The Prediabetes Detection and Physical Activity Intervention Delivery (PRE-PAID) Project
Bibliographic record
Abstract
Prediabetes is a prevalent condition which is a precursor to type 2 diabetes (T2D) and physical activity is known to counter T2D. Given the potential for alleviating health care expenditures through the prevention or delay of T2D, targeting individuals with prediabetes using physical activity intervention is a critical research question. The aim of this project was to; i) identify persons with prediabetes and thus at high risk for developing T2D, ii) engage individuals with prediabetes in community-based, culturally-preferred physical activity classes led by culturally-matched instructors with the goal of improving glycemic control and iii) investigate how two modes of laboratory-based aerobic exercise intervention (high intensity intervals versus continuous moderate intensity) impact glycemic control in persons with prediabetes. \n \nParticipants were recruited in various ethnic communities known to have high prevalence rates of T2D. Critical blood biomarkers and measures of physical and physiological fitness were assessed at different time points to ascertain the effectiveness of both community-based physical activity classes and two modes of laboratory-based exercise. The results of this project show that the PRE-PAID risk questionnaire coupled with point-of-care testing of glycated hemoglobin (A1C) are an effective tool for identifying persons with prediabetes who are at high risk for T2D. Individuals, who participated in community-based culturally matched physical activity classes, experienced improved glycemic control evidenced by reductions in A1C after 3 and 6 months plus improvements in resting blood pressure, combined hand grip strength and aerobic fitness after 6 months. There were no differences between the laboratory-based aerobic exercise interventions of high intensity intervals vs. continuous moderate intensity for any of the measured outcomes. However, the participants who underwent both laboratory exercise modes experienced significant improvements in glycemic control, beta cell function, waist circumference and aerobic fitness following 3 months of supervised exercise. This research provides evidence for early detection of persons with prediabetes and strategies for improving glycemic control and physical plus physiological fitness in this population. The observed improvements could potentially help prevent or delay the onset of T2D.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".