Predictive Factors for Drainage Volume after Expander-based Breast Reconstruction.
Plast Reconstr Surg Glob Open
; 4(6): e727, 2016 Jun.
Article
em En
| MEDLINE
| ID: mdl-27482475
ABSTRACT
BACKGROUND:
Closed suction drains are widely used in breast reconstruction, and the drains are removed based on a volume criterion. However, to the best of our knowledge, there has been no study analyzing predictive factors for drainage volume after breast reconstruction.METHODS:
Data of daily drainage in cases with expander-based breast reconstruction between February 2013 and March 2015 (131 patients and 134 expanders) were retrospectively analyzed. Patient factors and operative factors were examined for their influences on total drainage using univariate and multivariate analyses.RESULTS:
The total drainage was 557.3 ± 359.7 mL. A strong correlation was observed between total drainage and duration of drains (correlation coefficient, 0.908). Operative factors, such as mastectomy type, expander type, operative time, and blood loss, did not affect the total drainage. Patients with axillary lymph node dissection showed a higher total volume of drainage (P < 0.001). The weight of the resected specimen, body weight, and breast volume calculated preoperatively showed a strong correlation with total drainage (correlation coefficients, 0.454, 0.388, and 0.345, respectively). In multiple regression analysis with preoperative data, age (P = 0.008), body weight (P = 0.018), and scheduled axillary dissection (P < 0.001) were significant predictive factors for total drainage. Among postoperative data, age (P = 0.003), axillary dissection (P = 0.032), and weight of resected specimen (P = 0.013) were significant predictors.CONCLUSIONS:
Based on preoperative and/or postoperative information, plastic surgeons can predict the total drainage and duration of drains after expander-based breast reconstruction. Age, breast mass, and axillary lymph node dissection are important factors for this prediction.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article