HYDRA: possible determinants of unsatisfactory hypertension control in German primary care patients
Bibliographic record
Abstract
The Hypertension and Diabetes Screening and Awareness (HYDRA) study is a cross-sectional point-prevalence study performed in September 2001; 45,125 primary care attendees were recruited from a representative nationwide sample of 1912 primary care practices in Germany. Around 42% of all patients presenting in these practices had hypertension (WHO definition). In approximately 70% of these patients, hypertension was diagnosed by doctors and 84% of diagnosed patients were on antihypertensive medication, but in less than 30% of treated patients was blood pressure controlled (< 140/90 mmHg). The control rate in all patients presenting with hypertension (including those patients unrecognized) was as low as 19%. The present analysis aimed to find explanations for this unsatisfactory outcome of hypertension control. The main finding was that the rate of diagnosis of hypertension is alarmingly low in young people, probably due to insufficient blood pressure screenings. The data further indicated that doctors still set their target of treatment according to outdated guidelines and that doctors still orientate their treatment primarily with regard to the diastolic pressure. These insights into the causes of unsatisfactory hypertension control may help to direct future educational programmes designed to improve hypertension management specifically to these deficits and thereby to improve control rates.
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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 | 0.005 |
| 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 | 0.001 | 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".