NLR and BMI are independent predictors of postoperative drainage volume in macromastia patients following reduction mammoplasty.

[BACKGROUND] Accurate prediction of post-reduction mammoplasty drainage volume is critical for optimizing postoperative care and reducing complication risks in patients with macromastia. This study aimed to identify key predictors of total postoperative drainage volume. We further investigated whether these predictors demonstrate consistent effects across diverse populations or subgroups, thereby providing evidence to support personalized management of postoperative drainage.

[METHODS] Clinical data from 69 macromastia patients were analyzed, including preoperative and postoperative variables such as body mass index (BMI), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and postoperative differential blood cell counts (e.g., postoperative neutrophils, lymphocytes, and monocytes). Data were summarized using descriptive statistics. Variables significantly associated with total drainage volume were screened via Spearman's correlation analysis. Univariate and multivariate regression analyses were subsequently performed to identify independent predictors. Additionally, stratified subgroup analyses based on BMI and age were conducted to assess the consistency of predictor effects.

[RESULTS] Univariate and correlation analyses revealed significant positive associations between total drainage volume and both BMI (Spearman's  = 0.564,  < 0.0001) and postoperative NLR (Spearman's  = 0.506,  < 0.0001). Multivariate regression confirmed BMI ( < 0.001) and postoperative NLR ( = 0.033) as independent and significant predictors of postoperative drainage volume. Furthermore, stratified analyses demonstrated consistent predictive effects for BMI and postoperative NLR across all BMI and age subgroups ( < 0.05), with no significant heterogeneity observed.

[CONCLUSION] This study identifies BMI and postoperative NLR as independent predictors of total postoperative drainage volume, highlighting their clinical utility. The consistent predictive performance of these factors across BMI and age subgroups supports their broad applicability. These findings provide evidence-based support for personalized drainage management strategies and offer critical insights for clinical practice.