Step Monitoring to improve ARTERial health (SMARTER) through step count prescription in type 2 diabetes and hypertension: trial design and methods
Bibliographic record
Abstract
BACKGROUND: With increasing numbers of type 2 diabetes (DM2) and hypertension patients, there is a pressing need for effective, time-efficient and sustainable strategies to help physicians support their patients to achieve higher physical activity levels. SMARTER will determine whether physician-delivered step count prescriptions reduce arterial stiffness over a one-year period, compared with usual care, in sedentary overweight/obese adults with DM2/hypertension. DESIGN: Randomized, allocation-concealed, assessor-blind, multisite clinical trial. The primary outcome is change in arterial stiffness over one year. The secondary outcomes include changes in physical activity, individual vascular risk factors, medication use, and anthropometric parameters. Assessments are at baseline and one year. METHODS: Participants are sedentary/low active adults with 25 ≤ BMI < 40 kg/m2 followed for DM2/hypertension by a collaborating physician. The active arm uses pedometers to track daily step counts and review logs with their physicians at 3 to 4-month intervals. A written step count prescription is provided at each visit, aiming to increase counts by ≥3,000 steps/day over one year, with an individualized rate increase. The control arm visits physicians at the same frequency and receives advice to engage in physical activity 30-60 minutes/day. SMARTER will enroll 364 individuals to detect a 10 ± 5% difference in arterial stiffness change between arms. Arterial stiffness is assessed noninvasively with carotid femoral pulse wave velocity using applanation tonometry. DISCUSSION: The importance of SMARTER lies not simply in the use of pedometer-based monitoring but also on its integration into a prescription-based intervention delivered by the treating physician. Equally important is the measurement of impact of this approach on a summative indicator of arterial health, arterial stiffness. If effectiveness is demonstrated, this strategy has strong potential for widespread uptake and implementation, given that it is well-aligned with the structure of current clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov (NCT01475201).
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".