[LB.03.02] HOME BLOOD PRESSURE MEASUREMENT WITH HY-RESULT SYSTEM
Bibliographic record
Abstract
Objective: Hy-Result is a free web-based rule management software designed to help patients to comply with the home blood pressure measurement (HBPM) protocol and to self-interpret their results. The validation study was published in 2016. Here, we compare the opinion on the system of two groups of users: Patients seen in ESH Excellence Centres and Web Users. Design and method: We administered a web-based questionnaire with 24 independent closed questions to patients using the Hy-Result system. The same questionnaire was openly available through the system. A total of 194 anonymous subjects completed the questionnaire: 87 patients from 2 ESH centers (Paris and Brussels) and 107 Web Users. Results: Eighty percent of respondents were between 35 and 75-years old in both groups but ESH Centre patients tended to be younger (p = 0.04). Eighty six percent of the ESH Centre group received antihypertensive drugs, 48% of the subjects in the Web Users group (p < 0.001).In the subgroup of 39 persons (36% of the total) who transmitted the Hy-Result report to their general practitioner, 92% reported that their doctor had considered the report useful (7% of their doctors did not look at the report and 1% advised against the use of the software). Almost all respondents (99% in the ESH Centers group and 97% of the Web Users) trust the software. The high rate of confidence in the web users group was unexpected because we did not know if a medical doctor recommended the Hy-Result system or not. In the future, it will be necessary to study to what extent health professionals are ready to integrate this tool into their practice. Conclusions: The Hy-Result system is well accepted by the majority of responders to this survey, both ESH Patients and Web Users.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.374 | 0.304 |
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".