Characteristics of Adults With Type 2 Diabetes Mellitus by Category of Chronic Kidney Disease and Presence of Cardiovascular Disease in Alberta Canada: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with an excess risk of cardiovascular disease (CVD) and chronic kidney disease (CKD). Although CVD, CKD, and use of antihyperglycemic treatments are all key drivers of the costs and consequences experienced by people with diabetes, no recent Canadian data describe these characteristics among adults with diabetes. OBJECTIVE: To describe prevalence of CVD, CKD, and use of antihyperglycemic treatments among adults with diabetes. DESIGN: Retrospective population-based, cross-sectional study. SETTING: Alberta, Canada. PATIENTS: All adults with T2DM as of March 31, 2017. MEASUREMENTS: We described the demographic and clinical characteristics by CKD stage and CVD status and type. CKD stage was categorized according to international guidelines and based on estimated glomerular filtration rate (eGFR) and severity of albuminuria. METHODS: Clinical and demographic characteristics were defined using provincial administrative data; medication use was based on data from the provincial drug plan. Additional analyses examined subgroups based on demographic characteristics, clinical characteristics, and medication use. RESULTS: ; 11.1%, 5.6%, and 2.9% had CKD stages 3a, 3b, and 4/5, respectively. The overall prevalence of CVD (prior myocardial infarction, stroke/transient ischemic attack, or peripheral artery disease) was 22.5%; prevalence increased in parallel with the presence of CKD: 14.4%, 28.8%, 35.7%, 44.3%, and 50.9% for stages 1, 2, 3a, 3b, and 4/5, respectively. Prescriptions for antihyperglycemic medications were more common in people with CKD as compared with those without. However, the use of all antihyperglycemic medications except insulin and meglitinide was progressively lower in the presence of more severe CKD. LIMITATIONS: The study is based on administrative data; therefore, the findings could be influenced by measurement error (eg, accuracy of diagnostic and procedural codes and prescription drug codes used). CONCLUSIONS: These findings will be useful to policy makers seeking to understand the burden of diabetes-related kidney disease as well as the potential budget implications and potential clinical benefits of expanded use of antihyperglycemic use in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".