Patient reported QOL and EV‐ICD: Response to letter from Kataoka and Imamura (2024)
Notice bibliographique
Résumé
Our authorship group appreciates the careful consideration of the key issues related to the patient experience posited by Kataoka and Imamura.1 Following publishing of the efficacy and safety data of the extravascular implantable cardioverter defibrillator (EV-ICD),2 our study provided the first available patient reported outcomes (PROs) using both generic and device-specific quality of life (QOL) metrics, and we acknowledge that many questions remain to refine our understanding of the patient experience. Kataoka and Imamura1 queried possible additional group differences in PROs. First, the issue of primary versus secondary prevention indication for implantation (81.8% were primary prevention) and subsequent exposure to ICD shocks was questioned. We compared primary versus secondary indication on the physical and mental subscales of the SF-12 and the composite and subscales of the FPAS, and no differences were found (>0.05). Comparisons between groups with shock and no shock also did not show any differences. Collectively, the existing data does not suggest that device indication or shock exposure impacted PROs. The role of body mass index (BMI) was also raised as a particularly relevant limitation in our study. The average BMI for the full efficacy sample was 28.0 ± 5.6 kg/m2 and our subsamples were 27.8 and 29.3 kg/m2 (completed both SF-12 surveys or completed the FPAS survey, respectively). Kataoka and Imamura question whether there was equitable QOL outcomes by patients with smaller physiques with possible considerations for Asian populations. As we reported,3 BMI scores were significantly different with the smallest BMI group (BMI < 25) reporting a lower mental score on average. Moreover, body image concerns were the highest in the lowest BMI group (BMI < 25) and the youngest (age < 50 years). In contrast, previous reviews with subcutaneous ICDs (S-ICD) in pediatric populations4 has suggested only minor implant modifications may need to be considered, and Vincentini et al. did not find any differences in device acceptance by body habitus.5 The size of the EV-ICD may also be a consideration for shared decision making with respect to the decision of which ICD to implant in which patient. Specifically, the EV-ICD compares favorably in size to the S-ICD (33 vs. 60 cm3, respectively). Device related distress differed between groups and the size of the device may be a factor. The subscale of Device-Related Distress directly queries feelings of disfigurement from the device and this may account for the differences. Finally, the question was raised of selection bias related to the possibility of patients at risk for decreased QOL or patients with smaller body habitus leading to possible avoidance of being enrolled in this study. We do not have any data to refute or accept this limitation as this is the initial sample of patients considering EV-ICDs. However, as noted in the paper,3 we do acknowledge that the process of agreeing to a novel device may induce a degree of positive acceptance bias in patients and in their reporting of outcomes. As a result, we indicated that cautious interpretation of this data is needed until full randomized studies could disentangle these common psychological processes.
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 | 0,003 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,015 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,004 |
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 ».