Delphi Study Consensus Recommendations
Bibliographic record
Abstract
BACKGROUND: There is considerable variation in the planning and implementation process for breast augmentation. Although general guidelines are available, the distinctive characteristics of the Natrelle 410 breast implant warrant surgical guidelines specific to this device. This study aimed to develop consensus recommendations for patient selection and preoperative planning for Natrelle 410 in primary breast augmentation. METHODS: Surgeons were invited to participate in this study, which used a modified Delphi method. Participants completed 2 rounds of online surveys, with the second round (Recommendations Survey) based on responses from the first round. Respondents also listed their top priorities for using Natrelle 410 implants. RESULTS: Participants (n = 22) reached consensus on 15 of 18 criteria for patient selection; tuberous breasts, patient preference regarding upper pole shape, and asymmetry of the breasts were the top 3 patient characteristics considered appropriate for the use of Natrelle 410. Consensus was reached on 38 of 51 items related to preoperative planning, with 8 measurements and 6 markings recommended by the participants. Patient-desired outcome was considered the most essential element for Natrelle 410 implant selection; quality of skin envelope and height and width dimension of the breast were selected as the most essential elements for Natrelle 410 implant volume selection. CONCLUSIONS: The modified Delphi method resulted in consensus recommendations for patient selection and preoperative planning in primary breast augmentation with the Natrelle 410 breast implant. These recommendations and priorities, used in concert with a surgeon's clinical experience, are designed to optimize surgical outcomes.
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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 | 0.236 | 0.300 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".