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Patient Self-Assessment of the Cosmetic Results of Breast Reconstruction

2006· article· en· W2032601712 on OpenAlexaff
William Andrade, John L. Semple

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2006
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsCanadian Society of Plastic SurgeonsWomen's College HospitalUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineCosmesisBreast reconstructionPatient satisfactionScarsSurgeryInternal medicineBreast cancer

Abstract

fetched live from OpenAlex

Background: In a previous study, the authors evaluated factors that contribute to patient satisfaction with breast reconstruction, using a comprehensive chart review and questionnaire. The results of part of this questionnaire, regarding patients' rating of the cosmetic result of their breast reconstruction, are presented in this article. Methods: The questionnaire was mailed to 267 patients, 214 questionnaires (80.1 percent) were returned, and 200 contained a response to the question rating the overall cosmetic outcome of breast reconstruction (Fig. 1). To conduct a statistical analysis, the data were collapsed into two smaller groups. An “excellent” or “good” result was considered a “favorable” outcome, while lower responses were “unfavorable” outcomes.Fig. 1.: Portion of questionnaire analyzed for this study. Note that the responses to overall cosmesis were later condensed into “favorable” versus “unfavorable” categories to facilitate statistical analysis.Results: The outcome was rated as excellent by 82 patients, good by 76 patients, fair by 31 patients, and poor by 11 patients. A significant association was found between overall cosmesis and breast size, shape, or scars. Conclusion: It should not be assumed that patients' responses regarding satisfaction with reconstruction will reflect their specific feelings regarding cosmetic results.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations33
Published2006
Admission routes1
Has abstractyes

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