Performance of clinical prediction models for chronic kidney disease among people with diabetes: external validation using the Canadian Primary Care Sentinel Surveillance Network (CPCSSN).

ABSTRACT:

Background

Several clinical prediction models that predict the risk of chronic kidney disease (CKD) in people with diabetes have been developed; however, these models lack external validation demonstrating accurate predictions in Canadian primary care. We externally validated existing clinical prediction models for CKD in Canadian primary care data, overall and across subgroups defined by sex/gender, age, comorbidities, and neighbourhood-level deprivation.

Methods

We conducted a retrospective cohort study using data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) electronic medical record database (2014-2019). We identified models that use demographic, health behaviour, clinical and diabetes-related characteristics to predict incident CKD based on two r

SUBMITTER: Black JE 

PROVIDER: S-EPMC12604207 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature