Cardiovascular disease in Chinese Canadians: a case-mix study from an urban tertiary care cardiology clinic.
Bibliographic record
Abstract
BACKGROUND: Cardiovascular diseases (CVD) are the leading cause of death in Canada. Non-European ethnic groups such as the Chinese constitute an increasingly significant sector of the Canadian population. OBJECTIVE: To compare the frequency and risk factors of CVD in Chinese and white Canadians in a cardiology referral clinic that saw a high number of ethnic Chinese patients and provided equal access to advanced diagnostic facilities. PATIENTS AND METHODS: Clinic charts of patients referred between 1994 and 1999 were reviewed. Patients of Chinese descent were identified by their names. Primary cardiovascular and secondary cardiovascular diagnoses, as well as risk factors for coronary artery disease (CAD), were established. The frequency of disease and risk factors were age-standardized. RESULTS: The sample of patients with CVD consisted of 404 Chinese and 1129 white subjects. Chinese patients were older (median age 65 versus 62 years, P=0.006). CAD, heart failure and peripheral vascular disease were less frequent in Chinese than in white patients. On the other hand, valvular heart disease was more frequent in Chinese patients. Diabetes, smoking and family history of heart disease were less frequent in Chinese subjects, whereas the frequencies of hypertension and hypercholerolemia were similar to those of white patients. In patients who had undergone coronary angiography, the frequency of multivessel CAD was less in Chinese patients (40% versus 56%, P=0.0016). Angina pectoris was a more common manifestation of CAD in Chinese patients, whereas myocardial infarction was more common in people who were white. In patients with heart failure, the median left ventricular ejection fraction was higher in Chinese than in white patients (34% versus 28%, P=0.031). CONCLUSIONS: In patients referred to a cardiology clinic, the diagnosis of CAD and the majority of other CVDs was less frequent in Chinese Canadians than in white Canadians. However, selected modifiable risk factors for CAD, such as hypertension and hypercholesterolemia, were equally frequent. Further research at the population level is warranted to define the characteristics of CVD in Chinese Canadians, and may be useful to the future design of disease management and prevention programs tailored to the needs of this growing ethnic population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 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) | 0.003 | 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".