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Record W4406435255 · doi:10.1177/22925503241311255

Patient Perspectives of “Failure” in Breast Reconstruction: A Systematic Review of Qualitative Literature

2025· review· en· W4406435255 on OpenAlexaff
Caroline Hircock, Patrick Kim, Abhishek Achunair, Tara Behroozian, Lucas Gallo, Emily Dunn, Achilleas Thoma

Bibliographic record

VenuePlastic Surgery · 2025
Typereview
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsImpactUniversity of OttawaMcMaster University
Fundersnot available
KeywordsMedicineQualitative researchIntensive care medicineMedical physicsSociologySocial science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.321
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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