The left atrium: An overlooked prognostic tool
Notice bibliographique
Résumé
The increasing incidence and prevalence of chronic kidney disease (CKD) is associated with a parallel rise in atrial fibrillation (AF). The main reason for this epidemiological coupling is an increasing elderly population and shared risk factors, such as diabetes mellitus, hypertension and heart failure.1 However, more and more data are becoming available to suggest that both diseases likely share underlying pathophysiological mechanisms (Figure 1).2–4 Chronic kidney disease (CKD) and atrial fibrillation (AF) share many collective risk factors. Currently, growing evidence suggests that underlying pathophysiological mechanisms cause vascular disease that can give rise to atrial cardiomyopathy and vascular events.2 We hypothesise that AF, just as CKD, is a manifestation and marker of vascular disease burden. Monitoring of left atrium (LA) function and form may provide prognostic information and allow earlier detection of LA involvement in individuals with CKD. COPD: chronic obstructive pulmonary disease; HFpEF: heart failure with preserved ejection fraction; HFrEF: heart failure with reduced ejection fraction; OSAS: obstructive sleep apnoea syndrome. Cardiovascular events, rather than renal failure itself, are the most common cause of mortality and morbidity in patients with CKD. The presence of both CKD and AF exacerbates vascular-related adverse events (including stroke, systemic thromboembolism, heart failure and myocardial infarction).5 Unsurprisingly, structural and functional cardiac abnormalities are already present in CKD patients without overt cardiac disease. Diastolic dysfunction has a prevalence of 29% in patients with non-dialysis CKD.6 This may be one of the triggers of left atrial (LA) enlargement, which is an established predictive marker of AF and cardiovascular events.7 In this issue of the European Journal of Preventive Cardiology, Nakanishi et al. used real time 3-D echocardiography to study the association between CKD and LA volume and function in 358 patients from a community-based cohort study without overt cardiac disease. CKD (estimated glomerular filtration rate (eGFR)) <60 ml/min/1.73 m2) was present in 69 patients (19%). These were patients early in the disease process: kidney function was relatively preserved and LA volumes were within the normal range. However, patients with CKD (mean eGFR 50 ± 9 ml/min/1.73 m2) had a higher prevalence of diastolic dysfunction and reduced LA emptying fraction (42.7 ± 11.4 versus 47.8 ± 11.5%). Multivariate regression analysis showed that eGFR was associated with LA emptying fraction, independent of age, left ventricular mass index and diastolic dysfunction, but not with LA volume. Whereas LA maximum volume remained unchanged between the groups, early CKD was independently associated with impaired LA function. LA enlargement may eventually develop as renal dysfunction progresses.8 The authors are to be congratulated on this elegant and timely study. However, the results must be interpreted in light of limitations that are inherent to its design and small study population. Furthermore, patients with CKD were older, more often had hypertension, and received different pharmacological treatment, possibly influencing LA parameters. Additionally, information on aetiology and duration of CKD, and outcome parameters such as AF occurrence, are missing. Nevertheless, the observations are in line with data from Kadappu et al. who showed that patients with CKD have altered LA function and LA enlargement compared with risk factor-matched control subjects and healthy subjects.9 Indeed, AF often occurs in the setting of CKD. In the Atherosclerosis Risk in Communities study, new-onset AF was increasingly prevalent as GFR declined. Patients with GFR of 60–89, 30–59 and 15–29 ml/min/1.73 m2 had, compared to patients with GFR ≥ 90 ml/min/1.73 m2, hazard ratios (HRs) of 1.3, 1.6 and 3.2, respectively, for developing AF during a follow-up of 10 years.10 In 8265 individuals included in the Prevention of Renal and Vascular End-stage Disease (PREVEND) study, microalbuminuria, as a measure of renal vascular dysfunction, was related to incidence of new-onset AF during a follow-up of almost 10 years, independent of cardiovascular risk factors.11 Likewise, patients with AF have a higher incidence of CKD. In a UK cohort of 4.3 million adults, linked electronic health records were used to examine time to diagnosis of AF and associated vascular events. The presence of AF at baseline was associated with the occurrence of vascular events including CKD, especially in those not treated with antithrombotic therapy (HR 1.42, confidence interval 1.31–1.54).12 In a meta-analysis consisting of more than 9.6 million patients from 104 studies, AF was present in 587,867 patients. These patients also showed a higher risk of having CKD (HR 1.64, confidence interval 1.41–1.91).13 These studies, and the observations by Nakanishi et al. in this issue, contribute to the growing evidence that indicates that AF may be a marker of vascular disease rather than the mechanism. Structural, architectural, contractile or electrophysiological changes induce atrial remodelling, i.e. atrial cardiomyopathy. This is regarded as an important risk marker for ischaemic stroke, death and vascular events, including CKD, independent of AF.2 Atrial cardiomyopathy likely results from progressive atrial remodelling due to aging, stretch from pressure and volume overload, inflammation, endothelial dysfunction and oxidative stress.2 This causes atrial fibrosis leading to contractile dysfunction, dilation and an arrhythmogenic and thrombogenic substrate.2–4 Atrial cardiomyopathy may mirror vascular disease progression and consequently may reveal the risk of vascular events including CKD and AF occurrence. As a result of the ageing population, the prevalence of AF with concurrent CKD will increase. Imaging techniques, including echocardiography, may provide prognostic information and allow detection of LA involvement in individuals with CKD. Once initial abnormalities in LA function, or subsequent increases in size are identified, physicians might be more vigilant in initiating strategies to prevent progression and cardiovascular events, including stroke.2,3 However, the prognostic role of the LA in risk prediction and stratification requires prospective testing. This knowledge is paramount to optimise the benefits of personalised treatment and minimise potential harm in this high-risk and growing population. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors acknowledge the support from the Netherlands Cardiovascular Research Initiative: an initiative with support of the Dutch Heart Foundation, CVON 2014-9: Reappraisal of Atrial Fibrillation: interaction between hyperCoagulability, Electrical remodeling, and Vascular destabilisation in the progression of AF (RACE V).
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 | 0,001 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,012 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,002 |
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 ».