Impact of the 2021 CKD-EPI eGFR Equation on Kidney Care Referral Criteria in Ontario, Canada: A Population-based Cross-sectional Study
Notice bibliographique
Résumé
Background: In some jurisdictions, individuals become eligible or recommended for referral for different types of kidney care using criteria based on their estimated glomerular filtration rate (eGFR). Historically, GFR was estimated with an equation developed in 2009, which included a Black race term. An updated, race-free equation was developed in 2021. It is unclear how adoption of the 2021 equation will influence the number of individuals meeting referral criteria to receive different types of kidney care. Objective: To develop population-based estimates on how the number of individuals meeting the eGFR-based referral criteria to receive three different types of kidney care (nephrologist consultation, care in a multi-care specialty clinic, kidney transplant evaluation) changes when the 2021 versus 2009 equation is used to calculate eGFR. Design: Population-based, cross-sectional study. Setting: Ontario, Canada's most populous province with 14.2 million residents as of 2021. Less than 5% of Ontario's residents self-identify as being of Black race. Patients: Adults with at least one outpatient serum creatinine measurement in the 2 years prior to December 31, 2021. Measurements: Referral criteria to 3 different types of kidney care: nephrologist consultation, multi-care specialty clinic, and evaluation for a kidney transplant. The eGFR thresholds used to define referral eligibility or recommendation for these kidney health services were based on guidelines from Ontario's provincial renal agency. Methods: The number of individuals meeting referral criteria for the 3 different healthcare services was compared between the 2009 and 2021 equations, restricted to individuals not yet receiving that level of care. As individual-level race data were not available, estimates were repeated, randomly assigning a Black race status to 1%, 5%, and 10% of the population. Results: We had an outpatient serum creatinine measurement available for 1 048 110 adults. Using the 2009 equation, 37 345 individuals met the criteria to be referred to a nephrologist, 10 019 met the criteria to receive care in a multi-care specialty clinic, and 10 178 met the criteria to be referred for kidney transplant evaluation. Corresponding numbers with the 2021 equation (and the percent relative to the 2009 equation) were 26 645 (71.3%), 9009 (89.9%), and 8615 (84.6%) individuals, respectively. These numbers were largely unchanged when Black race was assumed in up to 10% of the population. Limitations: Referral criteria based solely on urine albumin-to-creatinine ratio were not assessed. Self-reported race data were unavailable. Conclusions: For healthcare planning, in regions where a minority of the population is Black, a substantial number of individuals may no longer meet referral criteria for different types of kidney healthcare following adoption of the new 2021 eGFR equation.
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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 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».