Incidence, cardiovascular complications and mortality of hypertension by sex and ethnicity
Bibliographic record
Abstract
OBJECTIVE: To compare ethnic and sex difference in the incidence of newly diagnosed hypertension, and subsequent risk of cardiovascular disease outcomes among South Asian, Chinese and white patients. METHODS: We identified patients with newly diagnosed hypertension aged ≥20 years. Patients were followed for 1-9 years for all-cause mortality and cardiovascular disease with myocardial infarction, heart failure and stroke. Cox proportional hazard models stratified by sex and adjusted for age, median income and co-morbid conditions, were constructed to determine the independent association between ethnicity and the development of the combined cardiovascular endpoint as well as death. RESULTS: There were 39 175 South Asian (49.4% men, 34.4% age ≥65), 49 892 Chinese (48.1% men, 36.7% age ≥65) and 841 277 white (47.9% men, 38.8% age ≥65) patients with newly diagnosed hypertension. Age and sex adjusted incidence of hypertension was highest in South Asian patients and lowest in Chinese patients. Compared with white patients, South Asian and Chinese patients had a lower mortality (adjusted HR (aHR) 0.91 and 0.66) and risk of cardiovascular disease outcomes (aHR 0.94 and 0.49). Compared to men, women had significantly lower mortality (aHR: 0.83 for Chinese, 0.78 for South Asian and 0.77 for white) and cardiovascular disease outcomes (0.72 for Chinese, 0.63 for South Asian and 0.65 for white). CONCLUSIONS: South Asian patients had higher rates of hypertension compared to the other ethnic groups. South Asian and Chinese patients had a lower risk of death and developing cardiovascular outcomes compared to whites. Women with hypertension have a better prognosis than men regardless of ethnicity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".