Racial Disparities in Immediate Breast Reconstruction After Mastectomy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: In the past few decades, there has been a gradual increase in breast reconstruction post mastectomy; however, there exists a conflict about whether race has an influence on reconstruction rates. Methods: We conducted an electronic search from MEDLINE and Cochrane CENTRAL from their inception to September 2022. Primary outcome was disparity in rates of Immediate Breast Reconstruction (IBR) in racial minorities. Odds ratios were pooled using a random-effects model. All statistical analyses were performed on the Review Manager. Quality of included studies was assessed using the Joanna Briggs Institute critical appraisal checklist. Results: Twenty studies ( n = 1 840 671) were identified. The pooled analysis of all the studies showed that subjects in racial minorities were significantly less likely to receive IBR as compared to White subjects (OR = 0.62, [95% confidence interval: 0.57-0.68; P < .01, I 2 = 97%]. Subgroup analyses revealed that Asian subjects were the least likely to undergo IBR among different minorities (OR = 0.43). Conclusion: There exists a significant disparity in rates of IBR in different racial minorities as compared to White subjects. Future studies are warranted to assess factors contributing to such disparities in provision of healthcare.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".