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Funding Acknowledgements Type of funding sources: None. Background The HeartLogic algorithm combines multiple implantable defibrillator (ICD) sensor data and has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation. Purpose We determined if remotely monitored data from this algorithm can be used to identify patients at high risk of mortality. Methods The HeartLogic feature was activated in 568 ICD patients from 26 centers. Results During a median follow-up of 26 months [25th–75th percentile: 16-37], 1200 HeartLogic alerts were recorded in 370 (65%) patients. Overall, the time IN the alert state was 13% of the total observation period (151 out of 1159 years) and 20% of the follow-up period of the 370 patients with alerts. During follow-up, 55 patients died (37 in the group with alerts). Experiencing any alert episode was associated with a substantially increased risk of death [hazard ratio (HR): 2.08, 95% confidence interval (CI): 1.16–3.73, P = 0.039]. Additionally, a time IN alert ≥20% was associated with death (HR: 4.07, 95%CI: 2.19-7.54, p Conclusions The HeartLogic algorithm provides an index that can be used to identify patients at higher risk of all-cause mortality. The index status identifies periods of significantly increased risk of death.

Funding Acknowledgements Type of funding sources: None. Background Predicting worsening heart failure (WHF) events in chronic heart failure (HF) patients is important to avoid hospitalizations. In patients implanted with cardiac implantable electronic devices (CIEDs) remote monitoring may help to identify patients at risk of WHF thanks to the ability to monitor physiological parameters that may change before WHF. However, clinicians need to know patient HF-related signs, symptoms and therapy non-compliance to determine type and time of necessary interventions. A patient Smartphone Application (App) may be an ideal option to remotely collect this information from patients and help clinicians in the decision-making process. Purpose to assess the penetration of App technology in a large real-world HF population and to evaluate patient willingness and compliance to use a HF-dedicated App to weekly send a diary on HF signs, symptoms and therapy compliance to the cardiologist. Methods From January 2021 to July 2022, 10 Italian hospitals in the framework of the One Hospital ClinicalService project designed a questionnaire on the use of App technology and submitted it to their HF patients with CIED during scheduled in-hospital follow-up. If the patient or his caregiver was able and willing to use Apps, the HF-dedicated App was activated on his smartphone. Compliance in using the App (= percentage of weeks in a year with at list an App diary received by all patients) was evaluated for patients who have received it for at least one year. Results 495 HF patients with CIED (age 67±13 years, 79% males, 26% NYHA III-IV, LVEF 35±11%, 60% with 3-chamber CIED, 43% with high school qualification) completed the questionnaire. Out of them, 80% have access to App technology, directly or through a caregiver; ≥62% can do all high-level activities (APP installation, email, web browsing) and 21% has already used Health Apps; 73% is willing to weekly send a diary using the App. 311 patients (63% of respondents) downloaded the HF-dedicated App on their or caregiver’s smartphone. They were younger and with higher school qualification than those not receiving the App. No other difference in baseline characteristics was seen. 138 patients have received the App for at least 1 year. Their compliance decreased during time, from 60% (weeks 1-13) to 42% (weeks 40-52; p Conclusion In a large real-world HF population with CIED patients, the penetration of Smartphone technology was high and > 60-year-old patients had higher compliance to the use of a new HF-dedicated App compared to younger patients. The use of Smartphone App technology to collect WHF sign/symptoms is feasible and may improve remote management of HF patients.