The Official Journal of EuroPCR and the European Association of Percutaneous Coronary Interventions (EAPCI)

Interventions for valvular disease and heart failure

Derivation and external validation of a simple risk tool to predict 30-day hospital readmissions after transcatheter aortic valve replacement

EuroIntervention 2019;15:155-163. DOI: 10.4244/EIJ-D-18-00954

1. Columbia University Medical Center, New York, NY, USA; 2. Massachusetts General Hospital, Boston, MA, USA; 3. University Hospitals Cleveland Medical Center, Cleveland, OH, USA; 4. Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY, USA; 5. Warren Alpert Medical School, Brown University, Providence, RI, USA; 6. Houston Methodist, Houston, TX, USA; 7. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 8. David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA

Aims: Patients undergoing transcatheter aortic valve replacement (TAVR) possess a higher risk of recurrent healthcare resource utilisation due to multiple comorbidities, frailty, and advanced age. We sought to devise a simple tool to identify TAVR patients at increased risk of 30-day readmission.

Methods and results: We used the Nationwide Readmissions Database from January 2013 to September 2015. Complex survey methods and hierarchical regression in R were implemented to create a prediction tool to determine probability of 30-day readmission. Boot-strapped internal validation and cross-validation were performed to assess model accuracy. External validation was performed using a single-centre data set. Of 39,305 patients who underwent endovascular TAVR, 6,380 (16.2%) were readmitted within 30 days. The final 30-day readmission risk prediction tool included the following variables: chronic kidney disease, end-stage renal disease on dialysis (ESRD), anaemia, chronic lung disease, chronic liver disease, atrial fibrillation, length of stay, acute kidney injury, and discharge disposition. ESRD (OR 2.11, 95% CI: 1.7-2.63), length of stay ≥5 days (OR 1.64, 95% CI: 1.50-1.79), and short-term hospital discharge disposition (OR 1.81, 95% CI: 1.2-2.7) were the strongest predictors. The c-statistic of the prediction model was 0.63. The c-statistic in the external validation cohort was 0.69. On internal calibration, the tool was extremely accurate in predicting readmissions up to 25%.

Conclusions: A simple and easy-to-use risk prediction tool utilising standard clinical parameters identifies TAVR patients at increased risk of 30-day readmission. The tool may consequently inform hospital discharge planning, optimise transitions of care, and reduce resource utilisation.

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