The Effect of a Lower Body Positive Pressure Supported Treadmill Exercise Regime on Systemic Biomarkers of Inflammation and Cartilage Degradation in Individuals with Knee Osteoarthritis: A Pilot Study
Bibliographic record
Abstract
Background: Knee osteoarthritis (OA) has been linked to a chronic low-grade inflammatory response and altered metabolic activity of articular cartilage. Objective: The purpose of this investigation was to evaluate the effectiveness of a 12-week (3 times/week) lower body positive pressure (LBPP) treadmill walking regime on knee pain and systemic biomarkers of inflammation and cartilage degradation. Methods: Sixteen overweight (BMI > 25 kg/m2) knee OA patients were randomized to a LBPP treadmill walking exercise group (N = 7) or non-exercise control group (N = 9). Baseline and 12-week follow-up assessments evaluated the following dependent variables: acute knee pain during full weight bearing treadmill walking; inflammatory biomarkers (C-reactive protein, interleukin-1β, interleukin-6, s100A8/A9, and tumor necrosis factor-α), and catabolic metabolism of articular cartilage (sCOMP). Results: Knee pain at baseline and follow-up remained unchanged for the non-exercise control group (P > 0.05). However, knee pain for the LBPP exercise group was significantly decreased at follow-up (P ≤ 0.05). No differences in the biomarkers of inflammation and cartilage degradation were observed for between and within group comparisons (all P > 0.05). Conclusions: Data suggested that the LBPP supported walking regime could be effectively used to promote regular weight bearing exercise without exacerbation of knee joint pain and did not increase levels of systemic inflammation or catabolic activity of articular cartilage in overweight knee OA patients. This pilot investigation offers important insight regarding the potential role that the LBPP technology could play in facilitating investigations examining the disease modifying effect of exercise on knee OA pathogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".