Successful treatment algorithm for evaluation of early pregnancy after in vitro fertilization

Abstract

Objective: To evaluate a prospectively implemented clinical algorithm for early identification of ectopic pregnancy (EP) and heterotopic pregnancy (HP) after assisted reproductive technology (ART).

Design: Analysis of prospectively collected data.

Setting: Academic medical center.

Patient(s): All ART-conceived pregnancies between January 1995 and June 2013.

Intervention(s): Early pregnancy monitoring via clinical algorithm with all pregnancies screened using human chorionic gonadotropin (hCG) levels and reported symptoms, with subsequent early ultrasound evaluation if hCG levels were abnormal or if the patient reported pain or vaginal bleeding.

Main outcome measure(s): Algorithmic efficiency for diagnosis of EP and HP and their subsequent clinical outcomes using a binary forward stepwise logistic regression model built to determine predictors of early pregnancy failure.

Result(s): Of the 3,904 pregnancies included, the incidence of EP and HP was 0.77% and 0.46%, respectively. The algorithm selected 96.7% and 83.3% of pregnancies diagnosed with EP and HP, respectively, for early ultrasound evaluation, leading to earlier treatment and resolution. Logistic regression revealed that first hCG, second hCG, hCG slope, age, pain, and vaginal bleeding were all independent predictors of early pregnancy failure after ART.

Conclusion(s): Our clinical algorithm for early pregnancy evaluation after ART is effective for identification and prompt intervention of EP and HP without significant over- or misdiagnosis, and avoids the potential catastrophic morbidity associated with delayed diagnosis.

Keywords: ART; IVF; algorithm; ectopic; heterotopic.