Kim SY, et al. J Korean Med Sci. 2021 Oct;36(44):e281. https://doi.org/10.3346/jkms.2021.36.e281

Wie JH, et al. Yonsei Med J. 2022 Aug;63(8):735-743. https://doi.org/10.3349/ymj.2022.63.8.735

Background/Objectives: Diagnosing interstitial pregnancy (IP) using ultrasonography can be challenging, as it is often mistaken for eccentrically located intrauterine pregnancy (IUP). In this retrospective cohort study, we aimed to develop a predictive scoring model using multiple clinical factors to enhance the diagnosis of IP and facilitate timely interventions in suspected cases. Methods: We enrolled 63 pregnant women with a diagnosis of suspected IP who visited a single tertiary center between January 2006 and December 2023. Data on the clinical risk factors, symptoms, laboratory test results, and ultrasound findings were analyzed. A statistical predictive score was developed using logistic regression analysis with feature selection based on the least absolute shrinkage and selection operator to optimize the predictive accuracy and clinical applicability. Results: From a total of 12 factors, a scoring model was constructed from the three most prominent factors—ultrasound findings showing no surrounding endometrium, myometrial thinning of less than 5 mm, and vaginal bleeding—all of which demonstrated high feature importance. This predictive score identified IP with a negative predictive value of 0.950 in the low-risk group and a positive predictive value of 1.000 in the high-risk group, whereas the overall area under the curve was 0.998 (95% confidence interval, 0.992–1.000). Conclusions: The statistically derived predictive model––ultrasound showing no surrounding endometrium and myometrial thinning < 5 mm combined with vaginal bleeding––demonstrated high accuracy and practical applicability for IP diagnosis, providing a robust tool to enhance clinical decision-making and optimize routine management strategies for IP.

Hong S, et al. J Korean Med Sci. 2024 Jul;39(34):e236. https://doi.org/10.3346/jkms.2024.39.e236

Lee SJ, et al. J Korean Med Sci. 2023 Sep;38(38):e300. https://doi.org/10.3346/jkms.2023.38.e300

Pyeon SY, et al. Perinatology. 2025 Jun;36(2):52-61. https://doi.org/10.14734/PN.2025.36.2.52