Brazilian oral herbal medication for osteoarthritis: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis affects 1 % of the world's population and is the most common cause of musculoskeletal impairment in the elderly. Herbal medications are commonly used in Brazil to manage symptoms associated with osteoarthritis, and some of them are financed by the Brazilian government; however, the effectiveness of most of these agents is uncertain. The aim was to systematically review the efficacy and safety of 13 oral herbal medications used in Brazil for the treatment of osteoarthritis. METHODS: Randomized clinical trials eligible for our systematic review will enroll adults with osteoarthritis treated by a Brazilian herbal medication or a control group (placebo or active control). Using terms to include all forms of osteoarthritis combined with herbal medications, we will search the following electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; EMBASE; CINAHL; Web of Science; Health Star; AMED, the database of the Cochrane Complementary Medicine Field, LILACS; CAB abstracts, Clinical trial.gov, WHO trials registry, and Bank of Brazil Thesis (CAPES), to 31 January 2016, without restrictions concerning language or status of publication. Outcomes of interest include the following: symptom relief (e.g., pain), adverse events (gastrointestinal bleeding, epigastric pain, nausea, and allergic reactions), discontinuation due to adverse events, quality of life, and the satisfaction with the treatment. Dichotomous data will be summarized as risk ratios; continuous data will be given as standard average differences with 95 % confidence intervals. A team of reviewers will assess each citation independently for eligibility and in duplicate it. For eligible studies, the same reviewers will perform data extraction, bias risk assessment, and determination of the overall quality of evidence for each of the outcomes using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) classification system. DISCUSSION: This is the first study that will evaluate the use of herbal medications used in Brazil for the treatment of pain caused by osteoarthritis. The results could guide prescribers in decision-making in clinical practice, to inform the patients with pain caused by osteoarthritis in relation to effective and safe treatment options and to inform the managers of the public health system which of the plants could actually be financed by the Brazilian government. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 42015019793.
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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 | 0.053 | 0.055 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.020 | 0.012 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.085 | 0.010 |
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".