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Enregistrement W4317477987 · doi:10.1093/asj/sjad012

Commentary on: Patient-Reported Outcomes After Reduction Mammoplasty Using BREAST-Q: A Systematic Review and Meta-Analysis

2023· review· en· W4317477987 sur OpenAlexaffabout
Elizabeth J. Hall-Findlay

Notice bibliographique

RevueAesthetic Surgery Journal · 2023
Typereview
Langueen
DomaineMedicine
ThématiqueBreast Implant and Reconstruction
Établissements canadiensBanff Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineReduction MammoplastyMammoplastyBreast reductionMeta-analysisGeneral surgeryGerontologySurgeryInternal medicineMammaplastyBreast cancer

Résumé

récupéré en direct d'OpenAlex

See the Original Article here. This is a helpful compilation of 28 qualified papers which have tried to sort out what variables result in more or less patient satisfaction with breast reduction as assessed by the validated BREAST-Q questionnaire.1 We are all aware that breast reduction is one of the most satisfying procedures in plastic surgery. The BREAST-Q, developed by Pusic et al in 2009, has allowed us to better evaluate what factors lead to more or less patient satisfaction in both physical and psychosocial aspects of patient well-being.2 The most important information provided by this review is that the amount of tissue resected is unrelated to patient satisfaction. Before validated questionnaires were available, I had patients fill out Likert scales comparing preoperative and postoperative symptoms after breast reduction, and Strong then performed a statistical analysis which showed that symptom improvement was independent of the amount of breast tissue resected.3 The authors conclude that these papers support a reassessment of insurance criteria for breast reduction coverage. Small breast reductions had high satisfaction scores. We all know that the Schnur scale was never meant to be used by insurance companies and it is unhelpful in determining when a breast reduction should be considered cosmetic vs medically indicated.4 I disagree with the authors’ words that a breast reduction is “medically necessary,” and I would prefer the description “medically indicated.” But when should psychosocial satisfaction be the criteria for coverage vs physical symptom improvement? We all know that patients who request purely cosmetic procedures such as mastopexy or breast augmentation can have significant improvement in psychosocial parameters, but should they be covered by insurance? As one of my Canadian colleagues frequently pointed out, patients want a breast reduction for medical reasons, but they sue us for the cosmetic result (John Taylor, personal communication, April 1994). The main conclusions from this meta-analysis are that the papers with large numbers of patients—Persichetti's group from Italy (414 patients),5 Jorgensen's group from Denmark (393 patients),6 and Cabral's group from Brazil (107 patients)7—show that not only is overall patient satisfaction in multiple areas significantly improved, but satisfaction rates are slightly reduced with higher BMIs and complication rates, and are increased with increasing age. Resection amounts did not affect satisfaction rates. We can also learn from series such as that presented by Morris et al that looked at racial disparities in 115 patients.8 It is clear from their review that we still have a lot to learn and improve in that aspect of our practices. Ozbey et al claim that “patient satisfaction is the most important determinant of surgical success,” but I would argue that we should somehow also be looking at aesthetic improvement from a surgical standpoint.9 We do not yet have a good way of analyzing the aesthetic result and this is where the BREAST-Q is not going to be particularly helpful. We know that our management of patient expectations can play a huge role in patient satisfaction. We have all experienced patients who are very satisfied with results that we find less than optimal from a surgical aesthetic perspective. The authors sometimes got sidetracked from patient satisfaction questionnaires and comment on irrelevant aspects of surgical technique. For example, they note that Aquinati et al's paper showed a “validated use of the hammock flaps for breast reduction resulting in positive outcomes in patient reported satisfaction.”10 There were only 10 patients in that study with no before-and-after proof that the hammock flaps had anything to do with either improved results or patient satisfaction. In fact, Aquinati et al only include 2 postoperative photographs with no preoperative photograph for comparison. Overall, however, this is an excellent review of validated studies based on the BREAST-Q that will help us understand which aspects of our breast reduction candidates will affect patient satisfaction scores. The author declared no potential conflicts of interest with respect to the research, authorship, and publication of this article. The author received no financial support for the research, authorship, and publication of this article.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,018
score de la tête « metaresearch » (Gemma)0,129
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,028
Score d'incertitude au seuil0,094

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0180,129
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,004
Bibliométrie0,0040,004
Études des sciences et des technologies0,0020,002
Communication savante0,0040,004
Science ouverte0,0050,002
Intégrité de la recherche0,0170,010
Charge utile insuffisante (le modèle a refusé de juger)0,0280,009

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,105
Tête enseignante GPT0,339
Écart entre enseignants0,234 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2023
Routes d'admission2
Résumé présentoui

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