Why the study?
The study was conducted to prospectively evaluate the accuracy of the LACE and BOOST models in predicting unplanned hospital readmission in older patients (>75 years).
Do the LACE and BOOST models accurately predict 30-day emergency readmission in older patients?
Do the LACE and BOOST models accurately predict 30-day emergency readmission in older patients?
Both the BOOST and LACE scores are significant but poor predictive models for 30-day hospital readmission in older patients.
LACE and BOOST may aid readmission risk stratification in patients >75; leaves open external validation before clinical adoption.
AIM: To undertake a prospective study of the accuracy of two models (LACE and BOOST) in predicting unplanned hospital readmission in older patients (>75 years). METHODS: Data were collected from a single centre prospectively on 110 patients over 75 years old admitted to the acute medical unit. Follow-up was conducted at 30 days. The primary outcome was the c-statistic for both models. RESULTS: The readmission rate was 32.7% and median age 82 years, and both BOOST and LACE scores were significantly higher in those readmitted compared with those who were not. C-statistics were calculated for both tools with BOOST score 0.667 (95% CI 0.559-0.775, P = .005) and LACE index 0.685 (95% CI 0.579-0.792, P = .002). CONCLUSION: In this prospective study, both the BOOST and LACE scores were found to be significant yet poor, predictive models of hospital readmission. Recent hospitalisation (within the previous 6 months) was found to be the most significant contributing factor.
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Armitage et al. (2021) studied this question.
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