Objective: To develop and validate a model for predicting 5-year eGFR-loss in type 2 diabetes mellitus (T2DM) patients with preserved renal function at baseline.Research design and methods: A cohort of 504.532 T2DM outpatients participating to the Medical Associations of Diabetologists (AMD) Annals Initiative was splitted into the Learning and Validation cohorts, in which the predictive model was respectively developed and validated. A multivariate Cox proportional hazard regression model including all baseline characteristics was performed to identify predictors of eGFR-loss. A weight derived from regression coefficients was assigned to each variable and the overall sum of weights determined the 0 to 8risk score.Results: A set of demographic, clinical and laboratory parameters entered the final model. The eGFR-loss score showed a good performance in the Validation cohort. Increasing score values progressively identified a higher risk of GFR loss: a score >= 8 was associated with a HR of 13.48 (12.96-14.01) in the Learning and a HR of 13.45 (12.93-13.99) in the Validation cohort. The 5 years-probability of developing the study outcome was 55.9% higher in subjects with a score >= 8.Conclusions: In the large AMD Annals Initiative cohort, we developed and validated an eGFR-loss prediction model to identify T2DM patients at risk of developing clinically meaningful renal complications within a 5-years time frame.
A prediction model to assess the risk of egfr loss in patients with type 2 diabetes and preserved kidney function: The amd annals initiative
Fioretto, P;
2022
Abstract
Objective: To develop and validate a model for predicting 5-year eGFR-loss in type 2 diabetes mellitus (T2DM) patients with preserved renal function at baseline.Research design and methods: A cohort of 504.532 T2DM outpatients participating to the Medical Associations of Diabetologists (AMD) Annals Initiative was splitted into the Learning and Validation cohorts, in which the predictive model was respectively developed and validated. A multivariate Cox proportional hazard regression model including all baseline characteristics was performed to identify predictors of eGFR-loss. A weight derived from regression coefficients was assigned to each variable and the overall sum of weights determined the 0 to 8risk score.Results: A set of demographic, clinical and laboratory parameters entered the final model. The eGFR-loss score showed a good performance in the Validation cohort. Increasing score values progressively identified a higher risk of GFR loss: a score >= 8 was associated with a HR of 13.48 (12.96-14.01) in the Learning and a HR of 13.45 (12.93-13.99) in the Validation cohort. The 5 years-probability of developing the study outcome was 55.9% higher in subjects with a score >= 8.Conclusions: In the large AMD Annals Initiative cohort, we developed and validated an eGFR-loss prediction model to identify T2DM patients at risk of developing clinically meaningful renal complications within a 5-years time frame.Pubblicazioni consigliate
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