White-coat hypertension: management and adherence to guidelines by European and Canadian GPs. A cross-sectional clinical vignette study
Bibliographic record
Abstract
Background White-coat hypertension (WCH) is also referred to as 'isolated clinic hypertension'. While it is a frequently encountered phenomenon, WCH is not systematically evoked, and its management remains unclear due to the contradictory guidelines provided by professional societies. Aim To examine WCH management by GPs in Europe and Canada. Design & setting A clinical vignette of a possible case of WCH was created from the literature, and the responses of GPs to WCH-specific questions in a cross-sectional electronic questionnaire were compared. Method Complete electronic questionnaire responses from Europe and Canada were systematically analysed. Results Among 770 eligible questionnaires (useful response rate: 10.6%), 43.5% were from France, 19.2% from Belgium, 7.8% from England, 19.5% from Switzerland, and 10.0% from Canada. Based on the clinical information provided in the vignette, GPs overall diagnosed hypertension and WCH equally (50.7% versus 49.3%, respectively). Canadian GPs suggested hypertension more frequently than European GPs in general (64.2% versus 46.1%, P<10–4), and more frequently used ambulatory blood pressure monitoring ([ABPM] 42.3% versus 26.1%, P = 0.01). In both groups of GPs, WCH was managed similarly (no treatment, 100% versus 97.3%, P = 0.39). Generally, the GPs all followed WCH patients for 3–6 months (51.3% versus 66.2%, P = 0.1), and they were not aware of the WCH guidelines (47.3% versus 52.1%, P = 0.54). Conclusion Although WCH guidelines are different, WCH management by GPs is very similar except for diagnosis. Homogeneity in WCH guidelines is required and should be systematically implemented in hypertension guidelines to avoid inappropriate management of the condition.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".