Tayma Ibrahem, Ragda Samnia, Zeky Mishakry - First Place
Advisor - Dr. Adir Solomon
Department of Information Systems
Data-Driven Approach for Analyzing Infections in Prosthetic Breast Reconstructions
Tayma Ibrahem1; Ragda Samnia1; Zeky Misharky1 ;Emad Khoury2; Dr. Adir Solomon1
1Department of Information Systems, University of Haifa, Haifa, Israel; 2Bnai Zion Medical Center
Infections following prosthetic breast reconstruction present significant challenges that can lead to breast loss, necessitating delayed reconstruction or even abandonment of reconstruction efforts. This retrospective study examines patients who underwent full mastectomy (either therapeutic or prophylactic) along with immediate alloplastic breast reconstruction. This work aims to identify risk factors for post-operative infections and evaluate the effectiveness of various treatment options.
Utilizing machine learning techniques, we develop a predictive model to identify patients at high risk of infection based on clinical and surgical parameters. These parameters include patient attributes such as age, body mass index (BMI), diabetes, smoking status, and exposure to radiation, as well as surgical details like the type of hospital and acellular dermal matrix. By analyzing these diverse factors, we provide a comprehensive understanding of the infection risks associated with different reconstruction methods.
The comparison between single-stage and two-stage reconstructions allows for the assessment of the outcomes of antibiotic treatment alone versus antibiotic treatment combined with implant replacement or removal. Additionally, we explore the impact of various treatment approaches on the rate of salvage for infected reconstructions, offering insights into the optimal management strategies.
Our data-driven approach not only aims to improve the prediction of infection risk but also to refine treatment protocols, ultimately contributing to the development of standardized guidelines that can enhance patient outcomes and reduce medical complications. By providing a detailed analysis of the factors influencing post-operative infections, this research offers valuable information for clinicians and helps in the formulation of targeted interventions to improve the success rates of prosthetic breast reconstructions.