Close monitoring of the patient's general condition in cases of non-specific abdominal pain is essential to identify the rare deteriorating patient for early surgical intervention and optimal outcome.
Background
The optimal strategy for oncologic sternectomy reconstruction has not been well characterized. We hypothesized that the major factors driving the reconstructive strategy for oncologic sternectomy include the need for skin replacement, extent of the bony sternectomy defect, and status of the internal mammary vessels.
Study Design
We reviewed consecutive oncologic sternectomy reconstructions performed at The University of Texas MD Anderson Cancer Center over a 10-year period. Regression models analyzed associations between patient, defect, and treatment factors and outcomes in order to identify patient and treatment selection criteria. We developed a generalized management algorithm based on these data.
Results
Forty-nine consecutive patients underwent oncologic sternectomy reconstruction (mean follow-up = 18±23 months). More sternectomies were partial (74%) rather than total/sub-total (26%). Most defects (N=40, 82%) required skeletal reconstruction. Pectoralis muscle flaps were most commonly employed for sternectomies with intact overlying skin (64%) and infrequently used when a presternal skin defect was present (36%; p=0.06). Free flaps were more often used for total/sub-total versus partial sternectomy defects (75% vs. 25%, respectively; p=0.02). Complication rates for total/sub-total sternectomy and partial sternectomy were equivalent (46% vs. 44%, respectively; p=0.92).
Conclusions
Despite more extensive sternal resections, total/sub-total sternectomies resulted in equivalent postoperative complications when combined with the appropriate soft tissue reconstruction. Good surgical and oncologic outcomes can be achieved with defect-characteristic-matched reconstructive strategies for these complex oncologic sternectomy resections.
Background
Plastic Surgeons and patients increasingly use social media. Despite evidence implicating its importance in Plastic Surgery, the large amount of data has made social media difficult to study.
Objectives
This study seeks to provide a comprehensive assessment of Plastic Surgery content throughout the world using techniques for analyzing large-scale data.
Methods
‘#PlasticSurgery’ was used to search public Instagram posts. Metadata was collected from posts between December 2018 and August 2020. In addition to descriptive analysis, we created two instruments to characterize textual data: a multi-lingual dictionary of procedural hashtags and a rule-based text classification model to categorize the source of the post.
Results
Plastic Surgery content yielded more than 2 million posts, 369 million likes, and 6 billion views globally over the 21-month study. The United States had the most posts of 182 countries studied (26.8%, 566,206). Various other regions had substantial presence including Istanbul, Turkey, which led all cities (4.8%, 102,208). Our classification model achieved high accuracy (94.9%) and strong agreement with independent raters (κ= 0.88). Providers accounted for 40% of all posts (847,356) and included Physician (28%), Plastic Surgery (9%), Advanced-Practice-Practitioners and Nurses (1.6%), Facial Plastics (1.3%), and Oculoplastics (0.2%). Content between Plastics and non-Plastics groups demonstrated high textual similarity, and only 1.4% of posts had a verified source.
Conclusions
Plastic Surgery content has immense global reach in social media. Textual similarity between groups coupled with the lack of an effective verification mechanism presents challenges in discerning the source and veracity of information.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.