Impact of Adaptive Optimization Algorithms on HF Readmissions | Journal Scan
What is the impact of the adaptive cardiac resynchronization therapy (aCRT) algorithm on 30-day hospital readmission rate compared with conventional CRT optimized by echocardiography?
The study cohort was comprised of individuals enrolled in the Adaptive CRT trial. This study (reported earlier) randomized 478 patients undergoing CRT defibrillation on a 2:1 basis to aCRT (n = 318) or to CRT with echocardiographic optimization (Echo, n = 160), and followed up on these patients for a mean of 20.2 months (range 0.2-1.3 months). The aCRT algorithm automatically adjusts atrioventricular (AV) and interventricular delays on the basis of frequent evaluation of the patient’s underlying conduction. Specifically, the algorithm provides left ventricular (LV)-only pacing synchronized to right ventricular (RV) activation when intrinsic AV conduction is normal, or biventricular pacing when AV conduction is prolonged. The investigators utilized logistic regression with generalized estimating equation methodology to compare the proportion of patients hospitalized for heart failure (HF) and for all causes, who had a readmission within 30 days.
The study investigators found a significant relative reduction in both all-cause 30-day readmissions (46%) and HF 30-day readmissions (59%). For all-cause hospitalization, the 30-day readmission rate was 14.8% (35 of 237) in the aCRT group compared with 24.8% (39 of 157) in the Echo group (odds ratio [OR], 0.54; 95% confidence interval [CI], 0.31-0.94; p = 0.03). For HF hospitalizations, the 30-day readmission rate was 19.1% (17 of 89) in the aCRT group and 35.7% (15 of 42) in the Echo group (OR, 0.41; 95% CI, 0.19-0.86; p = 0.02). The risk of readmission after HF or all-cause index hospitalization with aCRT was also significantly reduced beyond 30 days.
The authors concluded that aCRT algorithm is associated with a significant reduction in the probability of a 30-day readmission after both HF and all-cause hospitalizations, and the observation of reduced readmissions with aCRT suggests a physiological benefit related to reduced RV pacing and frequent optimization.
This study is important because it demonstrates how computer-associated algorithms can optimize cardiac resynchronization to reduce morbidity—computational medicine is now by the bedside. Potential mechanisms for these advantageous effects include decreased incidence of RV pacing and reduced burden of atrial fibrillation. As the authors point out, the next step would be to perform a prospective randomized clinical trial to validate these findings and to determine whether computer-generated optimization of CRT would result in sustainable improvements in LV remodeling and improve survival.
Keywords: Algorithms, Cardiac Resynchronization Therapy, Cohort Studies, Cost of Illness, Echocardiography, Heart Failure, Heart Ventricles, Hospitalization, Logistic Models, Patient Readmission
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