Real-world clinical characterisation and comorbidity burden of heart failure patients in a national remote monitoring program: the CODEC-HF registry
E Berthelot, G Faedda, Q Delbaere, J M Tartiere, P Khanoyan, M Greffe, M Manceau, F Albert, C Fauvel, G P Steg, F RoubilleAbstract
Background
Remote monitoring (RM) is a cornerstone of heart failure (HF) management. Identifying clinical phenotypes and comorbidity burdens in large RM registries is critical to tailoring digital health interventions and improving patient outcomes.
Purpose
To characterise the demographic and clinical profile of patients enrolled in the CODEC-HF registry and evaluate the distribution of personalised remote monitoring strategies.
Methods
CODEC-HF is a prospective, observational, multicentre research program conducted across 17 centres in France. The registry included adult patients with chronic HF eligible for standard RM frameworks under French national recommendations. Inclusion criteria required a HF-related hospitalisation within the 12 previous months or a NYHA functional class > II symptoms with elevated natriuretic peptides (BNP > 100 pg/mL or NT-proBNP > 1000 pg/mL). Patients were monitored via a centralised platform integrating data from connected scales, blood pressure monitors, and sleep analysers. The inclusion period spanned 31 months, with a follow-up duration of up to 2 years.
Results
A total of 1,486 patients were enrolled between May 2023 and December 2025. The cohort was predominantly composed by male (63.2%) with a mean age of 72.4 ± 13.7 years. Clinical assessment showed a primarily symptomatic population with 54.7% of patients in NYHA class I-II and 45.3% in NYHA class III-IV. Phenotypic distribution consisted of HFrEF (51.5%), HFpEF (36.6%), and HFmrEF (11.9%). Several comorbidities were highly prevalent: hypertension (61.8%), chronic kidney disease (36.7%), and type 2 diabetes (31.1%). At least one episode of atrial fibrillation was reported in 54.5% of the cohort. The mean BMI was 27.0 ± 6.0 kg/m², with 37.7% of patients having a normal BMI, 31.1% overweight, 23.4% obese, 3.4% with severe obesity and 4.4% underweight. Patients were allocated to three RM strategies at the investigators' discretion: connected weight scales alone (93.3%), scales combined with blood pressure monitors (5.5%), or scales combined with sleep analysers (1.2%).
Conclusion
The CODEC-HF registry will provide high-quality real-world evidence to optimise digital health interventions in heart failure. By identifying personalised combinations of connected devices and refining predictive algorithms, this research aims to enhance the prevention of health deterioration and align routine care with advanced ESC standards. Final results are expected to be available by 2028, following the completion of the long-term follow-up for the last enrolled patients.Characteristics of CODEC-HF population