Risk of stroke and coronary heart disease among various levels of blood pressure in diabetic and nondiabetic Chinese patients
Bibliographic record
Abstract
OBJECTIVE: To compare the risk of stroke and coronary heart disease (CHD) among various blood pressure (BP) levels in diabetic and people without diabetes Chinese patients. METHODS: This cross-sectional study was part of Prospective Urban Rural Epidemiology China study. Patients aged 35 to70 years were recruited from 12 provinces of China between 2005 and 2009. The participants were classified into three groups: hypertension (HTN), high normal BP, and normal BP, and also into SBP and DBP quintiles. RESULTS: A total of 42 959 patients were analyzed with 38 975 (90.7% of total population) people without diabetes and 3984 (9.3% of total population) diabetic patients. Among diabetic patients, the HTN group was associated with an increased risk of stroke (odds ratio, 3.03; 95% confidence interval, 1.47-6.25) and CHD (odds ratio, 2.21; 95% confidence interval, 1.45-3.38), when compared with normal BP group. Similar results were drawn in nondiabetic patients. However, no significant difference in risk of stroke or CHD was found between high normal BP and normal BP groups in either diabetic or nondiabetic patients. Risk of CHD and stroke increased significantly when SBP was above 125 mmHg or DBP above 72 mmHg in people without diabetes, whereas this trend was attenuated in diabetic patients. CONCLUSION: HTN was associated with a two-fold increased risk of CHD and a three-fold increased risk of stroke compared with normotension irrespective of diabetes status. For diabetic patients with HTN, a more comprehensive method is essential for assessing cardiovascular risk.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".