Recognizing and Managing Breast Implant Complications: A Review for Healthcare Providers Who Treat Women Who Underwent Breast Implant–Based Surgery
Notice bibliographique
Résumé
Paolo Fanzio,1,* Jason Hammer,1,* Nancy Van Laeken2,* 1Plastic Surgery & Regenerative Medicine, Allergan Aesthetics, an AbbVie Company, Irvine, CA, USA; 2Division of Plastic Surgery, University of British Columbia, Vancouver, BC, Canada*These authors contributed equally to this workCorrespondence: Nancy Van Laeken, Clinical Professor, Division of Plastic Surgery, University of British Columbia, 1788-1111 West Georgia Street, Vancouver, BC V6E 4M3, Canada, Tel +1 604-669-1633, Fax +1 604-669-4516, Email nancy@vanlaeken.comAbstract: Given the prevalence of breast implants, healthcare providers treating women should be familiar with potential complications that may result from breast augmentation and implant-based reconstruction surgeries and the appropriate management strategies to adopt for each. Familiarity with risk factors and variables involved in complications and an understanding of the patient’s surgical history and implant type/characteristics is key. This article provides an overview of implant types and surgical approaches and potential complications related to surgery that physicians treating women may encounter during routine clinical practice. It describes potential implant complications such as hematoma, implant rupture, infection, seroma, rare capsular lymphomas, capsular contracture, implant malposition, rippling, and animation deformity. This article also describes systemic symptoms that patients sometimes attribute to breast implants, such as fatigue, brain fog, joint pain, anxiety, hair loss, depression, rash, autoimmune diseases, inflammation, or gastrointestinal symptoms. Rare conditions, such as breast implant–associated anaplastic large cell lymphoma and squamous cell carcinoma in the capsule around breast implants, are also presented. Diagnostic criteria are summarized, with photographic examples, and management strategies and referral recommendations across the range of potential complications are provided. This article provides information to support healthcare providers who treat women in detecting breast implant complications and guiding their patients to an appropriate treatment and referral strategy.Plain Language Summary: Breast implants are used to increase breast size or to restore shape following surgical removal of the breast due to cancer. The use of breast implants is growing, increasing the likelihood of doctors providing care for women who have breast implants. As a result, it is important for doctors who treat women to recognize problems that may occur following breast implant surgery and how to manage them. Knowing the factors that increase the likelihood of problems that may be related to breast implants, the medical history of the patient, and the type of breast implant are important. This article reviews the types of breast implants, the types of implant surgeries, and the problems that can result from those surgeries. For each potential breast implant problem identified, example photographs are provided, along with details on how to diagnose and manage the problem and when to refer the patient to a specialist. This article provides information to doctors to aid in identifying and treating women who encounter problems that may be related to their breast implants.Keywords: contracture, hematoma, referral and consultation, mammaplasty, seroma
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Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».