Effects of glucosamine supplements on painful temporomandibular joint osteoarthritis: A systematic review
Bibliographic record
Abstract
The purpose of this study was to systematically review the literature for studies that assessed the effects of glucosamine supplements (GS) on pain and maximum mouth opening (MMO) restriction compared to other therapies, placebo or no intervention on painful temporomandibular joint osteoarthritis (TMJ OA). Randomised controlled trials were selected in a two-phase process. Seven electronic databases, in addition to three grey literature databases, were searched. Risk of bias was assessed using the Cochrane Collaboration's tool for assessing risk of bias in randomised trials. Twelve potentially eligible studies were identified, from which three were finally included. Furthermore, two were categorised at low risk and one at high risk of bias. Intervention groups were treated with glucosamine-sulphate, while controls were treated with placebo or ibuprofen. In two studies, GS were equally effective regarding pain reduction and mouth opening improvement compared to ibuprofen taken two or three times a day over 12 weeks; however, one study did not find significant differences in follow-up evaluations concerning these clinical variables in both glucosamine and placebo groups administered over six weeks. There is very low evidence regarding GS therapeutic effects on TMJ OA. Considering a follow-up of 12 weeks, GS were as effective as ibuprofen taken two or three times a day. However, over six weeks of medication intake, GS were not superior to placebo. Still, included studies presented major drawbacks, and therefore, conclusions must be interpreted with caution.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".