Chronic Kidney Disease in Primary Care: Outcomes after Five Years in a Prospective Cohort Study
Notice bibliographique
Résumé
BACKGROUND: Chronic kidney disease (CKD) is commonly managed in primary care, but most guidelines have a secondary care perspective emphasizing the risk of end-stage kidney disease (ESKD) and need for renal replacement therapy. In this prospective cohort study, we sought to study in detail the natural history of CKD in primary care to better inform the appropriate emphasis for future guidance. METHODS AND FINDINGS: In this study, 1,741 people with CKD stage 3 were individually recruited from 32 primary care practices in Derbyshire, United Kingdom. Study visits were undertaken at baseline, year 1, and year 5. Binomial logistic regression and Cox proportional hazards models were used to model progression, CKD remission, and all-cause mortality. We used Kidney Disease: Improving Global Outcomes (KDIGO) criteria to define CKD progression and defined CKD remission as the absence of diagnostic criteria (estimated glomerular filtration rate [eGFR] >60 ml/min/1.73 m2 and urine albumin-to-creatinine ratio [uACR] <3 mg/mmol) at any study visit. Participants were predominantly elderly (mean ± standard deviation (SD) age 72.9 ± 9.0 y), with relatively mild reduction in GFR (mean ± SD eGFR 53.5 ± 11.8 mL/min/1,73 m2) and a low prevalence of albuminuria (16.9%). After 5 y, 247 participants (14.2%) had died, most of cardiovascular causes. Only 4 (0.2%) developed ESKD, but 308 (17.7%) evidenced CKD progression by KDIGO criteria. Stable CKD was observed in 593 participants (34.1%), and 336 (19.3%) met the criteria for remission. Remission at baseline and year 1 was associated with a high likelihood of remission at year 5 (odds ratio [OR] = 23.6, 95% CI 16.5-33.9 relative to participants with no remission at baseline and year 1 study visits). Multivariable analyses confirmed eGFR and albuminuria as key risk factors for predicting adverse as well as positive outcomes. Limitations of this study include reliance on GFR estimated using the Modification of Diet in Renal Disease study (MDRD) equation for recruitment (but not subsequent analysis) and a study population that was predominantly elderly and white, implying that the results may not be directly applicable to younger populations of more diverse ethnicity. CONCLUSIONS: Management of CKD in primary care should focus principally on identifying the minority of people at high risk of adverse outcomes, to allow intervention to slow CKD progression and reduce cardiovascular events. Efforts should also be made to identify and reassure the majority who are at low risk of progression to ESKD. Consideration should be given to adopting an age-calibrated definition of CKD to avoid labelling a large group of people with age-related decline in GFR and low associated risk as having CKD.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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; un appel candidat d’une seule tête enseignante, 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 ».