Modulation of Physical Activity to Optimize Pain Sensation following an Intra-Articular Corticosteroid Injection in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Intra-articular corticosteroid injection is often used to relieve pain caused by knee osteoarthritis. This study aims to assess the impact after an intra-articular corticosteroid injection treatment on objective and subjective measurement of physical function in knee osteoarthritis patients. METHODS: Fourteen patients with unilateral knee osteoarthritis participated in this open-label uncontrolled trial. The intra-articular corticosteroid injection was given at the end of the second week. Physical activity was objectively measured by an accelerometer worn by the participants for eight weeks. Symptoms, quality of life and spatiotemporal parameters of gait were assessed every two weeks. RESULTS: From the injection until six weeks later, pain and stiffness were reduced by approximately 60%. Patients' daily physical activity time was significantly improved after injection: participation in light and moderate physical activities increased during four and two weeks, respectively. CONCLUSIONS: The beneficial effects after the intra-articular corticosteroid injection are visible in the duration and intensity of the knee osteoarthritis patients' daily physical activity. However, these effects declined gradually two weeks after injection. Modulating the intensity and duration of physical activity would allow patients to optimize pain sensation over a longer period following an intra-articular corticosteroid injection. Trial Registration. This trial was registered with ClinicalTrials: NCT02049879.
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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) | 0.000 | 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 | 0.000 |
| 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".