Outcome Measures to Evaluate Upper and Lower Extremity: Which Scores are Valid?
Bibliographic record
Abstract
OBJECTIVE: In orthopaedics and trauma surgery scores are frequently used to assess treatment outcomes. The purpose of the review is to create an overview analysing the content of validity studies of frequently utilized scores for upper and lower extremity. METHODS: Commonly used outcome measures to assess clinical outcome of upper (n = 19) and lower (n = 22) extremity were included. For each of the scores a comprehensive search in several databases (Medline, PubMed, google scholar) were performed to identify validation studies. The COSMIN-Checklist (COSMIN: Consensus-based Standards for the selection of health Measurement Instruments) introduced by Mokkink et al. were used to analyse systematically the methodological quality of the validation studies. RESULTS: Validity, objectivity and reliability were not routinely considered and addressed in validation studies. The score related validation studies did not include all defined criteria of the COSMIN-Checklist. Six scores of the upper extremity and four scores of the lower extremity are not adequately validated. The best validated scores of the upper extremity is Oxford Shoulder Score (OSS) and for the lower extremity Hip Disabilities and Osteoarthritis Outcome Score (HOOS) as well as Western Ontario and McMaster Universities Score (WOMAC). CONCLUSION: There is no gold standard for the content-comprehension of validation studies due to the structure of the original study. The more criteria were tested the more informative and significant the outcome measure is. However some scores, such as Neer and Castaing Score, that lack validation are still being successfully used in research and clinical practice. The present review provides an overview of frequently used score in orthopaedics and trauma surgery and their grade of validity.
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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 | 0.042 | 0.141 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".