Limited-resource, limited-guideline? Towards the delivery of appropriate and contextual cardiovascular care across settings
Notice bibliographique
Résumé
This commentary refers to ‘Applicability of European Society of Cardiology guidelines according to gross national income’, by W.B. van Dijk et al., https://doi.org/10.1093/eurheartj/ehac606 Societal guidelines are developed through a rigorous process involving multidisciplinary experts and evidence synthesis and drive clinical practice worldwide. Adoption of guidelines, however, can vary greatly due to resource constraints and other contextual factors. Van Dijk et al. finds that the implementation of European Society of Cardiology guidelines decreases as countries’ gross national income decreases.1 In other words, whereas high-income countries have a high implementation of guidelines, low- and middle-income countries (LMICs) do not. Barriers mainly include a lack of reimbursement of drugs and other care-related financial barriers. The authors are to be applauded for their important work, which underlines the poor generalizability of regional guidelines to other parts of the world. Cardiovascular guidelines have largely originated from major societies in North America and Europe. These guidelines have consistently been considered best practices for cardiovascular care and are, therefore, generally adopted worldwide. However, these guidelines have been developed with North American and European populations and health systems in mind, are informed by North American and European experts, and rely on evidence from trials and large observational studies that predominantly originate from high-income countries. Yet, differences exist in genetics, pathophysiology, and epidemiology across different regions. Similarly, systemic factors, such as health technology assessment, regulatory approval processes, and reimbursement mechanisms, vary and fragment the global generalizability of guidelines. Moreover, the costs and availability of drugs, equipment, and healthcare services differ widely worldwide. Cardiovascular and surgical supply chains are a considerable struggle in LMICs resulting in periodic stockouts of essential drugs and consumables.2 When available, costs may be prohibitive, either for patients and their families or for institutions themselves, limiting appropriate adoption of ‘global’ guidelines. Lastly, cultural, religious, and societal factors may influence the consideration of ‘appropriate use’ across different settings. It may be expected that the findings from the authors are similar, if not worse, for cardiac surgical guidelines. Six billion people lack access to safe, timely, and affordable cardiac surgical care when needed, whereby more than 100 countries and territories lack even a single cardiac surgeon.3 For example, for valvular surgery, the decision to replace or repair a valve is not always purely clinical4: the absence of valvular prostheses may force surgeons to repair a valve that may not be fully repairable. Similarly, the decision to use a mechanical or biological prosthesis is often an age-based and patient-driven one; the absence of one or another makes such decision-making and guideline recommendations obsolete. Collectively, these issues question whether existing guidelines should be considered the guiding light for cardiovascular care worldwide. The authors thoughtfully propose that ‘second and third best recommendations, for example, based on income levels’ may be included in future guidelines.1 Perhaps more appropriately and where possible, regional and/or national guidelines adapted to the local context, informed by representative stakeholders, and developed by the respective cardiology and cardiac surgical societies may be developed. Regardless, it is clear that change is urgently needed to deliver appropriate and contextual cardiovascular care in any setting: limited-resource settings should not equate to limited-guideline settings. D.V. is supported by the Canadian Institutes of Health Research (CIHR) Vanier Canada Graduate Scholarship. All authors declare no conflict of interest for this contribution.
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 | 0,085 | 0,180 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,008 | 0,015 |
| Communication savante | 0,024 | 0,027 |
| Science ouverte | 0,008 | 0,033 |
| Intégrité de la recherche | 0,014 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,003 |
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 ».