In Journal of minimally invasive gynecology ; h5-index 40.0
STUDY OBJECTIVE : To establish a clinically relevant prediction score for the diagnosis of adnexal torsion (AT) of women operated on for suspected AT.
DESIGN : A retrospective cohort between 2014 and 2021.
SETTING : A large tertiary teaching medical center.
PATIENTS : Women who underwent urgent laparoscopy for suspected AT INTERVENTIONS: Analyses included univariate and multivariable models combined with the machine learning (ML) Random Forest model which included all information available about the women and reported the accuracy of the model and the importance of each variable. Based on this model we created a predictive score and evaluated its accuracy by receiver operating characteristic (ROC) curve.
MEASUREMENTS AND MAIN RESULTS : A total of 503 women were included in our study, of which 244 (49%) were diagnosed with AT during the surgery and 44 (8.8%) cases of necrotic ovary were found. Based on the Random Forrest and multivariable models the most important pre-operative clinical predictive variable for AT was vomiting, left-side complaints, and concurrent pregnancy; cervical tenderness and urinary symptoms decreased the likelihood of surgically confirmed AT. The most important sonographic findings were ovarian edema and decreased vascular flow; hemorrhagic corpus luteum decreased the likelihood of surgically confirmed AT. The accuracy of the Random Forest model was 71% for the training set and 68% for the testing set, and the area under the curve for the multivariable model was 0.75 (95%CI 0.69-0.80). Based on these models we created a predictive score with a total score that ranges from -4 to 12 points. The area under the curve for this score was 0.72 (95%CI 0.67-0.76), and the best cutoff for the final score was > 5 points with sensitivity/specificity/PPV/NPV of 64%/73%/70%/67%.
CONCLUSION : Clinical characteristics and ultrasound findings may be incorporated into the emergency room workup of women with suspected AT. ML in this setting has no diagnostic/predictive advantage over the performance of logistic regression methods. Further prospective studies to strengthen the accuracy of this model are needed.
Atia Ohad, Hazan Ella, Rotem Reut, Armon Shunit, Yagel Simcha, Grisaru-Granovsky Sorina, Sela Hen Y, Rottenstreich Misgav
2023-Feb-10
Adnexal torsion, Laparoscopy, Prediction, Scoring, Ultrasound
