Primary-care physicians' views about the use of home/self blood pressure monitoring: nationwide survey in Hungary
Bibliographic record
Abstract
OBJECTIVE: To obtain unbiased views of primary-care physicians about home blood pressure monitoring (HBPM). METHODS: A mail survey was conducted in a random sample (n = 700) of all Hungarian primary-care physicians (n = 5112). Items in the questionnaire related to the extent and indications for use of HBPM, to the significance attributed to its results, to the methods of its use, and to concerns physicians had with HBPM. RESULTS: Of the 700 questionnaires, 405 (58%) could be analysed. HBPM was popular among the respondents: 60% of them had more then 50 patients on HBPM, 90% of them were recommending its use either 'often' or 'almost all the time', and 75% of them considered the results of HBPM of either 'considerable' or of 'extreme importance'. The most frequent indications for use were white-coat hypertension (97%), assessing 24-h drug effects (87%), improving compliance (82%), suspicion of hypotension (63%), and resistant hypertension (61%). Physicians actively recommended devices with an upper-arm cuff (83%), equipped with a built in memory (63%). Most respondents (67%) had someone in their offices to teach the patient the correct measurement technique. Surprisingly, 65% of the physicians only reviewed the data to obtain a 'general picture' and did not analyse the data. Most of the respondents (78%) encouraged their patients to call their offices, and 90% of them did receive a call. Main concerns with HBPM were the use of non-validated devices (75%), and patient preoccupation with blood pressure (55%). Areas for suggested improvements were the need for patient training facilities (48%), established measurement protocols (44%) and better methods of displaying readings (30%). CONCLUSIONS: We found an unexpected popularity in the use of HBPM among primary-care physicians. In order to fully exploit the benefits of HBPM, the concerns raised (validated devices, patient preoccupation) and areas to be improved upon (patient training, better methods of displaying results) will have to be addressed by researchers, societies and the industry.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".