Consistency of Reported Outcomes After Arthroscopic Management of Femoroacetabular Impingement
Bibliographic record
Abstract
PURPOSE: The purpose of this systematic review is to evaluate the consistency of the reporting of clinical and radiographic outcomes after arthroscopic management of femoroacetabular impingement (FAI). METHODS: Two databases (Medline and EMBASE) were screened for clinical studies involving the arthroscopic management of FAI. A full-text review of eligible studies was conducted, and the references were searched. Inclusion and exclusion criteria were applied to the searched studies, and a quality assessment was completed for included studies. RESULTS: We identified 29 eligible studies involving 2,816 patients. There was a lack of consensus with regard to reported outcomes (clinical and radiographic) after arthroscopic treatment of FAI. Clinical outcomes reported include the Harris Hip Score (45%) and the Non-Arthritic Hip Scale (28%), range of motion (34%), pain scores (24%), and patient satisfaction (28%). The most commonly reported radiographic outcomes included the alpha angle (38%), head-neck offset (14%), and degenerative changes (21%). CONCLUSIONS: There is significant variation in reported clinical and radiographic outcomes after arthroscopic treatment of FAI. This study highlights the need for consistent outcome reporting after arthroscopic FAI surgery. LEVEL OF EVIDENCE: Level IV, systematic review of Level II, III, and IV studies.
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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 | 0.091 | 0.395 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".