Abstract 096: Comparing Strategies to Improve Systolic Blood Pressure Over 10 Years: A Simulation Study Using the Blood Pressure Control Model
Bibliographic record
Abstract
Background: Uncontrolled hypertension increases patients’ risk for cardiovascular and kidney disease. This study compared strategies to improve systolic blood pressure (SBP) among 1000 simulated patients with uncontrolled hypertension (SBP >=140 mmHg) from the National Health and Nutrition Examination Survey (NHANES). Methods: The Blood Pressure Control Model (BPCM) is a microsimulation, health state transition model that predicts the weekly SBP of patients receiving usual care. In the BPCM, patient SBPs are estimated using office visit frequency, measured SBP accuracy and variability, probability of treatment intensification with uncontrolled SBP, effect of antihypertensive medications, and adherence. BPCM inputs are derived from national survey data, meta-analyses, and other published literature. The effects of usual care on SBP were compared to 10% and 50% increases in global strategies for SBP control (i.e., visit frequency, treatment intensification, and/or adherence) over 10 years. SBP outcomes were validated against published literature values of 44-46% prior to implementation (i.e., usual care) and 74-80% 8-10 years after implementation of aggressive hypertension management programs in large health systems. Results: In the simulated NHANES population, the mean (SD) age was 61.1 (14.6), 52% were male, and mean baseline SBP was 153.2 (13.6) mmHg. Under usual care, the BPCM estimated a mean SBP of 140.1 (16.4) mmHg and 49% of patients achieving SBP <140 mmHg after 10 years. Compared to usual care, 50% improvements in global strategies resulted in more rapid reductions in SBP and earlier achievement of SBP control. Simultaneously improving all global strategies by 50% resulted in an estimated mean SBP of 132.4 (15.5) mmHg with 71% achieving control after 10 years. Conclusions: Usual care and intervention BPCM predictions are consistent with hypertension control rates observed in contemporary national surveys and the observed results of recent systematic hypertension control improvement programs. These results show the BPCM may be used by health system planners to project the impact of implementing hypertension control strategies.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".