROCs of 0.92 and 0.71, respectively, in a validation cohort of 234,987 patients.

Population

704,963 ICU survivors from 32 health systems representing 219 hospitals and 402 ICUs in the United States…

Design

Cohort, Patients were randomized in a 2:1 fashion to development and…

Follow-up

48 hours

Authors

OBOmar BadawiUniversity of Maryland, Baltimore MBMichael J. BreslowPhilips (United States)

Discussion

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Implication

Models show strong discrimination for post-ICU death; hypothesis-generating for clinical use pending prospective validation.

Study Design

Type

Cohort (n=704,963)

Randomization

2:1 to development and validation cohorts

Multicenter

Yes

Structured PICO

Population

704,963 ICU survivors from 32 health systems representing 219 hospitals and 402 ICUs in the United States. Exclusions: ICU length of stay < 4 hours; age < 16 years; expired in the ICU; discharge location of transfer to another ICU or locations external to the hospital; and the presence of a 'do not resuscitate' (DNR) or 'comfort measures only' (CMO) order at ICU discharge.

Intervention

Development and validation of two predictive models (ICU Discharge Readiness Score) using multivariable logistic regression on variables including patient demographics, ICU admission diagnosis, admission severity of illness, laboratory values, and physiologic variables present during the last 24 hours of the ICU stay.

Outcome

Area under the receiver operator characteristic curves (auROC) in the validation cohorts for the models predicting readmission and death within 48 hours of ICU dischargehard clinical

Predictive models utilizing electronic clinical information system data from the last 24 hours of an ICU stay demonstrated good to excellent discrimination for predicting death and readmission within 48 hours of ICU discharge.

Limitations

Retrospective study design limited by the quality of documentation in the clinical information system
Calculation of the score is complex and cannot be performed manually
High proportion of missing Glasgow Coma Scale (GCS) values on the day of discharge
Potential inclusion of patients with undocumented care limitations
High collinearity among variables prevents clinical interpretation of adjusted odds ratios
Retrospective design
Prospective validation is warranted
Low positive predictive values due to the relatively low prevalence of each outcome

Cite This Study

Badawi et al. (2012) conducted a cohort in ICU survivors (n=704,963). ICU Discharge Readiness Score (predictive models) was evaluated on Area under the receiver operator characteristic curves (auROC) for models predicting readmission and death within 48 hours of ICU discharge. Predictive models for death and readmission after ICU discharge demonstrated auROCs of 0.92 and 0.71, respectively, in a validation cohort of 234,987 patients.

synapsesocial.com/papers/6a1555deb03a896dfa820d34 https://doi.org/10.1371/journal.pone.0048758

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Readmissions and Death after ICU Discharge: Development and Validation of Two Predictive Models

Discussion

Member takes

Implication

Study Design

Structured PICO

Limitations

Cite This Study

Readmissions and Death after ICU Discharge: Development and Validation of Two Predictive Models

Discussion

Member takes

Implication

Study Design

Structured PICO

Limitations

Cite This Study

Also Consider

Also Consider