Prevalence, Awareness, and Management of CKD and Cardiovascular Risk Factors in Publicly Funded Health Care
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: It is uncertain how many patients with CKD and cardiovascular risk factors in publicly funded universal health care systems are aware of their disease and how to achieve their treatment targets. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The CARTaGENE study evaluated BP, lipid, and diabetes profiles as well as corresponding treatments in 20,004 random individuals between 40 and 69 years of age. Participants had free access to health care and were recruited from four regions within the province of Quebec, Canada in 2009 and 2010. RESULTS: CKD (Chronic Kidney Disease Epidemiology Collaboration equation; <60 ml/min per 1.73 m(2)) was present in 4.0% of the respondents, and hypertension, diabetes, and hypercholesterolemia were reported by 25%, 7.4%, and 28% of participants, respectively. Self-awareness was low: 8% for CKD, 73% for diabetes, and 45% for hypercholesterolemia. Overall, 31% of patients with hypertension did not meet BP goals, and many received fewer antihypertensive drugs than appropriately controlled individuals; 41% of patients with diabetes failed to meet treatment targets. Among those patients with a moderate or high Framingham risk score, 53% of patients had LDL levels above the recommended levels, and many patients were not receiving a statin. Physician checkups were not associated with greater awareness but did increase the achievement of targets. CONCLUSION: In this population with access to publicly funded health care, CKD and cardiovascular risk factors are common, and self-awareness of these conditions is low. Recommended targets were frequently not achieved, and treatments were less intensive in those patients who failed to reach goals. New strategies to enhance public awareness and reach guideline targets should be developed.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".