Expert perspectives on polmacoxib monotherapy in the management of osteoarthritis in Indian settings
Bibliographic record
Abstract
Background: Although there were several clinical studies available, there was a dearth of studies among clinicians in actual practice. So, the present survey-based study aimed to gather expert perspectives on the clinical use of polmacoxib monotherapy for the management of osteoarthritis (OA) in routine Indian settings. Methods: This cross-sectional study employed a 19-item questionnaire to gather expert opinions on managing OA and covered topics such as prescription practices, clinical observations, preferences and experiences with polmacoxib for routine OA management. Descriptive statistics were used to analyze the gathered data. Results: The study involved 239 participants, with 45% of respondents noting that 31-40% of OA patients are women. According to 65% of the participants, etoricoxib emerged as the most preferred nonsteroidal anti-inflammatory drug (NSAID) in clinical practice. Moreover, 87% of experts recognized the dual cyclooxygenase-2 (COX-2) and carbonic anhydrase (CA) binding properties of polmacoxib as potentially offering superior safety profiles in cardiovascular (CV), renal aspects and Gastrointestinal (GI) tolerability. Around 35% of respondents observed improvements in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), pain reduction, stiffness alleviation and enhanced physical function with polmacoxib. Conclusions: The study highlighted a significant preference among Indian clinicians for polmacoxib in managing OA, primarily due to its dual COX-2 and CA binding properties that potentially offer better safety profiles in terms of cardiovascular, renal and GI tolerability. Additionally, the observed improvements in pain, stiffness and physical function with polmacoxib underscore its effectiveness as a monotherapy in routine OA management.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".