Xin Wang, Liyuan Ma, Siting Peng, Yuqing Yang, Jihao Wu, Na Su, Zhenhong Qi, Xinyan Liu, Qing Dai, Jianchu Li, Zhenzhen Liu
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引用次数: 0
Abstract
Objectives: Cesarean scar pregnancy (CSP) refers to a special type of pregnancy with a variable prognosis. We aimed to establish a prognostic classification system using ultrasound and clinical features to provide a reference for management strategies.
Methods: Exactly 230 patients with CSP were included and categorized into three groups based on treatment and prognosis: Group A (favorable prognosis), Group B (moderate prognosis), and Group C (poor prognosis). A total of 26 ultrasound features and 8 clinical features were collected for further analysis. Machine learning and traditional scoring models were then constructed for Group A and Group C and integrated to predict CSP prognosis using the significant features.
Results: In the univariate analysis, 26 variables were significantly correlated with Group C, while 21 variables were significantly correlated with Group A. For Group C, a linear scoring model was established using three key features: the criteria length of the implantation portion (IMPL) ≥2.43 cm, the height of the gestational sac or mass protruding above the uterine cavity line (GSUCL) ≥1.4 cm, and absent residual myometrial thickness (RMT), achieving an area under the curve (AUC) of 0.939 (0.872, 1.000), which demonstrated comparable performance to the machine learning model (P = .814). For Group A, 13 significant univariate variables were utilized to construct the machine learning model with an AUC of 0.917 (0.842, 0.993).
Conclusion: Multiple features were associated with CSP prognosis, such as GSUCL, IMPL, RMT, and the anterior-posterior diameter of the gestational sac at the level of the niche (GSSH). The CSP prognostic prediction can be achieved by integrating machine learning and linear scoring models to balance performance and interpretability, which can assist clinicians in treatment decisions.
期刊介绍:
The Journal of Ultrasound in Medicine (JUM) is dedicated to the rapid, accurate publication of original articles dealing with all aspects of medical ultrasound, particularly its direct application to patient care but also relevant basic science, advances in instrumentation, and biological effects. The journal is an official publication of the American Institute of Ultrasound in Medicine and publishes articles in a variety of categories, including Original Research papers, Review Articles, Pictorial Essays, Technical Innovations, Case Series, Letters to the Editor, and more, from an international bevy of countries in a continual effort to showcase and promote advances in the ultrasound community.
Represented through these efforts are a wide variety of disciplines of ultrasound, including, but not limited to:
-Basic Science-
Breast Ultrasound-
Contrast-Enhanced Ultrasound-
Dermatology-
Echocardiography-
Elastography-
Emergency Medicine-
Fetal Echocardiography-
Gastrointestinal Ultrasound-
General and Abdominal Ultrasound-
Genitourinary Ultrasound-
Gynecologic Ultrasound-
Head and Neck Ultrasound-
High Frequency Clinical and Preclinical Imaging-
Interventional-Intraoperative Ultrasound-
Musculoskeletal Ultrasound-
Neurosonology-
Obstetric Ultrasound-
Ophthalmologic Ultrasound-
Pediatric Ultrasound-
Point-of-Care Ultrasound-
Public Policy-
Superficial Structures-
Therapeutic Ultrasound-
Ultrasound Education-
Ultrasound in Global Health-
Urologic Ultrasound-
Vascular Ultrasound