The predictive effect of red cell distribution width on hypertensive disorders of pregnancy: A propensity score-matching study

Abstract

Abstract Background Red cell distribution width (RDW) is found to be related to inflammation and oxidative stress, and gradually used as a predictor of in cardiovascular diseases. This study aimed at investigated the predicting effects of RDW on hypertensive disorders of pregnancy (HDP). Methods This is a retrospective, propensity score-matching (PSM) cohort study. Cohort 1 studied patients with gestational hypertension/chronic hypertension (named the simple hypertension group), while cohort 2 studied patients with preeclampsia (including preeclampsia, severe preeclampsia, and chronic hypertension patients with preeclampsia). Univariate logistic regression analysis was conducted on variables that were not corrected after PSM. Receiver operating characteristic (ROC) curves were used to explore the predictive ability of RDW for HDP. Results After 1:1 PSM, 1546 women admitted to West China Second University Hospital between January 2021 and January 2022 were enrolled in the analysis, including 420 in the simple hypertension group, 353 in the preeclampsia group, and the remaining 773 in the control group. Univariate logistic regression analysis showed that although there was no significant correlation between RDW and simple hypertension (gestational hypertension and chronic hypertension), there was a significant correlation between RDW and preeclampsia. The ROC curve analysis showed a diagnostic accuracy of RDW coefficient variation (RDWCV) for severe preeclampsia at 72%, with a cutoff value of ≥ 14.65% and AUC = 0.696, and a diagnostic accuracy of RDW standard deviation (RDWSD) for severe preeclampsia at 76%, with a cutoff value of ≥ 51.85fl and AUC = 0.661. Conclusion RDW is significantly correlated with preeclampsia and had a good predictive effect on severe preeclampsia (AUC = 0.7). RDW has the advantages of being fast, low-cost, and easily available, so it can be routinely used for predicting preeclampsia in clinical practice.