A-201 The Impact of Implementing the CKD-EPI 2021 Equation for Calculation of Estimated Glomerular Filtration Rate (eGFR) and the Kidney Failure Risk Equation (KFRE) on a Large Community Laboratory Population
Notice bibliographique
Résumé
Abstract Background Community laboratories in Ontario, Canada have reported estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009 equation without race adjustment since 2020. In 2023, the Canadian Society of Nephrology recommended implementation of the CKD-EPI 2021 equation for eGFR, which does not incorporate a race-based modifier. Community laboratories will also report the 5-year Kidney Failure Risk Equation (KFRE), a risk prediction model to estimate the risk of renal failure in people with chronic kidney disease (CKD) Stages 3 to 5 (eGFR <60 mL/min/1.73m2), which is more accurate than judging by eGFR alone. This study assessed the impact of implementing the CKD-EPI 2021 equation for eGFR and the 5-year KFRE in a large community laboratory population. Methods Laboratory results for serum creatinine and urine albumin to creatinine ratio (ACR), patient sex and age were extracted from Dynacare’s laboratory information system for November 2023. The CKD-EPI 2009 without race adjustment and the CKD-EPI 2021 were calculated. Reclassification of CKD stage using the CKD-EPI 2021 equation was assessed. The 4-variable 5-year KFRE was calculated for patients in CKD Stage 3-5 (eGFR <60 mL/min/1.73m2) when all parameters including, patient age, sex, creatinine and ACR, were available. Results Data was extracted for 242,843 patients. The median age was 61 years old and 47% of the population was female. The calculated median eGFR was 83 and 87 mL/min/1.73m2 when the CKD-EPI 2009 with no race adjustment, and CKD-EPI 2021 equation, respectively, were applied. Linear regression analysis showed a correlation of 0.997 with a slope of 0.990 and y-intercept of 4.513. A total of 13.0% (n=31,679) of patients were reclassified into a less progressive CKD stage when the CKD-EPI 2021 was applied compared to the CKD-EPI 2009 without race adjustment. Notable, was the reclassification of 21.8% (n=6899) of those patients from Stage 3a to 2, i.e. patients no longer have CKD (eGFR >60 mL/min/1.73m2) based on the new calculation. 64.8% (n=20513) of patients were reclassified from Stage 2 to 1, 9.4% (n=2977) were reclassified from Stage 3b to 3a, 3.5% (n=1102) were classified from Stage 4 to 3b, and 0.6% (n=188) were reclassified from Stage 5 to 4. The 5-year KFRE was calculated when creatinine and ACR were included on the same order and the patient was classified as Stage 3 to 5 (n=12,737 patients with eGFR <60 mL/min/1.73m2). The 5-year KFRE showed increasing median risk, 1%, 4%, 27%, 95%, as CKD stage increased from 3a, 3b, 4 and 5, respectively. 1.1% (n=58) of patients in Stage 3a, 43.3% (n=1584) of patients in Stage 3b, 96.6% (n=1994) of patients in Stage 4, and 100% (n=401) of patients in Stage 5 met the KFRE threshold of ≥5% for referral to nephrology. Conclusions Implementation of the CKD-EPI 2021 resulted in reclassification to a less progressive CKD stage. Use of the KFRE as a clinical decision tool will increase patient referral to nephrology. This study provided insight into the impact of the implementation of the CKD-EPI 2021 and KFRE and highlights the underutilization of ACR in a community population.
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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 | 0,012 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».