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Enregistrement W3083459899 · doi:10.1002/joa3.12423

Stature, obesity, and atrial fibrillation: Does appearance matter?

2020· editorial· en· W3083459899 sur OpenAlexaboutno aff
Li‐Wei Lo

Notice bibliographique

RevueJournal of Arrhythmia · 2020
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAtrial Fibrillation Management and Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineAtrial fibrillationInternal medicineCardiologyRisk factorBody mass indexLeft atrial enlargementObesityCohortIncidence (geometry)Sinus rhythm

Résumé

récupéré en direct d'OpenAlex

Observation studies showed that body weight, height, and body mass index (BMI) have significant impacts on the occurrence of atrial fibrillation (AF). It has been firstly in the Manitoba Follow-up Study identified that the obesity as a risk factor for AF. BMI is a surrogate of obesity and it has been found that every 1-unit of increment in BMI is associated with a 4% increase in risk of AF in both men and women.1 In addition, other aspects of body habitus have also been associated with AF. Hanna et al reported the increasing stature portends a higher risk of AF in patients with left ventricular dysfunction.2 A cross-sectional study through generations in Denmark showed the height was consistently a risk factor of incident AF, and a 35%-65% higher risk of AF per 10-cm increase in body height. Since then, numerous observational cohort literatures also demonstrated the similar findings. There are several hypotheses for the predilection of body habitus to incidence of AF. The most commonly accepted factor that reported by studies is the left atrial dimension. Left atrial dimension is a universal predictor of AF and also AF recurrence after rhythm control treatment. Larger left atrial size may harbor multiple reentrant wavelets and thus lead to a sustained AF after a trigger developed in the atrium. Once AF sustained, it could result in further electrical and structural remodeling and contribute to a subsequent left atrial enlargement, which brings to a vicious cycle. In addition to the left atrial size, obesity and higher BMI may also cause high blood pressure, sleep apnea, ventricular diastolic dysfunction, etc. Those factors also predispose to left atrial dilation and mediate the AF promotion. Our recent basic study also revealed that the obesity can contribute to left atrial fibrosis and increase catecholamine spillover, which also related to the effect of autonomic remodeling that prone to cause AF initiation and maintenance.3 In this issue of Journal of Arrhythmia, Johansson and colleagues reported on results from Västerbotten Intervention Programme (VIP) participants in the health examination follow-ups.4 This is a large population-based study cohort with more than 100,100 participants, with a total follow-up of near 1.5 million person-years, across the age between 30 and 60 years old when enrolled. Not surprisingly that height, weight, BMI, and body surface area were positively associated with the risk of incident AF in both genders. The key point from this study is whether the changes of those anthropometric factors affect the risk of incident of AF in men and women. The height is relatively fixed in adult, but body weight can be adjusted individually. Unfortunately, in this study, the risk of incident AF was not significantly associated with the body weight changes (either gain or loss) during the past 10 years among the middle-age men or women. The possible explanations of no difference in AF incidence after gain or loss of body weight might because of the age of the study population. Some studies reported that the weight gain earlier in life (ex: 20-25 years old) affects the incident AF. As the age gets older, more confounding factors may interfere with the incidence of AF (ex: blood pressure, metabolic factors, myocardial ischemia etc). Therefore, the changes might not be that evident if we investigate the mid-life population. Second, the study sampled the body weight and AF diagnosis in a frequency of every 10 years. The fluctuation of the body weight may occur within months or years. If the follow-ups are more frequent, the result might be different. Third, medications or other AF risk factors (valvular heart disease or obstructive lung disease) may influence the result. Therefore, a more rigorous prospective follow-up design is required in the future to ascertain the effect of body weight fluctuation to AF. Antiarrhythmic medications and catheter ablation are important rhythm control strategies for the treatment of symptomatic AF. How about the effects of body weight, height, and BMI to the treatment response? It has been reported in some studies with a limited patient population.5 The AF recurrence after catheter ablation is higher in overweight, obese patients comparing to normal-weight controls. Recent abstract report also demonstrated that the height was independently associated with AF recurrence in patients with paroxysmal AF undergoing catheter ablation, especially in the women above 160 cm.5 Based on those preliminary findings, if we can predict the efficacy of rhythm control strategy from the anthropometric factors in patients with symptomatic AF, modify those factors before application of catheter ablation, we may possibly achieve a better treatment outcome. Therefore, further large population-based designs are required to provide the answer for the anthropometric factors to the efficacy in the AF patients who are going to receive rhythm control treatment. The author declares that he has no conflict of interest.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,855

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,301
Écart entre enseignants0,284 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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