The Level of Evidence Presented at Plastic Surgery Meetings
Bibliographic record
Abstract
BACKGROUND: Internationally, plastic surgery societies have placed an increasing emphasis on the importance of evidence-based medicine. The authors aimed to categorize levels of evidence of podium presentations at three major North American plastic surgical meetings, and to assess the factors associated with a higher level evidence. METHODS: Presentations at the 2010/2011 meetings of three of the largest societies of plastic surgeons in North America were evaluated for the area of research, number and origin of authors, subdomain of plastic surgery, number of centers of collaboration, number of subjects, study subtype, and level of evidence. RESULTS: One hundred eighty-eight presentations were screened, and 126 met eligibility criteria. The American Society of Plastic Surgeons was the largest meeting with 74 presentations (58.7 percent). Breast (23.8 percent) and craniofacial (21.4 percent) topics were most frequently covered. Most studies had five or fewer authors (76.4 percent), were conducted at a single center (84.3 percent), were therapeutic (89.7 percent), and had 50 or fewer subjects (36.8 percent). Two studies (1.6 percent) were level I, 11 (8.7 percent) were level II, 54 (42.9 percent) were level III, 46 (36.5 percent) were level IV, and 13 (10.3 percent) were level V. Overall, the mean level of evidence was 3.45, and one of every 10 presentations was of higher level of evidence (level I or II). Higher level evidence presentations were found to be associated with multicenter studies. CONCLUSIONS: Evidence presented at major plastic surgical meetings is rarely level I and infrequently level II. Opportunities to create greater awareness of the need for prospective high-level studies are needed.
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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 | 0.020 | 0.165 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 0.016 |
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".