The Impact of Implant Location on Breast Cancer Characteristics in Previously Augmented Patients: A Systematic Literature Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: There is a paucity of data comparing the oncologic properties of breast cancer among patients previously having undergone breast augmentation in either the subglandular or subpectoral planes. The objective of the present systematic review was to evaluate whether implant location influenced the characteristics of breast tumors in previously augmented women. Methods: A systematic literature search was performed to identify relevant articles reporting tumor characteristics in augmented patients. The search included published articles in three electronic databases; Ovid MEDLINE, EMBASE, and PubMed. Comparative studies (subglandular vs. subpectoral) were included. Results: Analysis of data pooled from the included studies showed that subglandular implants had a higher frequency of tumors between 2 to 5 cm (26.5% vs. 9.9%, P = 0.0130). Subglandular implants also had a higher frequency of stage 2 tumors (42.9% vs. 23.7%, P = 0.0308). There was no significant difference in lymphovascular invasion between the 2 groups. These results of this systematic review suggest that the prognosis of patients undergoing augmentation is unaffected by implant location (subpectoral vs. subglandular). Conclusions: With the absence of large randomized controlled trials, our study provides surgeons with an evidence-based reference to improve informed consent with regards to implant placement.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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