Health outcomes in offspring of mother with breast implants
Bibliographic record
Abstract
BACKGROUND: An increasing number of women undergo breast augmentation at their reproductive age. The most existing evidence focuses on the impact of breast implant on the index women's health and breastfeeding after they give birth to a child. No previous systematic review has investigated the association between breast implant in mother and health outcomes in offspring. In this study, we aimed to conduct a systematic review and meta-analysis to evaluate the influence of breast implant on offspring's health outcomes. METHODS: A comprehensive search strategy will be conducted including the following databases: MEDLINE (via PubMed), Embase, Cochrane Central Register of Controlled Trials, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Wan Fang Data. The World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) will be searched as well for retrieving the ongoing studies. The cohort study and case-control study will be considered as eligible study if investigating the impact of breast implant in mother on health outcomes in offspring. The risk of bias of included studies will be appraised by the Newcastle-Ottawa scale. RESULTS: The results of this study will be presented in the full-text of the systematic review. CONCLUSION: This systematic review and meta-analysis will infer a conclusion on the association between breast implant in mother and health outcomes in offspring, and the quality of existing evidence.PROSPERO registration number: CRD42019121221.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".