Improved cardiovascular health following a progressive walking and dietary intervention for type 2 diabetes
Bibliographic record
Abstract
AIM: To examine the impact of two different lifestyle programmes on cardiovascular health and glycaemic control among people with type 2 diabetes. METHODS: A two-phase 24-week randomized trial. During the first phase, participants were to increase daily steps using a pedometer. At week 12, participants were randomly allocated to either an enhanced lifestyle programme (ELP) targeting walking speed or a basic lifestyle programme (BLP) targeting total daily steps. Both programmes focused on increasing the intake of low glycaemic index foods but utilized different goal setting strategies. Clinical measurements were completed at baseline, week 12 and week 24. Principal outcomes were change in resting pulse rate (PR) and glycated haemoglobin A1c (A1c) between week 12 and week 24 compared between groups using analysis of covariance. RESULTS: Forty-one participants [mean +/- s.d. : age = 56.5 +/- 7.2 years, body mass index (BMI) = 32.7 +/- 6.1 kg/m(2)] were randomized. After 12 weeks, we observed an increase in average total daily steps of 1688 (95% confidence interval: 330-3040, [corrected] p = 0.02). Weight, BMI and systolic and diastolic blood pressure improved (p < 0.01 for all). No changes were observed for energy intake. At week 24, those in the ELP had a lower resting PR (71 +/- 12 b.p.m.) compared with those in the BLP (78 +/- 12 b.p.m.) (adjusted p = 0.03), while no group differences for total daily steps or glycaemic control were observed. CONCLUSIONS: Improvements in cardiovascular health can be expected following a pedometer-based lifestyle modification programme that progresses from walking more to walking faster.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".