Use of Alternative Medicines by Patients with OA that Adversely Interact with Commonly Prescribed Medications
Bibliographic record
Abstract
UNLABELLED: Owing to the increasing prevalence, patient interest, and high risk of adverse effects associated with use of complementary and alternative medicine (CAM), investigation of this issue in an orthopaedic population is warranted. The objectives of this study were to (1) identify the prevalence of CAM use, (2) assess the level of communication between patients and physicians regarding CAMs, (3) uncover reasons for nondisclosure, and (4) identify potentially harmful interactions between CAMs and conventional therapy. We conducted a cross-sectional observational study among patients being treated in orthopaedic surgical clinics for osteoarthritis (OA). Of the 373 participants, 42.9% reported taking one or more CAMs, and 40.6% admitted their surgeons were unaware of their alternative therapy use. Reasons for nondisclosure included, the patient thought: (1) it was not important (29.7%); (2) the surgeon would not be interested (13.5%); and (3) their surgeon would not know about CAMs (8.2%). Twenty-two of 281 patients (7.8%) were taking alternative medicines that could interact with their blood pressure medication, 28.6% were taking anticoagulant/antiplatelet medication and also taking a CAM that could interact, and 5.9% were taking conventional pain medications along with a CAM that potentially could interact. Orthopaedic surgeons should make it part of their consultation to inquire about CAM use. LEVEL OF EVIDENCE: Level III, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".