Assessing atrial fibrillation ablation priority during COVID-19 -does use of patient questionnaires help in stratification above physician assessment?
Notice bibliographique
Résumé
Abstract Funding Acknowledgements Type of funding sources: None. Introduction Catheter ablation for atrial fibrillation (AF) is largely offered for symptomatic relief. The ORBIT registry has shown that patients with a higher EHRA class and lower quality of life (QoL) scores (AFEQT score <65.7) are more likely to suffer emergency hospital admissions. To help prevent unplanned AF admissions and to best utilise the reduced capacity for elective work during the COVID-19 pandemic, it has become even more important to prioritise the most symptomatic AF patients for ablation. Purpose: To evaluate the accuracy of a subjective symptom-based clinician prioritisation schema compared to objective patient-completed quality of life (QoL) scores. Methods: In July 2020, all elective cases awaiting AF ablation at our institution were categorised by their cardiologist as either category 1 (C1-urgent), category 2 (C2–priority, procedure to be done during the ongoing COVID-19 pandemic) or category 3 (C3–routine, procedure may be delayed until post pandemic). This categorisation was based on review of clinic letters where EHRA AF symptom class or PROMS are not routinely recorded. All patients in C2 and C3 were then posted an AF specific (AFEQT) and a generic (EQ5D) QoL questionnaire to complete. Physicians were blinded to patient responses on the QoL questionnaires. Results: Details of physician prioritisation and completed questionnaires were available for 85 patients (62 ± 10 years, PAF in 61%, males 66%). The 18 patients that had been categorised in C2 (priority) group were found to have a significantly lower AFEQT score (30.4, IQR 17.2-51.9) compared to the 67 patients classed in C3 (routine) group (56.5, IQR 32.1-74.1; p < 0.01)(Figure 1a). EQ5D scores also tended to be lower in the C2 patients (0.7, IQR 0.4-0.8) compared to C3 (0.8, IQR 0.6-0.9; p = 0.056) (Figure 1c). 16 (89%) patients in C2 had significant AF-related impact on QoL (as defined as AFEQT score <65.7) compared to 42 (63%) of patients in C3. However, there was significant overlap between groups (Figure 1b). 4 patients in C3 had unplanned AF related hospital admissions while awaiting ablation, as compared to none in C2. The median AFEQT score of these 4 patients was 23.3, indicating that they were highly symptomatic despite being classified in C3 by their cardiologist. Conclusion : Physician assessments are moderately accurate in prioritising patients awaiting AF ablation. The addition of formal patient-completed QoL assessment such as with AFEQT, helps to identify the most symptomatic patients at risk of emergency hospital admission, and physicians should consider using these as part of routine assessment, especially during the COVID pandemic. Abstract Figure 1
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 | 0,024 | 0,082 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».