Polygenic risk scores for risk prediction of atrial fibrillation in cardiac surgery patients: Insights from the prospective, multinational VISION cardiac surgery cohort
Notice bibliographique
Résumé
Abstract Background New-onset postoperative atrial fibrillation (POAF) complicates 1 in 3 cardiac surgeries and is associated with morbidity, mortality and clinical AF in long-term follow-up. Clinical risk scores have modest performance for predicting POAF. Polygenic risk scores are derived from the summation of up to millions of genetic variants and have shown good predictive ability for incident AF in the community. The ability of polygenic risk scores to predict POAF and subsequent recurrence of clinical AF in cardiac surgery patients is unclear. Methods We performed a prospective cohort study of patients from 4 regions (Canada, Hong Kong, Malaysia, United Kingdom) without a pre-operative history of atrial fibrillation (AF) who underwent cardiac surgery and were followed for 1 year. From pre-operative blood samples, we extracted DNA and calculated each participant’s polygenic risk score for AF using a penalized regression method (lassosum) to combine the effects of 5,000,621 genetic variants, weighted by their association with AF status from a previous genome-wide association study by Miyazawa (Nature Genetics, 2023). We estimated the association of this polygenic risk score for AF with the incidence of new-onset POAF using analyses adjusted for genetic ancestry. We assessed the ability of the polygenic risk score to predict POAF when added to common clinical risk scores. As a secondary objective, among patients who developed POAF, we estimated the association of the polygenic risk score with AF recurrence in follow-up beyond 30 post-operative days. Results Among 3031 patients (63.5% isolated coronary artery bypass grafting), 1282 patients (42.3%) developed new-onset POAF. The polygenic risk score for AF was strongly associated with the risk for POAF (odds ratio 1.3 per standard deviation increase in polygenic risk score [95% CI 1.2-1.4]). The 10% of participants with highest polygenic risk had a risk of POAF of 50.5% as compared to 41.4% for the bottom 90% (odds ratio 1.4 [95% CI 1.1-1.8]). When the polygenic risk score was added to the clinical risk scores, it improved the model fit for all scores, significantly improved the C-statistic for the CHA2DS2-VASc, POAF and HATCH Scores and improved measures of risk classification for all scores (Table). Follow-up data on AF status beyond 30 days were available for 902 patients; 71 patients (7.9%) had AF recurrence detected beyond 30 days post-operatively. The polygenic risk score was not significantly associated with a higher risk for AF recurrence (odds ratio, 1.1 per standard deviation increase in polygenic risk score [95% CI, 0.9-1.5]). Conclusions A higher polygenic risk score for AF is associated with the development of new-onset POAF following cardiac surgery and improves risk classification compared with clinical risk scores alone. However, this study failed to demonstrate an association of the polygenic risk score with AF recurrence in patients who develop POAF.
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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 | 0,011 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 ».