All Insights Report Burden of Illness of Intrauterine Adhesions Following Intrauterine Procedures: A Retrospective Analysis of Real-World Data

    Burden of Illness of Intrauterine Adhesions Following Intrauterine Procedures: A Retrospective Analysis of Real-World Data

    RWE, HEOR & Evidence Synthesis

    Burden of Illness of Intrauterine Adhesions Following Intrauterine Procedures: A Retrospective Analysis of Real-World Data

    This study evaluated clinical and economic outcomes of intrauterine adhesions (IUAs) by comparing women undergoing adhesiolysis to those not undergoing uterine procedures, focusing on healthcare resource use and key clinical outcomes over a period from December 2019 to May 2023.

    Download Report
    Burden of Illness of Intrauterine Adhesions Following Intrauterine Procedures: A Retrospective Analysis of Real-World Data

    Intrauterine adhesions (IUAs) occur when scar tissue binds the uterine cavity surfaces, often due to surgery or infections. IUAs can lead to menstrual abnormalities, abdominal pain, infertility, recurrent abortion, and pregnancy complications, resulting in significant healthcare costs. The high recurrence rates and lack of effective treatments make IUAs a substantial clinical and economic burden. This study aimed to evaluate clinical and obstetrical outcomes in women undergoing adhesiolysis compared to those not undergoing uterine procedures, and to determine the overall disease burden regarding healthcare resource use, clinical outcomes, and costs. Key outcomes included rates of absent uterine bleeding, placenta accreta spectrum, postpartum hemorrhage, pregnancies, live births, miscarriages, pre-term deliveries, and cesarean deliveries. The observational study, conducted from before December 2019 through May 2023, involved three cohorts: women who underwent adhesiolysis, procedure-free non-IUA women, and procedure-experienced non-IUA women. Propensity score matching was used to match cohorts based on key characteristics, with clinical and economic outcomes evaluated and compared.

    This report is a poster presentation of Axtria from ISPOR 2024.

    Contact us at connect@axtria.com with any questions.

    Complete the brief form to download the white paper

    Recommended insights

    A Retrospective Analysis of Real-World Data

    Report

    The Use of Natural Language Processing in Literature Reviews

    A Retrospective Analysis of Real-World Data

    Report

    Novel Drug Approvals by the U.S. Food and Drug Administration in Rare Diseases: Findings From 2020–2023

    A Retrospective Analysis of Real-World Data

    Report

    FDA-Approved Artificial Intelligence and Machine Learning-Enabled Medical Devices: An Updated Landscape From 1995 to 2023