Blood Pressure Variability Causes Spurious Identification of Hypertension in Clinical Studies: A Computer Simulation Study
Bibliographic record
Abstract
BACKGROUND: The blood pressure (BP) of an individual varies considerably from day to day. Hypertension is commonly identified based on the average of two BPs taken at each of two visits, a practice consistent with current guidelines. We hypothesized that (i) in the setting of high-normal BP ("prehypertension"), this practice results in frequent spurious detection of hypertension, and (ii) that random, spurious detection of hypertension and flawed study design together explain why in the Trial of Preventing Hypertension (TROPHY) study candesartan appeared to suppress the development of hypertension for 2 years after cessation of therapy. METHODS: We used Monte Carlo simulation to quantify spurious detection of hypertension at repeated clinic visits in one million subjects with unchanging usual systolic BPs (SBPs) between 130 and 139 mm Hg and normal BP variability. Criteria for identifying hypertension derived from Rosner and Polk, Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7), and the Trials of Hypertension Prevention (TOHP), TROPHY, and Framingham studies were applied to Canadian Heart Health Survey data. On the basis of these simulations, we created a three-parameter model of Kaplan-Meier curves recorded in the TROPHY study. We used the model to analyze the rates at which hypertension was identified in the TROPHY study. RESULTS: TROPHY criteria spuriously identify hypertension in 76% of subjects over 18 clinic visits. Higher rates of spurious detection of hypertension are seen with JNC 7, TOHP and Framingham study criteria. Even highly conservative criteria falsely identify hypertension in 27% of subjects over 18 visits. Our three-parameter model suggests no postdiscontinuation benefit of candesartan. CONCLUSIONS: When applied over multiple visits, current criteria for detecting hypertension are intolerant of normal BP variation. The use of conservative criteria would reduce spurious identification of hypertension. The apparent long-term beneficial effect of candesartan seen in the TROPHY study can be explained by an inadequate method for detecting hypertension, and flawed study design.
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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 | 0.040 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".