Security and performance of remote patient monitoring for chronic heart failure with Satelia® Cardio: First results from real-world use

Background: Since 2019, remote patient monitoring (RPM) for patients with chronic heart failure (CHF) has been supported by the European Society of Cardiology. However, real-world data on the use of such solutions has been limited and not primarily based on patient-reported outcomes. The aim of this study was to describe the Satelia® Cardio solution in France within the French ETAPES funding program and assess the security and performance of its clinical algorithm.Methods: A retrospective observational study was conducted on CHF patients monitored by RPM through Satelia® Cardio. From September 1, 2018, to June 30, 2020, patients were included if they had completed over six months of follow-up. The risk of a possible CHF decompensation was categorized by the system in three levels: green, orange and red. The algorithm security and performance were assessed through the negative predictive value (NPV) of the prediction of hospitalization of a patient within seven days.Results: In total, 331 patients were included in this study with 36,682 patient self-administered questionnaires answered. Patients were mostly males (70.4%) and had a mean age of 68.1 years. The mean left ventricular ejection fraction (LVEF) was 35.4% (± 12.3) and 73.3% of patients had a LVEF ≤ 40%. The questionnaire response rate was 90.9%. A green status was generated for 95.3% of answers. There were 4.5% (n = 1,499) orange alerts and 0.2% (n = 74) red alerts. Overall, 92.1% of patients had at least one CHF related hospitalization and 31.7% (n = 105) of these cases were non-scheduled. The NPV at seven days was 99.43%.Conclusion: Satelia® Cardio is a feasible, relevant and reliable solution to safely monitor the cohorts of patients with CHF, reassuring cardiologists about patient stability

Renal function estimation and Cockcroft–Gault formulas for predicting cardiovascular mortality in population-based, cardiovascular risk, heart failure and post-myocardial infarction cohorts: The Heart ‘OMics’ in AGEing (HOMAGE) and the high-risk myocardial infarction database initiatives

Background: Renal impairment is a major risk factor for mortality in various populations. Three formulas are frequently used to assess both glomerular filtration rate (eGFR) or creatinine clearance (CrCl) and mortality prediction: body surface area adjusted-Cockcroft–Gault (CG-BSA), Modification of Diet in Renal Disease Study (MDRD4), and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. The CKD-EPI is the most accurate eGFR estimator as compared to a “gold-standard”; however, which of the latter is the best formula to assess prognosis remains to be clarified. This study aimed to compare the prognostic value of these formulas in predicting the risk of cardiovascular mortality (CVM) in population-based, cardiovascular risk, heart failure (HF) and post-myocardial infarction (MI) cohorts. Methods: Two previously published cohorts of pooled patient data derived from the partners involved in the HOMAGE-consortium and from four clinical trials – CAPRICORN, EPHESUS, OPTIMAAL and VALIANT – the high risk MI initiative, were used. A total of 54,111 patients were included in the present analysis: 2644 from population-based cohorts; 20,895 from cardiovascular risk cohorts; 1801 from heart failure cohorts; and 28,771 from post-myocardial infarction cohorts. Participants were patients enrolled in the respective cohorts and trials. The primary outcome was CVM. Results: All formulas were strongly and independently associated with CVM. Lower eGFR/CrCl was associated with increasing CVM rates for values below 60 mL/min/m2. Categorical renal function stages diverged in a more pronounced manner with the CG-BSA formula in all populations (higher χ2 values), with lower stages showing stronger associations. The discriminative improvement driven by the CG-BSA formula was superior to that of MDRD4 and CKD-EPI, but remained low overall (increase in C-index ranging from 0.5 to 2%) while not statistically significant in population-based cohorts. The integrated discrimination improvement and net reclassification improvement were higher (P < 0.05) for the CG-BSA formula compared to MDRD4 and CKD-EPI in CV risk, HF and post-MI cohorts, but not in population-based cohorts. The CKD-EPI formula was superior overall to MDRD4. Conclusions: The CG-BSA formula was slightly more accurate in predicting CVM in CV risk, HF, and post-MI cohorts (but not in population-based cohorts). However, the CG-BSA discriminative improvement was globally low compared to MDRD4 and especially CKD-EPI, the latter offering the best compromise between renal function estimation and CVM prediction. Electronic supplementary material The online version of this article (doi:10.1186/s12916-016-0731-2) contains supplementary material, which is available to authorized users