Performance of first pacemaker to use smart device app for remote monitoring.

BACKGROUND: High adherence to remote monitoring (RM) in pacemaker (PM) patients improves outcomes; however, adherence remains suboptimal. Bluetooth low-energy (BLE) technology in newer-generation PMs enables communication directly with patient-owned smart devices using an app without a bedside console. OBJECTIVE: To evaluate the success rate of scheduled RM transmissions using the app compared to other RM methods. METHODS: The BlueSync Field Evaluation was a prospective, international cohort evaluation, measuring the success rate of scheduled RM transmissions using a BLE PM or cardiac resynchronization therapy PM coupled with the MyCareLink Heart app. App transmission success was compared to 3 historical "control" groups from the Medtronic de-identified CareLink database: (1) PM patients with manual communication using a wand with a bedside console (PM manual transmission), (2) PM patients with wireless automatic communication with the bedside console (PM wireless); (3) defibrillator patients with similar automatic communication (defibrillator wireless). RESULTS: Among 245 patients enrolled (age 64.8±15.6 years, 58.4% men), 953 transmissions were scheduled through 12 months, of which 902 (94.6%) were successfully completed. In comparison, transmission success rates were 56.3% for PM manual transmission patients, 77.0% for PM wireless patients, and 87.1% for defibrillator wireless patients. Transmission success with the app was superior across matched cohorts based on age, sex, and device type (single vs dual vs triple chamber). CONCLUSION: The success rate of scheduled RM transmissions was higher among patients using the smart device app compared to patients using traditional RM using bedside consoles. This novel technology may improve patient engagement and adherence to RM.

Predicting Persistent Left Ventricular Dysfunction Following Myocardial Infarction: The PREDICTS Study.

BACKGROUND: Persistent severe left ventricular (LV) systolic dysfunction after myocardial infarction (MI) is associated with increased mortality and is a class I indication for implantation of a cardioverter-defibrillator. OBJECTIVES: This study developed models and assessed independent predictors of LV recovery to >35% and ≥50% after 90-day follow-up in patients presenting with acute MI and severe LV dysfunction. METHODS: Our multicenter prospective observational study enrolled participants with ejection fraction (EF) of ≤35% at the time of MI (n = 231). Predictors for EF recovery to >35% and ≥50% were identified after multivariate modeling and validated in a separate cohort (n = 236). RESULTS: In the PREDICTS (PREDiction of ICd Treatment Study) study, 43% of patients had persistent EF ≤35%, 31% had an EF of 36% to 49%, and 26% had an EF ≥50%. The model that best predicted recovery of EF to >35% included EF at presentation, length of stay, prior MI, lateral wall motion abnormality at presentation, and peak troponin. The model that best predicted recovery of EF to ≥50% included EF at presentation, peak troponin, prior MI, and presentation with ventricular fibrillation or cardiac arrest. After predictors were transformed into point scores, the lowest point scores predicted a 9% and 4% probability of EF recovery to >35% and ≥50%, respectively, whereas profiles with the highest point scores predicted an 87% and 49% probability of EF recovery to >35% and ≥50%, respectively. CONCLUSIONS: In patients with severe systolic dysfunction following acute MI with an EF ≤35%, 57% had EF recovery to >35%. A model using clinical variables present at the time of MI can help predict EF recovery.