Reduction of mortality following better detection of hypertension and alcohol problems in primary health care in Spain
Bibliographic record
Abstract
Through a simulation study, we estimated the potential effects of better detection of hypertension and improved screening for alcohol problems with subsequent interventions. Results showed that if 50% of Spanish males between 40 and 64 years of age who are currently unaware of their hypertension become aware of their condition and receive the usual treatment, and 50% of these males with hypertension are screened for alcohol and are treated for hazardous drinking or alcohol use disorders, then the percentage of uncontrolled hypertension among men with hypertension decreases from 61.2% to 55.9%, i.e. by 8.6%, with about 1/3 of the effect due to the alcohol intervention. For women, likewise, these interventions would decrease the percentage of women in the same age group with uncontrolled hypertension by 7.4% (about 40% due to the alcohol intervention). The reduction of blood pressure in the population would avoid 412 premature CVD deaths (346 in men, 66 in women) within one year. Therefore, better detection of hypertension and screening for alcohol with subsequent interventions would result in marked reductions of uncontrolled hypertension and CVD mortality.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".