37 Personalising MET levels for moderate-vigorous physical activity, where public health recommendations can potentially miscategorise patients as only achieving light activity
Bibliographic record
Abstract
<h3>Background</h3> Public health thresholds for light, moderate and vigorous physical activity (MVPA) have been set at 1.5–2.9, 3.0–5.9, and 6.0+ metabolic equivalents (METs), respectively. These targets are programmed into software used in research-grade and commercial activity tracking devices. For many with low exercise tolerance such absolute thresholds have been questioned for miscategorising patients as doing light PA when in fact they have achieved physiologically defined thresholds of MVPA. <h3>Aim</h3> To review existing fitness data of patients with cardiometabolic disease, specifically comparing physiologically defined thresholds for light and MVPA with the recommended absolute Public Health accelerometery thresholds. <h3>Methods</h3> Data from cardiopulmonary exercise tests (CPET) and ActiGraph accelerometry was retrospectively assessed from 34 patients with heart failure (preserved ejection fraction; HFpEF), peripheral artery disease (PAD) and low and high functioning diabetes (LoDiab and middle-aged HiDiab) who enrolled in an exercise programme at the University Hospital Leuven (Belgium). Each patient’s data was then categorised as time spent in light PA and MVPA using the standard public health threshold of ≥3 METs and the BACPR physiological threshold of >40% VO2max <h3>Results</h3> Table 1 summarises the patient demographic, aerobic fitness (Max METs), PA intensity (Light and MVPA) and duration mins/week; mean (+/-1SD). <h3>Conclusion</h3> In this cohort of older low-fitness cardio-vascular-metabolic patients and middle-aged higher-fit patients with diabetes, all were wrongly categorised by Public Health recommendations as only performing MVPA for 18% of their total weekly activity time. In relation to their personalised BACPR physiological MVPA threshold they were all active in MVPA for 100% of their total weekly PA time. When prescribing exercise and recommending PA to patients with lower fitness it is vital to personalise the patients’ MVPA goals in relation to individually assessed thresholds based on their CPET data and not to rely on general Public Health promotion threshold definitions for MVPA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".