Current Status of Breast Implant Survival Properties and the Management of the Woman with Silicone Gel Breast Implants
Notice bibliographique
Résumé
The survival properties of silicone gel breast implants are dependent on their vintage (year of manufacture), duration in situ and manufacturer. A total of 527 gel implants have been explanted and analyzed in the author's laboratories. Of the 28 first-generation implants (1963 to 1972), 27 (96.4%) remained intact after 14 to 28 years in situ (mean 20.8 years). Of the 216 second-generation implants (1973 to mid-1980s) that were explanted from 1992 to 1998, 158 (73%) had disrupted. Kaplan-Meier survival curves demonstrated significantly different survival properties among second-generation manufacturers. Surgitek implants were by far the least durable. After 14 years, all second-generation Surgitek implants had disrupted. By contrast, after 20 years, about half of the Dow Corning and Heyer-Schulte implants remained intact. Among third-generation implants (mid-1980s to 1992), 43 of 46 (93.4%) remained intact after a mean of 6.3 years (range three to 12 years). The three disruptions were Surgitek implants. Implants from other manufacturers remained intact. However, the disruption frequencies of third-generation implants have yet to be measured over the relevant periods of time. Survival patterns appeared to be related to the thickness of the elastomeric shell of the three generations of implants. Mechanical strength analyses of the elastomeric shells of explants have exhibited little or no large scale material degradation, even after as long as 28 years in situ. The mechanism of implant disruption likely involves the ‘fold flaw’ theory, whereby an internal abrasion can develop over time at the site of a fold in the implant wall. Diagnosis of disruption is difficult. Mammography is helpful only if there has been extravasation of silicone gel into breast tissue. Extravasation was observed in only 4.2% of second-generation implants removed from 1992 to 1998. It was not seen with first- or third-generation implants. Ultrasound analyses are not generally helpful to predict disruption because they are very operator dependent and because capsular contracture causes folds in the implant wall, which result in false positives. Magnetic resonance imaging is the most accurate imaging modality to detect implant disruption. However, this technology is not indicated for monitoring implant status because it is too costly and time consuming, and because it has significant limitations, particularly with first-generation and textured implants. Careful explantation and direct visual examination are the standards for diagnosing gel implant disruption. Many implant disruptions are likely ‘silent’, with no specific symptoms or clinical findings. After disruption, none of the following are elevated above the levels seen in control women without implant exposure: serum autoantibodies, blood and serum silicon, and the incidence of breast cancer, autoimmune disease or any other medical disease. There is no evidence to support the existence of any ‘novel’ or ‘atypical’ syndrome associated with gel implants. Women over 30 years of age with breast implants require regular monitoring for breast cancer detection. This should include monthly breast self examination and annual clinical breast examination. In addition, women over 50 years old require annual eight-view mammographic assessment using the implant displacement technique. Even then, breast implants have been shown to interfere with complete imaging, particularly if the implants are subglandular, large or associated with significant capsular contracture. A logical approach to explantation should involve consideration of a patient's personal concerns and anxiety, her implant vintage, the plane of insertion of her implants, her current clinical status and whether she chooses to replace her gel implants. Women requesting explantation require extensive information before deciding on surgery. At explantation, capsulectomy seems to be indicated if there is capsular calcification or major capsular thickening. (Pour le résumé, voir page suivante)
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».