Metabolic and physiological effects of high intensity interval training in patients with knee osteoarthritis: A pilot and feasibility study
Bibliographic record
Abstract
To examine the feasibility of a 6-week high intensity interval training (HIIT) program in patients with symptomatic knee osteoarthritis (OA). A secondary aim was to evaluate the change in whole-body metabolism. In a single-arm intervention, 16 adults (mean age 59.9 yrs; BMI: 29.0 ± 4.3 kg/m2; 77% female) with radiographically diagnosed knee OA (Kellgren-Lawrence [KLG]: 2–4) and moderate to severe pain score (≥6) from the Western Ontario and McMasters Universities Index (WOMAC) enrolled in a 6-week, twice weekly, supervised HIIT cycle ergometry intervention. The primary outcome was feasibility; secondary outcomes included change in peak oxygen consumption (VO2peak), WOMAC, and circulating biomarkers of metabolism. Feasibility was moderate; of the 21 participants screened by phone, 16 were enrolled; 13 completed pre- and post-testing. The average adherence rate (sessions completed/available) was >96%. VO2peak was significantly improved (mean ± SD: 2.6 ± 3.0 mL/min/kg; 95% CI [0.70–4.56]). Significant improvements in WOMAC (mean ± SD: −8.7 ± 12.5; CI: [18.9 to −2.80]), pain [-5.15 to −1.01], and function [-12.9 to −0.98] resulted. There was a significant reduction in concentrations of amino acids: methionine, phenylalanine, and tyrosine (p < 0.02 for all), with trends towards lower concentrations of serine (p = 0.08; [-20.66-1.18]) and greater aspartate/asparagine (p = 0.06; [-1.99-65.73].). Post-training acylcarnitine concentrations were reduced with training. In this cohort of overweight adults with symptomatic knee OA, 6-weeks of HIIT cycling showed excellent rates of retention and adherence with no adverse events, improved cardiorespiratory fitness and OA symptoms, in concert with metabolic alterations indicative of improved skeletal muscle energetics. clinicaltrials.gov: NCT03039452.
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".