Growing Trends in Scientific Publication in Physiotherapy Treatment of Knee Osteoarthritis: A Bibliometric Literature Analysis
Bibliographic record
Abstract
There has been an increase in the life expectancy of people worldwide, especially in developing countries like India. Osteoarthritis, a condition that usually onsets during later decades of life, has also been on the rise, even with advancing technology. This has led osteoarthritis of the knee to become a global disabling condition of the lower extremity that increases dependency on the affected individual. A bibliometric study has not been conducted on knee osteoarthritis research. Therefore, a bibliometric analysis which includes statistical analysis of recent articles, books, and other forms of publications is done for evaluation of scientific output and to find the importance of scientific studies in terms of quality as well as quantity. The aim of this analysis was to evaluate the productivity of research articles indexed in PubMed related to the condition. The PubMed database was used and articles related to osteoarthritis of the knee, phonophoresis, and start excursion balance test were extracted. In the bib text format, all the files were downloaded and placed together. The R studio software (R Foundation for Statistical Computing, Vienna, Austria) for bibliometric analysis was then used, into which the research data was uploaded and a data framework of bibliometric analysis was made. Analysis of bibliometric publications related to knee osteoarthritis, phonophoresis, Otago exercises, star excursion balance test, ultrasound, and exercise therapy generated between 1989 and 2021 lists a total of 120 relevant documents from 75 sources with an average of 4.53 articles per year of publication. The use of an advanced PubMed database enables the extraction of adequate articles and powerful bibliometric analysis of the studies conducted on osteoarthritis of the knee published from 1989 to 2021. It includes an assessment of the contributions from major countries. This study allowed us to validate our methodology which can be used to evaluate research policies and promote international collaboration.
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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 | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.184 | 0.223 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".