Revolutionizing cardiac rehabilitation: France’s new paths beyond the centre
Notice bibliographique
Résumé
Cardiac rehabilitation (CR) is recognized worldwide as one of the most effective post-cardiac event interventions: it helps patients recover strength, reduce the risk of recurrence, and improve overall quality of life. Despite robust guidelines and clear benefits, CR under-utilization remains a major issue across both high- and middle-income countries. For example, in the United States only about one-third of eligible patients after myocardial infarction,1 percutaneous coronary intervention, or coronary artery bypass surgery are referred to CR, and participation rates decline sharply among women and older adults. In the United Kingdom, participation hovers around 50%,2 while in Canada and Australia, referral and enrolment rates vary widely, often below 30–40%.3,4 In many low- and middle-income countries, rates are even lower, in some cases under 20%.5 Barriers to participation are similarly global: long travel distances to rehab facilities, competing work or family responsibilities, lack of transportation, limited programme capacity, and socio-economic disparities. These challenges create a gap between what guidelines recommend and what patients actually receive. To address this challenge, the Group Exercise Rehabilitation Sports–Prevention of the French Society of Cardiology recently published a consensus document proposing innovative solutions.6 Their aim is to make CR more flexible, more accessible, and better adapted to the realities of patients’ lives. The document outlines four experimental care models that go beyond traditional hospital-based rehabilitation. 1. Light private rehabilitation structures (LPRS) Community-based teams mirror traditional centres but with greater flexibility. Extended opening hours help patients balance rehab with work and family life. Early trials involving thousands of patients suggest strong adherence and higher participation among women. 2. Home-based telerehabilitation (Walk Hop) After an initial in-centre assessment, patients continue at home with a cycle ergometer, heart-rate monitor, and digital platform. Data are transmitted daily, with remote supervision and weekly video calls. Results: improved fitness (+15%), adherence near 90%, and high patient satisfaction. 3. Hybrid telerehabilitation (Read’hy) Combines supervised centre sessions with home-based training, supported by telemedicine. Tested across various patient groups, it showed gains of +22% in exercise capacity and improved quality of life, with adherence above 80%. 4. Coupled care with multi-professional group practices (EVA CORSE) Patients begin in a specialist centre and continue locally in multi-professional group practices (MGPs), coordinated remotely by the central team. This reduces travel barriers and supports vulnerable patients, while maintaining safety and quality. To gain insight into how these models work in practice, we interviewed Dr. Frédéric Schnell, one of the consensus document’s authors. He emphasized that these initiatives are not academic trials in the traditional sense, but rather real-world experiments launched under France’s Article 51 innovation framework. ‘It’s more like experimentation than academic research’, Dr. Schnell explained. ‘The goal is to test new organizational models, to see whether they are safe, effective, and acceptable. If they prove successful, the government may eventually reimburse them and integrate them into standard care’. According to Dr. Schnell, the need for innovation is clear. Traditional inpatient CR requires substantial resources and is not scalable to the entire patient population. ‘We cannot provide enough inpatient rehab for everyone’, he said. ‘We need simpler, lighter solutions so that more patients can benefit’. In some regions of France, the shortage of rehabilitation centres is particularly stark. Patients may face journeys of over an hour each way to attend sessions, a barrier that makes participation unrealistic. This geographical factor also explains why France still relies more heavily on inpatient rehabilitation compared with neighbouring Belgium, where distances are shorter and outpatient rehab is more feasible. One of the key challenges is deciding which patients should go to inpatient, outpatient, or home-based rehabilitation. Dr. Schnell described the process as a step-by-step evaluation: patients who have undergone major surgery or transplantation, or who remain medically unstable, clearly require inpatient care. Stable patients living close to a centre may be directed to outpatient programmes. Meanwhile, patients at lower risk who live further away can be referred to LPRS facilities or to telerehabilitation. ‘We think we need a bit of everything to cover a broad range of patients’, Dr. Schnell said. ‘It would be dangerous to impose a single model. Flexibility is essential’. The pilots have demonstrated that telerehabilitation can be safe, effective, and popular with patients. But financial and policy barriers remain. ‘The government is cautious’, Dr. Schnell noted. ‘They fear that if telerehabilitation is reimbursed for everyone, costs could escalate quickly. For now, these models are still experimental. But early results suggest that they are cost-effective in the long run, because preventing complications and hospital readmissions saves money overall’. In this respect, the French debate mirrors international discussions about how best to integrate digital health into mainstream care. The challenge is not only technical but also political: how to balance innovation, safety, and financial sustainability. Geography is a central theme in the French experience. ‘Sometimes it’s just too far’, Dr. Schnell said. ‘In Brittany, for example, patients may live more than an hour from the nearest rehabilitation centre. That explains why we still rely more on inpatient rehabilitation’. In contrast, in small countries like Belgium distances are shorter, which has allowed outpatient rehabilitation to dominate. These differences highlight the importance of tailoring health policy to the realities of each healthcare system and its geography. The consensus document represents an important milestone in the evolution of CR in France. By formalizing the lessons of ongoing experiments, it provides a framework for scaling up alternative models of care. Whether these models will be widely adopted depends on the results of ongoing evaluations and on future policy decisions. For Schnell, one principle remains non-negotiable: safety. ‘Safety was the first requirement’, he said. ‘The patient must understand when they should not be in a remote pathway. But if we do this right, we can finally reach many more patients who need rehabilitation’. In the end, France’s experiments in CR may hold lessons not just for its own health system, but for other countries grappling with similar challenges of access, cost, and patient engagement. Frédéric Schnell (Conceptualization [lead], Project administration [equal], Resources [lead], Supervision [equal], Writing—original draft [equal], Writing—review & editing [lead]), Xuejiao Wu (Project administration [supporting], Supervision [supporting], Writing—original draft [equal], Writing—review & editing [lead]), and Linqi Xu (Conceptualization [lead], Methodology [lead], Project administration [lead], Supervision [lead], Writing—original draft [lead], Writing—review & editing [equal])
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,010 | 0,007 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,012 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,005 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».