Does the use of hyaluronic acid viscosupplementation prolong the viability of a patient's knee with oseteoarthritis, delaying the need for surgical management? A systematic review of the literature
Bibliographic record
Abstract
Introduction: Osteoarthritis of the knee is a very common complaint in the aging population and a significant burden on not only the patient, causing pain, decreased mobility and a lowered quality of life, but also the healthcare system with frequent primary care visit associated with its symptoms. We investigated the use of viscosupplementation with hyaluronic acid and how long improvement was sustained, preventing the need for costly total knee arthroplasty. Methods: Using Medline (OVID) search strategy from 1946 until February 2016 was developed with they guidance of library personnel trained in research. We searched for studies that looked specifically at the amount of time that a patient would be able to continue using their knee with appropriate level of function and pain before the gold-standard of treatment via total knee arthroplasty would need to be performed. Titles and abstracts of articles were read to determine if appropriate and four articles met the inclusion criteria which meant the articles must look specifically at how long the use of viscosupplementation prevented the need for total knee arthroplasty. Results: In all four articles the time to total knee arthroplasty was increase over no treatment. In all the studies they calculated average time to total knee arthroplasty based on the point in which half the knees treated by viscosupplementation required surgical intervention. The range in these studies saw a prolongation between 370 to 919 days over the control groups which were patients whom did not receive viscosupplementation. It was also found that in patients who were considered positive responders, the more courses of viscosupplementation received, the longer the delay of surgical intervention. Conclusion: Based on the research reviewed it can be said that the use of viscosupplementation vs. no treatment or failed conservative treatment delays the need for total knee arthroplasty in patient with knee osteoarthritis. Further research must be done with more high quality studies using controls to improve the accuracy of this information. Also, further research should be done to determine if these positive results would in turn lead to savings for the Canadian healthcare system and how best to implement them.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".