医学
乳房整形术
外科
还原(数学)
结果(博弈论)
投影(关系代数)
乳房缩小术
群(周期表)
关系(数据库)
假体设计
作者
Daniel Hilewitz,Oren Ganor,NETA ADLER,Asaf Olshinka,Dafna Shilo Yaacobi,Itay Chen,Tamir Shay,Yehiel Hayun,DEAN AD-EL,Sagit Meshulam Derazon
标识
DOI:10.1097/prs.0000000000012634
摘要
Background: Despite the short-scar reduction-mammaplasty documented advantages, it remains debatable regarding their broad applicability. Critics argue that it does not manage lower-pole skin-excess as effectively as the T-scar technique. The S-flap modification of the Hall-Findlay technique potentially retains the advantages of the short-scar while providing a more stable lower-pole. Methods: Out of 147 single surgeon consecutive cases operated on between 2016 and 2022, 58 (39.5%) completed at least one year of follow-up and answered a Breast-Q reduction mammaplasty questionnaire. They were divided into three groups: vertical-scar, J-scar, and the more recent S-scar. The S-scar modification is analyzed in relation to the previously used vertical and J-scar techniques. Results: The S-scar group was characterized by a significantly (p=0.002) higher mean resection-weight (456±226g) than the vertical-scar group (317±158g), longer preoperative nipple-intramammary-fold (Ni-IMF) distance (20±3cm) than the V and J groups (both 16±2cm), and shorter follow-up time (57±3 weeks vs 128±80 and 110±55 weeks, respectively). Long-term improvement rates in Ni-IMF-distance in the J, V, and S groups were 12.44%±13.08, 13.01%±13.63, and 21.83%±8.8, respectively (p=0.003). Breast-Q questionnaire scores across all parameters ranged from 72.35 to 98.63, with no significant differences among the groups, except for general outcome and information criteria which were higher in the S-scar group (p=0.001 for both). Conclusions: The S-flap modification maintains the short-scar advantages in terms of shape and projection with the added advantages of a more stable lower-pole, as reflected by a shorter NI-IMF distance and a better general outcome score. A follow-up period exceeding one year, and a larger cohort are still needed.
科研通智能强力驱动
Strongly Powered by AbleSci AI