Can We Reach a Consensus on the Appropriate Use of Before and After Photos in Breast Surgery?
Why this work is in the frame
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Bibliographic record
Abstract
Breast surgery is an area of practice where patients value before and after photographs (BAPs). Consensus is needed to develop guidelines to address the deficit in the literature regarding appropriate use of BAPs, as these may ultimately play a significant role in the breast surgery consent process. METHODS: Expert breast reconstructive surgeons participated in a modified nominal group technique (NGT) to establish expert consensus on categories and criteria to be used when evaluating appropriate use of BAPs as part of informed consent. Endorsement rate of 75% and coefficients of variance within and between rounds were conducted to determine validity of each criteria item's rank order. RESULTS: Eight experts participated in the NGT in-person meeting and subsequent online survey. five of seven categories were endorsed for discussion: purpose, image type, anatomy, results, and photographic integrity. Overall consensus was obtained for six of 11 criteria. Criteria items found to have consensus were: patients considering surgery being the intended photograph audience (100% endorsement, CV1 - CV2 = 0.01), use of photographic images (75% endorsement, CV1 - CV2 = 0.04), defining the standard clinical photograph by having patients in the same body position (100% endorsement, CV1 - CV2 = 0.14), anonymizing images by removing all digital tags (88% endorsement, CV1 - CV2 = 0.03) and patient identifiers (75% endorsement, CV1 - CV2 = 0.00), not limiting the number of photograph sets needed for sufficient representation (100% endorsement, CV1 - CV2 = 0.07), and representing average outcomes (100%, CV1 - CV2 = 0.06). CONCLUSIONS: Early use of this validated and effective technique helps identify potential consensus categories and criteria that surgeons recommend for the use of BAPs in the informed consent process. Further study is required.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it