Breast Reconstruction in Older Women: Should Age Be an Exclusion Criterion?
Bibliographic record
Abstract
BACKGROUND: At present, breast reconstruction is undertaken by fewer than 10 percent of breast cancer patients undergoing mastectomy. Even though the benefits are numerous, this finding is even more notable among older women. Traditionally, women older than the age of 60 have been offered implant reconstruction or no reconstruction at all in hopes of minimizing potential morbidity. This practice may be due to a number of factors including a lack of patient education and information, as well as physician/surgeon bias regarding the safety or relevance of breast reconstruction in older women. METHODS: The authors undertook a retrospective study in which they surveyed 75 women (age range, 60 to 77 years) from two surgeons' practices who underwent various forms of breast reconstruction over the past 8 years. Type of reconstruction, recovery time, and complication rate were correlated with patient satisfaction, general health, and quality of life. RESULTS: An 81 percent response rate was obtained, yielding an average age of 66.6 years over a 3.8-year period. The overall rate of complications requiring operative intervention was 20.5 percent. When asked whether age should be a determining factor for breast reconstruction, more than 90 percent felt that it should not be. Only 16.1 percent of patients who had a delayed reconstruction stated that the option of breast reconstruction was presented to them at the time of their diagnosis, although 100 percent felt that it should have been. A significantly poorer physical health score was found among patients who experienced a complication, and lower mental health scores correlated with women who were less satisfied with their outcome. CONCLUSIONS: The authors believe that all types of reconstruction should be an option for women older than 60 years of age and that age as an isolated factor should not deter physicians from offering these women the option of breast reconstruction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".