Early Osteoarthritis Questionnaire (EOAQ): a tool to assess knee osteoarthritis at initial stage
Bibliographic record
Abstract
Background: Early stage of osteoarthritis (OA) is characterized by joint stiffness and pain as well as by subclinical structural changes that may affect cartilage, synovium, and bone. At the moment, the lack of a validated definition of early osteoarthritis (EOA) does not allow to make an early diagnosis and adopt a therapeutic strategy to slow disease progression. Also, no questionnaires are available to evaluate the early stage, and therefore this remains an unmet need. Objective: Therefore, the purpose of the technical experts panel (TEP) of 'International Symposium of intra-articular treatment' (ISIAT) was to create a specific questionnaire to evaluate and monitor the follow-up and clinical progress of patients affected by early knee OA. Design: The items for the Early Osteoarthritis Questionnaire (EOAQ) were identified according to the following steps: items generation, items reduction, and pre-test submission. Methods: During the first step, literature has been reviewed and a comprehensive list of items about pain and function in knee EOA was drafted. Then, during the ISIAT (5th edition 2019), the draft has been discussed by the board, which reformulated, deleted, or subdivided some of the items. After the ISIAT symposium, the draft was submitted to 24 subjects affected by knee OA. A score based on the importance and the frequency was created and the items with a score ⩾0.75 were selected. After intermediate evaluation made by a sample of patients, the second and final version of the questionnaire EOAQ was submitted to the whole board for final analysis and acceptance in a second meeting (29 January 2021). Results: After an exhaustive elaboration, the final version of the questionnaire contains two domains (Clinical Features and Patients Reported Outcome) with respectively 2 and 9 questions, for a total of 11 questions. Questions mainly explored the fields of early symptoms and patients reported outcomes. Marginally, the need of the symptoms treatment and the use of painkillers were investigated. Conclusions: Adoption of diagnostic criteria of early OA is strongly encouraged and a specific questionnaire for the whole management of the clinical features and patients' outcome might really improve the evolution of OA in the early stages of the disease, when the treatment is expected to be more effective.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".