Key result
Derived model outperforms LACE index in predicting 30-day readmissions with a 0.65 c-statistic.
Why the study?
Does a derived logistic regression model improve the prediction of 30-day readmissions compared to the LACE index in general medicine patients?
Population
5,862 general medicine patients in Singapore
Comparison
Derived logistic regression model vs LACE index
Design
Cohort
Follow-up
30 days
Authors
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Should not yet alter readmission risk stratification; leaves open need for validation and outcome trials in general medicine.
Observational (n=5,862)
Does a derived logistic regression model improve the prediction of 30-day readmissions compared to the LACE index in general medicine patients?
A derived logistic regression model demonstrated fair discriminative ability and slightly outperformed the LACE index for predicting 30-day readmissions in a general medicine population.
Low et al. (2015) conducted an observational in 30-day hospital readmission (n=5,862). Derived logistic regression model vs. LACE index was evaluated on 30-day readmission. A derived logistic regression model predicted 30-day readmissions with a c-statistic of 0.650, compared to 0.628 for the LACE index, in a cohort with a 9.8% readmission rate.
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