Evaluation of disease burden, patient journey, unmet diagnosis and treatment needs of patients with HIP and knee osteoarthritis in Turkey: A study through Delphi Methodology
Bibliographic record
Abstract
Objective: To get information-driven insights from expert physicians regarding multiple aspects of the patient journey in knee and hip OA and establish a consensus for future studies and decision tree models in Turkey. Design: 157 questions were asked in total during this three-round modified Delphi-method panel to 10 physical medicine and rehabilitation specialists (2 have rheumatology and 3 have algology subspeciality), one orthopaedic surgeon and one algology specialist from anaesthesia specialty background. A consensus was achieved when 80% of the panel members agreed with an item. Contradictions between different disciplines were accepted as a non-consensus factor. Results: Panellists agreed that American College of Rheumatology classification criteria is mostly sufficient to provide an OA diagnosis in clinical practice, OA patients with ≥5 Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain or physical function score can be defined as moderate-to-severe OA if they have an additional ≥2 Kellgren-Lawrence (KL) score, a minimum improvement of 30% from baseline in WOMAC pain or function subscales or in PGA score can be accepted as moderate treatment response where ≥50% improvement from baseline in those scores as substantial response. Panellists stated that arthroplasty procedures need to be delayed as long as possible, but this delay should not jeopardize a beneficial and successful operation. Conclusions: These findings show that there is a significant disease burden, unmet treatment needs for patients with moderate-to-severe OA in Turkey from experts' perspective. Therefore, an updated systematic approach and decision tree models are needed to be implemented.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".