Variation in the utilisation of physiotherapy in patients with advanced knee osteoarthritis prior to total knee arthroplasty a systematic review
Bibliographic record
Abstract
INTRODUCTION: Due to demographic changes and increasing knee osteoarthritis (KOA) prevalence, the incidence of total knee arthroplasties (TKA) is constantly rising. Clinical practice guidelines for the treatment of KOA unanimously recommend non-surgical interventions such as exercise, education, and weight reduction in overweight patients. The aim of this systematic review is to determine the proportion of patients with end-stage KOA who attended physiotherapy (PT) prior to TKA. METHODS: A systematic literature search was carried out in the medical databases MEDLINE (via Pubmed), PEDro, and EBSCO in August of 2022. Studies were included regardless of their design, if they reported the proportion of patients with a diagnosis of primary KOA, who participated in PT prior to undergoing TKA. Study quality assessment was performed by two independent authors using the Joanna Briggs Institutes Checklist for studies reporting prevalence data. Results were presented by using a narrative synthesis. RESULTS: Eighteen studies, comprising 579,718 patients, were identified in this systematic review. PT utilisation prior to TKA ranged from 10% to 73% for patients with advanced KOA. Only two studies showed PT utilisation rates of 60% or higher. Female gender, higher income, better socioeconomic status, higher education levels, older age were associated with PT utilisation. Data for other predicting factors was conflicting. DISCUSSION: This review shows substantial variation in the utilisation of PT in patients with end-stage KOA. This is concerning, considering the uniform recommendation from clinical practice guidelines for non-surgical treatments like exercise and education in patients with KOA, which are mostly provided by physiotherapists.
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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 | 0.010 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".