Misclassification of Blood Pressure by Usual Measurement in Ambulatory Physician Practices
Bibliographic record
Abstract
BACKGROUND: Standardized measurement of blood pressure (BP) is widely recommended but rarely followed in usual clinical practice. METHODS: We compared the classification of hypertension status of 107 patients referred by family physicians for ambulatory BP monitoring (ABPM) and with elevated clinic BP when assessed by usual clinical office measurement, a trained hypertension research nurse using a standardized measurement protocol, or an ambulatory BP monitor. RESULTS: Usual clinic readings resulted in higher BP readings than those obtained by the research nurse: mean (95% confidence interval [CI]), 10.8 (8.0 to 13.6)/4.9 (2.9 to 6.9) mm Hg, the daytime ambulatory BP 7.7 (5.1 to 10.3)/5.1 (3.0 to 7.1), and the 24-h ambulatory BP 12.1 (9.6 to 14.6)/8.9 (6.9 to 10.9). The interpretation of whether the patient had a hypertensive versus normotensive reading in the usual clinic setting differed in 42% of patients relative to standardized nurse readings. CONCLUSIONS: Following standardized technique is important for correct classification of the BP status of patients. Use of usual or casual technique results in higher readings than standardized or ambulatory BP readings. This study indicates that significant improvement in the assessment of BP is required for diagnosis and optimal management of hypertension. Consideration strongly needs to be given to the development of alternative methods of assessing BP in clinical practice.
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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 | 0.017 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".