Influence of Socio-cultural Factors on Student Transition and Retention in Schools in Msambweni Sub-county, Kwale County, Kenya

Abstract

Preoperative determination of breast weight to be removed aids plastic surgeons in counseling the patient, application for insurance coverage and ensures optimal postoperative breast symmetry. Various mathematical models have been developed to preoperatively predict resection weights. We validate and determine which model is most accurate. A sample of 24 consecutive women undergoing reduction mammaplasty were involved; anthropometric measurements of each individual breast (48 samples) was collected and used to predict mass of breast excised within a 1 year period. Predicted weight deviations from the actual weight of breast tissue excised were compared between 4 models using repeated measures ANOVA at 95% confidence interval. Mean age was 32.25±2.14 and 60.8% of the patients undergoing reduction mammaplasty were aged 35 years and below. Three-quarter of the respondents were obese (BMI ≥ 30kg/m2). While two models significantly under-estimated breast mass to be excised; the other two provided accurate predictions with model 1 predicting 78.1% (correlation = 0.884) of actual mass excised and model 2 predicting 77.1% (correlation = 0.879). The model reported by Yavuz et al can be safely utilized in preoperative prediction of resection weight in reduction mammaplasty.