THE CLINICAL EPIDEMIOLOGY OF CARDIOVASCULAR DISEASES IN CHRONIC KIDNEY DISEASE: Clinical Epidemiology of Cardiovascular Disease in Chronic Kidney Disease Prior to Dialysis
Notice bibliographique
Résumé
Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in patients with end-stage renal disease (ESRD). Both in dialysis and in transplant patients, CVD remains the leading cause of death. There is accumulating evidence that the increase in CVD burden is present in patients prior to dialysis, due to both conventional risk factors as well as those specific to kidney disease. Of importance is that even in patients with mild kidney disease, the risk of cardiovascular events and death is increased relative to patients without evidence of kidney disease. The new classification system proposed by the National Kidney Foundation as part of the Dialysis Outcomes Quality Initiative (DOQI) process describes the five stages of kidney disease, as well as those complications associated with chronic kidney disease (CKD), in particular cardiovascular risk factors and disease. Patients with kidney disease are deemed to be at highest cardiovascular risk. CVD, defined as the presence of either congestive heart failure (CHF), ischemic heart disease (IHD), or left ventricular hypertrophy (LVH), is prevalent in cohorts with established CKD (8-40%). The prevalence of hypertension, a major risk factor for coronary artery disease (CAD) and LVH is high in patients with CKD (87-90%). At least 35% of patients with CKD have evidence of an ischemic event (myocardial infarction or angina) at the time of presentation to a nephrologist. The prevalence of LVH increases at each stage of CKD, reaching 75% at the time of dialysis initiation, and the modifiable risk factors for LVH include anemia and systolic blood pressure, which are also worse at each stage of kidney disease. Even under the care of nephrologists, a change in cardiac status (worsening of heart failure or anginal symptoms) occurs in 20% of patients. The presence of CVD predicts a faster decline of kidney function and the need for dialysis, after controlling for all other factors including glomerular filtration rate (GFR), age, and the presence of LVH. This article describes the new classification system for staging of CKD, defines and describes CVD in CKD, and reviews the evidence and its limitations with respect to the current understanding of CKD and CVD. Specifically, methodologic issues related to survival and referral bias limit our current understanding of the complex interaction of conventional and nonconventional kidney disease-specific risk factors. We identify the importance of well-conducted studies of patient groups with and without CVD, with and without CKD, in order to better understand the complex physiology so that treatment strategies can be appropriately applied.
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 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 | 0,032 | 0,114 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,025 | 0,032 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».