Recurrence of Endometriosis (Symptoms and Imaging) in Post-Surgical Patients With and Without Hysterectomy: A Retrospective Study

• Grant number: 25/03392-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2025
• End date: April 30, 2026
• Field of knowledge: Health Sciences - Medicine
• Principal Investigator: Maurício Simões Abrão
• Grantee: Gabriela Nicole Valverde Avelar
• Host Institution: Hospital de Beneficência Portuguesa de São Paulo. Real e Benemérita Associação Portuguesa de Beneficência de São Paulo (RBAPB). São Paulo , SP, Brazil

Abstract

IntroductionEndometriosis is a benign gynecological disease characterized by the presence of endometrial cells outside the uterus. It is a chronic inflammatory condition with symptoms such as chronic pelvic pain, dysmenorrhea, dyspareunia, dyschezia, dysuria, and infertility. This disease negatively impacts patients' psychosocial well-being and reduces their quality of life. Currently, the literature provides limited information on long-term outcomes following endometriosis surgery. Patients interested in preserving the uterus have a strong interest in understanding the likelihood of endometriosis recurrence, which could lead to additional surgeries, including hysterectomy. Objective To evaluate the recurrence of endometriosis symptoms and lesions in patients who underwent surgical treatment with hysterectomy compared to those who preserved the uterus during the procedure. MethodsThis study involves a retrospective analysis of patients who underwent surgical treatment for endometriosis between 2010 and 2022 at Hospital Beneficência Portuguesa de São Paulo and Clínica Medicina da Mulher. Patients will be selected from the previously tabulated Redcap database, and follow-up data at 0, 3, 6, 12, and 24 months, as well as more than 5 years post-procedure, will be retrieved retrospectively from the Tasy electronic medical records. The study will assess pain symptoms, quality of life (SF-36), lesion recurrence through imaging exams, and reoperation rates during follow-up. Data will be analyzed using the Student's t-test, mixed linear analysis, and Kaplan-Meier survival analysis.