Prevalence of Chronic Kidney Disease in Type 2 Diabetes: The Canadian REgistry of Chronic Kidney Disease in Diabetes Outcomes (CREDO) Study
Bibliographic record
Abstract
PURPOSE: Chronic kidney disease (CKD) in patients with type 2 diabetes (T2D) is associated with an elevated risk of end-stage kidney disease, cardiovascular disease (CVD), and death. As the breadth of treatment options for CKD in patients with T2D (CKD in T2D) continues to expand, an analysis of the current use of therapies and cardiovascular and kidney outcomes is necessary. The objectives of the study were to assess the prevalence of CKD in T2D among a contemporary cohort of patients, to describe patient characteristics and treatment patterns, and to examine health care practitioner rationale for initiating therapies. METHODS: The study was a retrospective, observational study (module A) with a prospective component (module B). For module A, sociodemographic data, medical history, prescription information, and laboratory investigations for patients seen by an endocrinologist in 2019 were retrieved from the LMC Diabetes Registry. Module B included a subset of patients for health care practitioner surveys to understand rationale for administering angiotensin-converting enzyme inhibitors (ACEis) or angiotensin receptor blockers (ARBs), steroidal mineralocorticoid receptor antagonists (MRAs), sodium-glucose cotransporter 2 inhibitors (SGLT2is), and glucagon-like peptide 1 receptor agonists (GLP-1RAs). Descriptive analyses were conducted. FINDINGS: , and mean glycosylated hemoglobin was 7.6%. Mean diabetes duration was 16 years. The prevalence of CKD in patients with T2D was 47.9%. Common comorbidities were hypertension (76%), dyslipidemia (71%), and obesity (51%). CVD was reported in 22%. The proportion of kidney medications and emerging therapies varied, with 76% of patients using an ACEi or ARB, 48% using an SGLT2i, 30% using a GLP-1RA, and 3% using a steroidal MRA. In module B, physicians identified that ACEis/ARBs, SGLT2is, GLP-1RAs, or steroidal MRAs were administered to primarily treat CKD in 33%, 12%, 0%, and 4% of the patients (n = 500), respectively. IMPLICATIONS: These findings improved our understanding of the current landscape and treatment patterns of CKD inT2D and highlighted the importance of considering treatments that will provide a comprehensive strategy for cardiovascular and kidney risk protection. Despite the high prevalence of CKD and comorbidities reported in a large, Canadian T2D specialist population, ACEis/ARBs, SGLT2is, and GLP-1RAs were underused, especially considering recent clinical trial reports. The relative use of steroidal MRAs was expectedly low. With an immense burden of CKD progression and among patients with T2D, the use of treatments that provide a comprehensive strategy for kidney protection will transform the landscape of CKD in T2D. ClinicalTrials.gov identifier: NCT04445181.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".