The RESTORE C19 Study: Outcomes for women denied immediate breast reconstruction in the United Kingdom during the first wave of the COVID-19 pandemic.
Bibliographic record
Abstract
Abstract Purpose The RESTORE C19 study aimed to explore outcomes for women not offered immediate breast reconstruction (IBR) following mastectomy for breast cancer during the first wave of the COVID-19 pandemic in the UK. Methods Women who were not offered IBR during the first wave of the COVID-19 pandemic (March-October 2020) were identified from the B-Map-C study database. Local collaborators were contacted between December 2021 and July 2022 to provide follow up data on the cohort, specifically whether women had been seen to discuss delayed breast reconstruction (DBR) and if so by whom; the receipt and timing of delayed reconstruction or documented decisions not to pursue reconstruction. Results Of the 366 women who were not offered IBR, complete follow-up data were available for 311 (85.0%). At a time point of between 21–28 months after mastectomy, less than half of women (n = 149, 47.6%) had been seen by a surgeon to discuss DBR and less than a third (n = 91, 29.2%) had been referred to plastic surgery to discuss autologous options. Only 21 (6.8%) women had actually received a DBR (4 with implant, 17 with autologous tissue). Almost one in five (n = 57) had decided against reconstructive surgery. Conclusions The majority of women denied IBR during the first wave of COVID-19 are still waiting for reconstructive surgery with almost 20% deciding not to pursue this option. Qualitative work is now needed to explore the experiences of this group in more detail to determine how best to support these women to complete their breast cancer journeys.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".