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May 16, 2022Mayo Clinic Proceedings Innovations Quality & OutcomesOpen Access

Predictive Model for Heart Failure Readmission Using Nationwide Readmissions Database

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Why the study?

A heart failure readmission prediction model using the Nationwide Readmissions Database was needed to guide clinical management and reduce heart failure readmissions.

Population

Approximately 1,420,564 patients admitted for HF in the Nationwide Readmissions Database

Comparison

Derivation cohort (2010-2012) vs validation cohort (2013-2014)

Design

Retrospective cohort analysis

Follow-up

180 days

Key result

A predictive model for heart failure readmission using the Nationwide Readmissions Database yielded an area under the ROC curve of 0.58 in the derivation cohort and 0.59 in the validation cohort.

Authors

LZLillian ZhengNSNathan J. SmithBTBi Qing Teng

Discussion

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Member takes

Overview

Limited discrimination cautions against clinical use for readmission forecasting; leaves open development of improved models with richer predictors.

Study Design

Type

Cohort (n=1,420,564)

Multicenter

Yes

Structured PICO

P
Population
1,420,564 patients admitted for heart failure in the Nationwide Readmissions Database from January 1, 2010, to December 31, 2014
I
Intervention
Heart failure readmission prediction model based on a Cox proportional hazards model
O
Outcome
Prediction of readmission for heart failure at 30, 60, 90, and 180 dayshard clinical

A predictive model for heart failure readmission using a nationwide database demonstrated poor discriminative ability with an AUC of 0.58-0.59.

Cite This Study

Zheng et al. (2022) conducted a cohort in Heart failure (n=1,420,564). Heart failure readmission prediction model was evaluated on Heart failure readmission. A predictive model for heart failure readmission using the Nationwide Readmissions Database yielded an area under the ROC curve of 0.58 in the derivation cohort and 0.59 in the validation cohort.

synapsesocial.com/papers/6a082498df3db87398107de3https://doi.org/10.1016/j.mayocpiqo.2022.04.002
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