Top 100 cited studies in periacetabular osteotomy for acetabular dysplasia: do lower levels of evidence guide clinical practice?
Bibliographic record
Abstract
As no prior study has examined the citations profile of key articles related to periacetabular osteotomy (PAO), our analysis utilized the Web of Science database to (1) identify the most-cited clinical studies relating to PAO in the management of acetabular dysplasia and (2) assess any trends over time with respect to the quality of literature. The top 100 highest-cited studies related to PAO had a mean of 49 citations (range, 6-666 per study). With respect to the level of evidence, most studies had level IV evidence (58%); 1% level I, 16% level II, 28% level III and 2% level V. Most studies were retrospective ( n = 86); there were 14 prospective studies (including one randomized study). The most common study designs were case series ( n = 58) and cohort ( n = 16), followed by matched-cohort ( n = 13) and case-control ( n = 6). The mean ± SD Newcastle-Ottawa Scale score was 6.48 ± 1.31. A total of 59 and 41 of the included articles were classified as high risk and high quality, respectively. No studies were classified as very high risk. As a whole, our analysis demonstrated that currently available PAO literature is still of low quality and of low level of evidence. While PAO has been well-documented as a durable procedure for addressing acetabular dysplasia, future research must focus on higher quality, randomized and prospective data to answer key clinical or technique-related topics.
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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 | 0.072 | 0.315 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.108 | 0.086 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".