Obstetrical Outcomes Among Asherman's Syndrome Patients: Comparing Classification Systems and Developing a Novel Calculator

Study Objective To compare the March Classification and ASRM Classification of Asherman's Syndrome as predictors of pregnancy and live birth, and to develop an obstetrical outcomes calculator. Design Cross-sectional observational study. Setting Outpatient minimally invasive gynecological surgery (MIGS) clinic Patients or Participants Asherman's Syndrome patients (n=127). Interventions Office hysteroscopic lysis of adhesions (LOA). Measurements and Main Results Patients were classified as “mild,” “moderate,” or “severe,” following both the March and ASRM classifications. Inconsistencies between March and ASRM classifications were found in 37.8% of patients. Model fit was assessed using Akaike information criterion (AIC), where lower AIC indicated better fit. Based on multivariable logistic regression analyses and controlling for confounding, the March Classification model was a stronger predictor of both pregnancy (AIC: 117.6 vs. 178.6) and live birth (AIC: 178.6 vs 178.9) following office hysteroscopic LOA than the ASRM Classification model. To address these discrepancies, patient medical history and obstetric/gynecologic history, presumed etiology, and cavity involvement were used to develop new models for pregnancy (AIC: 112.1) and live birth (AIC: 173.0). Using the estimates from the logistic regression, an Asherman's Syndrome obstetrical outcomes calculator was created to predict the probability of pregnancy and live birth following office hysteroscopic LOA. Conclusion First, this study underscores discrepancies between the March and ASRM classification systems regarding association with obstetrical outcomes; because of such inconsistency, these classification systems may have limited predictive ability and, thus, limited clinical utility. This study then offers a novel model for predicting obstetrical outcomes among Asherman's Syndrome patients who have undergone office hysteroscopic LOA, and we present it as a proof-of-concept calculator. This calculator has promising potential as a clinical tool. Limitations and areas to build upon include larger sample size and accounting for potential confounders.