Towards a better standard for defining high bleeding risk patients: can we now translate this into a better practice?
Notice bibliographique
Résumé
This editorial refers to ‘Validation of high bleeding risk criteria and definition as proposed by the Academic Research Consortium for High Bleeding Risk’†, by N. Corpataux et al., on page 3743. A decade ago, the Academic Research Consortium (ARC) published a standardized bleeding definition with the aim of simplifying comparisons across clinical studies.1 Recently, the same international group of experts developed a set of high bleeding risk (HBR) criteria to promote consistency across trials evaluating this vulnerable subset of patients.2 The ARC-HBR criteria were not developed as a clinical decision support tool, but rather to simplify the comparisons between studies focusing on patients bearing a HBR phenotype, and to facilitate regulatory decisions. The ARC-HBR criteria represent a multi-stakeholder expert consensus based on the previous literature, but their validation remains a necessary step before they can be widely accepted and put into use. Previous studies have demonstrated that approximations of the ARC-HBR criteria, modified to ‘fit’ with the available datasets, were able to identify high and low bleeding risk patients (Table 1),3–6 but the discriminative accuracy of the complete ARC-HBR criteria has never been evaluated. ARC-HBR validation studies ARC-HBR validation studies In this issue of the European Heart Journal, Corpataux and colleagues present the largest, most comprehensive study so far to evaluate the accuracy of the ARC-HBR criteria to identify post-PCI patients at high vs. low bleeding risk.7 Their analysis leverages a high-quality dataset including 16 850 consecutive all-comer patients encountered in routine clinical practice. They demonstrate that slightly more than a third of all PCI (percutaneous coronary intervention) patients fulfilled the ARC-HBR definition, and that those incurred a three-fold greater risk of BARC 3 or 5 bleeding within 30 days (4.06% vs. 1.18%, respectively), and from 30 days to 1 year (3.96% vs. 1.36%, respectively) after the intervention. Importantly, the 1-year rates of adjudicated BARC 3 or 5 bleeding events among those fulfilling the ARC-HBR criteria was >4%, meeting the intended ARC-HBR threshold. Furthermore, they demonstrate that the risk of BARC 3 or 5 bleeding increased progressively as a function of the number of major or minor criteria present, with roughly a doubling of the risk for every single unit of ARC-HBR score increase. This latter finding cannot be underestimated as it also suggests that a combination of only ‘minor’ risk factors is also associated with a higher risk of bleeding. Another important finding is that patients not meeting the ARC-HBR criteria were at low risk for bleeding. These results were robust and consistent in a number of sensitivity analyses (competing mortality risk modelling, complete follow-up subset, and landmark analysis), and using alternative definitions of bleeding. These findings suggest that we can now use the ARC-HBR criteria for what they were really designed to do: evaluating the comparative efficacy, effectiveness, and/or safety of devices and/or drugs in a standardized HBR population. HBR patients constitute a vulnerable population representing a sizeable proportion of patients referred to cardiac catheterization laboratories in routine clinical practice, but they have been historically excluded from randomized trials evaluating coronary devices. This leaves physicians in a decision conundrum regarding the most appropriate stent platform and which dual antiplatelet therapy (DAPT) duration to use in this subset. More recently, HBR patients have been the intended population of a series of completed and ongoing randomized trials evaluating novel stent designs adapted to their high-risk profile.8–10 These trials specifically excluded patients who were not at HBR to evaluate the safety and efficacy of a variety of novel stent platforms in patients requiring a very short DAPT course (e.g. 30 days) because of a perceived HBR by their physicians. Unfortunately, while sharing many similarities and overlaps, currently available randomized trials that specifically focused on HBR patients have used different sets of eligibility criteria to define what constitutes a true HBR population, which makes comparison across studies and translation of the findings into routine clinical practice difficult. We believe that the ARC-HBR should now be the new standard for those types of trials. Many trials that have tested modified durations of DAPT have already adopted the ARC bleeding definitions,11 and the same should happen for the ARC-HBR criteria. Whether the findings from previous trials that evaluated the safety and efficacy of novel stent designs in heterogeneously defined HBR patients also apply in the ARC-HBR-defined subsets of these trials also needs to be evaluated, especially for pivotal studies such as the LEADERS FREE studies. It is important to recognize that the purpose of the ARC-HBR criteria is not to guide clinical practice to identify patients who might benefit from bleeding prevention strategies involving de-escalation of intensity or duration of antiplatelet therapy (such as aspirin-free antiplatelet regimens or shorter DAPT duration after PCI) unless explicitly studied. This important consideration is reinforced by the study of Corpataux et al., in which the ARC-HBR phenotype was also associated with a higher risk of developing ischaemic events. For example, the 1-year myocardial infarction rates were 6.0% and 3.7% in the ARC-HBR and the non-ARC-HBR subsets, respectively (P < 0.001). Therefore, reducing antiplatelet intensity or duration in patients meeting the ARC-HBR definition would put them at undue risk of subsequent ischaemic events. Tools developed and validated for this purpose, such as the PRECISE-DAPT and the DAPT scores, still remain the best choices to guide clinicians selecting the most appropriate DAPT duration following PCI.12 , 13 The previously mentioned trials focusing on the HBR population may provide an important piece of the bleeding puzzle to further enhance our practice. In this jigsaw of managing bleeding vs. ischaemic outcomes, we need to optimize therapies for those at HBR after PCI as a post-PCI bleeding event confers an adverse prognosis similar to post-PCI myocardial infarction.14 Our goal for antiplatelet therapies should be just a long enough duration to prevent ischaemic events in the acute phase, but short enough to avoid later bleeding. This is a challenging goal that Corpataux and colleagues should be congratulated for having facilitated by validating the best definition for the assessment of patients at high risk of bleeding. Conflict of interest: G.M.-G. reports research grants from the Canadian Institutes of Health Research, and personal fees from Novartis and Servier. E.M.O. reports research grants from Abiomed and Chiesi, and consulting fees from AstraZeneca, Cara Therapeutics, Faculty Connection, Imbria, Impulse Medical, Janssen Pharmaceuticals, Milestone Pharmaceuticals, Xylocor, and Zoll Medical. The opinions expressed in this article are not necessarily those of the Editors of the European Heart Journal or of the European Society of Cardiology.
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 | 0,052 | 0,214 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,003 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,006 |
| Communication savante | 0,014 | 0,013 |
| Science ouverte | 0,006 | 0,003 |
| Intégrité de la recherche | 0,016 | 0,033 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,011 |
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 ».