Cardiovascular risk factors and their effects on the decision to treat hypertension: evidence based review
Bibliographic record
Abstract
This is the second in a series of five articles Blood pressure, like any physiological variable, is normally distributed in the population. Not surprisingly, expert bodies disagree substantially on the definition of hypertension—of the 27 national hypertension societies represented at the 17th world conference of the Hypertension League Council held in Montreal in 1997, 14 use 140/90 mm Hg to diagnose hypertension and 13 use 160/95 mm Hg.1 #### Summary points There is a continuous, strong, and graded relation between blood pressure and cardiovascular disease, but no clear threshold value separates hypertensive patients who will experience future cardiovascular events from those who will not Risk of cardiovascular disease depends on blood pressure, coexistent risk factors, and whether there is hypertensive damage to target organs Numerous factors definitely increase cardiovascular risk, including age, male sex, family history, raised cholesterol, smoking, diabetes mellitus, obesity, sedentary lifestyle, and left ventricular hypertrophy Models can be used to predict an individual's risk of cardiovascular disease to define the expected benefits and harms of treatment ### Relative risk Most population based studies confirm that hypertension increases an individual's risk of various cardiovascular consequences approximately two to three times (figure). Large population based cohort studies consistently show continuous, strong, and graded relations between blood pressure (particularly systolic pressure) and the subsequent occurrence of various atherosclerotic events. 2 3 The sizes of the relative risks reported in each study depend on the duration of follow up and the definition of hypertension in use.4 These relative risks are consistent across all settings5 and for all patient subgroups, including those with and without known atherosclerotic disease.6 Risk of atherosclerotic disease in people with hypertension Multiple high quality long term cohort studies and randomised clinical trials have shown that the risks from raised blood pressure can be partially reversed. 6 7 Two important …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".