Predictive value of ophthalmic artery Doppler velocimetry in relation to development of pre-eclampsia

Objective To test the hypothesis that ophthalmic artery Doppler velocimetry is predictive of the development of pre-eclampsia (PE). Methods This was a prospective cohort study that included pregnant women in the second trimester who had risk factors for PE. Seven ophthalmic artery Doppler parameters, in addition to uterine artery (UtA) Doppler and clinical variables, were investigated for their prognostic value with respect to PE. Results A total of 347 women were recruited, of whom 40 developed PE. A comparison of the mean ophthalmic artery Doppler parameter values between women with and those without PE showed statistically significant differences in several parameters: peak systolic velocity, end-diastolic velocity, mean velocity, peak mesodiastolic velocity (PMDV) and peak ratio. After adjusting for confounding variables, only PMDV remained statistically significant (P < 0.001), with an area under the receiver-operating characteristics curve (AUC) of 0.73. The best cut-off for predicting PE was a PMDV of >22.11 cm/s, with sensitivity of 70%, specificity of 75%, positive likelihood ratio of 2.8, negative likelihood ratio of 0.4, positive predictive value of 28% and negative predictive value of 95%. The AUC increased from 0.72 to 0.78 when the PMDV was incorporated into a prediction model based on clinical variables, demonstrating that this marker increased the discriminatory capability of the model. The performance of ophthalmic artery Doppler was similar to that of UtA Doppler for predicting PE. Additionally, the AUC increased significantly from 0.82 to 0.88 when the PMDV was incorporated into the model containing clinical variables and UtA Doppler indices. Conclusion A high ophthalmic artery PMDV in the second trimester of pregnancy is an independent predictor of PE that increases the discriminatory ability of clinical markers, as well as of models that include clinical variables and UtA Doppler indices. Copyright (C) 2014 ISUOG. Published by John Wiley & Sons Ltd.