One of the most important aims in oncology should be the quality of life, even in the cases of limited life expectancy. With this objective, the Authors report their experience of immediate breast reconstruction after surgical treatment for neoplasms and "high risk" lesions. In 76 cases they analyzed aesthetic results and morbidity. In immediate reconstruction after Patey mastectomies, the tissue expanders offered good cosmetic results with an acceptable complication rate in comparison with more complex methods as myocutaneous flaps. These flaps represent the alternative in selected cases of Halsted mastectomies, where the mutilation is not acceptable to the patient. In "high risk" lesions surgical approach, namely subcutaneous mastectomy, may be proposed in selected cases only. The Authors emphasize that subcutaneous mastectomy with an immediate submuscular reconstruction offer good aesthetic results especially in small size breasts with mild ptosis. The capsular contracture is however significant in 25% of the patients treated with these techniques.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Objective: This quality improvement initiative aimed to increase the rate of provider screening and documentation of contraception use for reproductive-aged women seen in an academic rheumatology fellows' clinic to >50% by 24 weeks, with sustained improvement at one year.
Methods: With a multidisciplinary team, we devised and implemented six interventional cycles over 24 weeks informed by key stakeholder survey responses. The primary outcome measure was the percentage of eligible visits with contraception information documented in the structured electronic health record field.
Artificial intelligence and machine learning capabilities in the detection of acute scaphoid fracture: a critical review.
J Hand Surg Eur Vol
January 2025
Clinical Scientific Computing, Guy's and St Thomas' NHS Foundation Trust, London, UK.
This paper discusses the current literature surrounding the potential use of artificial intelligence and machine learning models in the diagnosis of acute obvious and occult scaphoid fractures. Current studies have notable methodological flaws and are at high risk of bias, precluding meaningful comparisons with clinician performance (the current reference standard). Specific areas should be addressed in future studies to help advance the meaningful and clinical use of artificial intelligence for radiograph interpretation.
View Article and Find Full Text PDFUse of artificial intelligence to predict outcomes in mild aortic valve stenosis.
Eur Heart J Digit Health
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
Aims: Aortic stenosis (AS) is a common and progressive disease, which, if left untreated, results in increased morbidity and mortality. Monitoring and follow-up care can be challenging due to significant variability in disease progression. This study aimed to develop machine learning models to predict the risks of disease progression and mortality in patients with mild AS.
View Article and Find Full Text PDFMachine learning approaches for risk prediction after percutaneous coronary intervention: a systematic review and meta-analysis.
Eur Heart J Digit Health
January 2025
Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
Aims: Accurate prediction of clinical outcomes following percutaneous coronary intervention (PCI) is essential for mitigating risk and peri-procedural planning. Traditional risk models have demonstrated a modest predictive value. Machine learning (ML) models offer an alternative risk stratification that may provide improved predictive accuracy.
View Article and Find Full Text PDFPredicting Factors Affecting Survival Rate in Patients Undergoing On-Pump Coronary Artery Bypass Graft Surgery Using Machine Learning Methods: A Systematic Review.
Health Sci Rep
January 2025
Department of Cardiac Surgery, School of Medicine Hamadan University of Medical Sciences Hamadan Iran.
Background And Aim: Coronary artery bypass grafting (CABG) is a key treatment for coronary artery disease, but accurately predicting patient survival after the procedure presents significant challenges. This study aimed to systematically review articles using machine learning techniques to predict patient survival rates and identify factors affecting these rates after CABG surgery.
Methods: From January 1, 2015, to January 20, 2024, a comprehensive literature search was conducted across PubMed, Scopus, IEEE Xplore, and Web of Science.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!