Late Surgical-Site Infection in Immediate Implant-Based Breast Reconstruction
Notice bibliographique
Résumé
Sir: Sinha and colleagues have recently published in Plastic and Reconstructive Surgery a very interesting prospective, multicenter cohort study about patients submitted to mastectomy and immediate implant-based reconstruction.1 A total of 11 centers in the United States and Canada contributed to this study. A total of 1662 implant-based breast reconstructions in 1024 patients were evaluated for early versus late surgical-site infections. We would like to congratulate the authors on their article, which systematically analyzes several factors to identify possible clinical predictors. We consider their work essential because implant-based breast reconstruction is currently the most popular method for breast reconstruction, and surgical-site infection is currently the major cause that leads to reconstructive failure. Large multicenter trials regarding patients submitted to immediate implant-based reconstruction are fundamental for identifying predictors of surgical-site infections and thus improving surgical-site infection clinical management and development of preventative measures. In our Breast Unit, we are performing a retrospective single-center trial on our population of patients submitted to immediate implant-based breast reconstruction. At present, we have evaluated a total of 477 first-stage breast reconstructions in 417 patients between March of 2013 and May of 2016. Different from the study by Sinha et al., which is multicenter, our work is a single-institution study, thus reducing variability in terms of surgical-site infection evaluation and treatment protocol, including the criteria for inpatient hospitalization and intravenous antibiotics, explantation versus salvage, and radiotherapy protocol. Our preliminary data confirm that the majority of surgical-site infection complications in immediate implant-based breast reconstructions occur more than 30 days after first-stage breast reconstruction (mean time of presentation, 51 ± 59.8 days) and present a total infection rate of 9.2 percent, comparable to that declared by Sinha et al. In addition, we confirm obesity as a major predictor for surgical-site infection, although, different from Sinha et al., we observe a strong statistical relation between increased age and the development of local infection. Differing from Sinha et al., we analyzed as a possible risk factor axillary dissection that could be related to delayed seroma without finding any relations with infection. In contrast, we did not observe any relation between radiotherapy and surgical-site infection. It should be emphasized that we consider only patients submitted to first-stage breast reconstruction and, as confirmed by Sinha et al., radiation therapy is identified as a significant independent risk factor for late surgical-site infection, particularly following a second-stage tissue expander exchange procedure. Nevertheless, moving from our long experience in adopting autologous fat graft in irradiated breasts to reduce pain syndrome,2–4 we developed a clinical protocol5 that widely adopts this regenerative procedure to reduce complications, obtaining a 5.6 percent reconstruction failure rate in patients submitted to immediate two-stage breast reconstruction followed by radiotherapy. In conclusion, we consider studies such as the one published by Sinha et al. essential to critically evaluate outcomes in implant-based breast reconstruction, finding possible clinical predictors for surgical infection, analyzing therapeutic protocols, and comparing the experience of different centers. DISCLOSURE The authors have no financial interest to declare in relation to the content of this communication. Fabio Caviggioli, M.D.Francesco Klinger, M.D.University of MilanReconstructive and Aesthetic Plastic Surgery SchoolMultiMedica Holding S.p.A.Plastic Surgery UnitSesto San Giovanni, Milan, Italy Andrea Lisa, M.D.Monica Vappiani, M.S.Valeriano Vinci, M.D.Marco Klinger, M.D.University of MilanReconstructive and Aesthetic Plastic Surgery SchoolDepartment of Medical Biotechnology and TranslationalMedicine BIOMETRAPlastic Surgery UnitHumanitas Research HospitalRozzano, Milan, Italy
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 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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».