Patient Perspectives of “Failure” in Breast Reconstruction: A Systematic Review of Qualitative Literature
Bibliographic record
Abstract
Introduction: The concept of failure in breast reconstruction can occur when negative outcomes dominate the patient experience. The primary objective of this review was to identify experiences of failure in breast reconstruction from the patient's perspective in the qualitative literature. Methods: MEDLINE, Embase, Psychinfo, Emcare, and CINAHL were searched on July 31, 2023 using terms related to breast reconstruction and qualitative research. Thematic analysis was performed on direct quotations from included studies. Confidence in the Evidence from Reviews of Qualitative (CERQual) Research was used to assess confidence of the final findings. Results: Forty-two studies were identified. The following themes were identified in breast reconstruction failure : (1) failure occurs when expectations of restoring the original breast are not met with reconstruction, (2) failure occurs when unexpected outcomes were associated with the reconstruction, and (3) healthcare providers negatively impact the experience of breast reconstruction failure through lack of transparency when educating patients on expected results and poor relational support in the post-operative period. The evidence supporting themes 1-3 scored high confidence with CERQual. Conclusion: Breast reconstruction failure from the patient perspective arises from the limitations and adverse outcomes of the surgery. They may also arise even when the procedure was deemed “successful” from the surgeon's perspective. Dissatisfaction with result is increased by procedural complications. Healthcare providers can aggravate the perception of failure through inadequate patient education. Incorporating these perceptions of failure into discussions with patients can aid in their decision making.
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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 | 0.080 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".