Notice bibliographique
Résumé
SIR—We thank Drs Khan and Myers for their comments relating to our paper [1]. We reported that older patients with atrial fibrillation (AF) in acute hospital care were less likely to receive warfarin if they fulfilled frailty criteria. Frailty was defined using a reported version of the Edmonton Frail Scale, a validated scale for use by non-clinicians that assesses cognition, health attitudes and mood, medication use, nutrition, continence, burden of medical illness, social support and functional independence [2]. Furthermore, our study found a significant difference in the rates of embolic stroke and death between patients deemed frail and those deemed non-frail. The study also found that frail patients were more likely to have a haemorrhagic event 3 and 6 months post-discharge. Frailty was associated with age but not directly related to age. In fact frailty was better correlated with disability and co-morbidity than with age. Our findings support the view of Drs Khan and Myers that age alone should not (and does not) determine prescribing of antithrombotic medication for older patients with AF. A previous interventional study in the same hospital acknowledged this issue by specifically excluding age per se from the decision-making process, and instead focussing on medical, functional, cognitive, iatrogenic and social factors affecting the use of antithrombotics [3]. The present study follows from this in evaluating additional factors that may help determine the optimum treatment for older patients with AF. We found that frailty may be a useful risk stratification tool for such patients. Most of the factors that Drs Khan and Myers advocate considering in anticoagulation of older patients would be assessed using the frailty tool that was applied in our study. Differences in the event rates observed between our studies may relate to the populations studied: our participants all had AF, were recruited from acute care wards, were followed over 6 months and were not all anticoagulated; while their participants had a range of conditions, were followed for an average of 3.78 years in the community and were all anticoagulated. It is possible that there was a higher prevalence of frailty in our study (64% of participants) than in the population reported by Drs Khan and Myers, which may contribute to the higher rates of adverse events we observed. Risk stratification tools such as frailty are valuable when prescribing for older patients, who have wide inter-individual variability, and potentially have much to gain from medication as well as a high risk of adverse drug reactions. None declared.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».