Factors associated with subjective knee joint stiffness in people with knee osteoarthritis: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Subjective knee stiffness is a common symptom in patients with knee osteoarthritis treated conservatively. However, the influencing factors or effects of knee joint stiffness are unknown. The aim of this study was to explore the factors associated with subjective knee stiffness in patients with knee osteoarthritis. METHODS: The MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Web of Science, and PEDro databases were searched in November 2021. Prospective or retrospective cohort studies were included. The methodological quality of the selected articles was assessed using the Scottish Intercollegiate Guidelines Network checklist. RESULTS: Twenty out of 1943 screened articles were included in this systematic review. Eighteen and two studies were rated as having acceptable and low quality, respectively. All the included studies measured subjective knee stiffness using the Western Ontario and McMaster Universities Osteoarthritis Index. The main findings were that worse preoperative subjective knee stiffness was associated with worse pain, subjective knee stiffness, and patient satisfaction at 1 year after total knee arthroplasty. In addition, worse subjective knee stiffness was associated with future degenerative changes in the knee joint, such as joint space narrowing and osteophyte growth progression. CONCLUSION: Subjective knee stiffness may be associated with the prognosis after total knee arthroplasty and degenerative changes in the knee joint. Early detection and treatment of knee stiffness could lead to a good prognosis after total knee arthroplasty and prevent the progression of degenerative changes in the knee joint.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".