Hypertensive disorder of pregnancy (HDP) involves the presence of hypertension during pregnancy and persists for up to 12 weeks after delivery [1]. HDP is typically classified into four subtypes: chronic hypertension, gestational hypertension, preeclampsia, and chronic hypertension with superimposed preeclampsia. Chronic hypertension with superimposed preeclampsia is characterized by chronic hypertension accompanied by organ damage or proteinuria [1, 2, 3]. Severe preeclampsia is commonly defined as preeclampsia associated with any of the following: severe hypertension (i.e., systolic blood pressure $\ge$160 mmHg and/or diastolic blood pressure $\ge$110 mmHg), thrombocytopenia [platelet (PLT) count 100,000/µL], impaired liver function, severe and persistent right upper quadrant or epigastric pain unexplained by other diagnoses, renal insufficiency (serum creatinine concentration $>$1.1 mg/dL or a doubling of the serum creatinine concentration in the absence of another renal disease), pulmonary edema, or new-onset cerebral or visual disturbances, and fetal growth restriction (FGR) [1, 2, 3]. Although the exact pathophysiology and pathogenesis of preeclampsia remain elusive, it is hypothesized that placental dysplasia/abnormality in early pregnancy may lead to placental ischemia and the release of vasoactive substances, resulting in endothelial cell activation and dysfunction.

Red blood cell distribution width (RDW) indicates the fluctuation in red blood cell volume, a sign of complete blood count. It was previously utilized for the differential diagnosis of anemia, but recently, it has been linked to inflammation and oxidative stress, thereby gradually becoming a predictor of incidence rate and mortality in various diseases, particularly cardiovascular diseases [4, 5, 6, 7]. Despite existing studies exploring the correlation between RDW and HDP, these have primarily taken the form of case-control studies with small sample sizes [8, 9, 10]. The objective of this study is to examine the predictive effectiveness of RDW in HDP using the propensity score-matching (PSM) approach.

During the study period, our hospital admitted 20,445 pregnant women, of whom 15,662 met the inclusion criteria. The baseline characteristics of patients before PSM are shown in Supplementary Table 1. Following a 1:1 PSM, the analysis included 1546 women (420, 353, and 773 in the hypertension, preeclampsia, and matched control groups, respectively). The selection process is illustrated in Fig. 1. The baseline characteristics of the enrolled patients post-PSM are presented in Tables 1,2. Except for RDW, other baseline data, including age and complications [SLE, antiphospholipid syndrome (APS), and gestational diabetes mellitus (GDM)], showed no statistically significant differences.

Fig. 1.

Flow chart of patients’ selection.

3.1 RDW in the Simple Hypertension Cohort

The patient characteristics before (Supplementary Table 1) and after (Tables 1,2) PSM are listed. Table 1 displays p-values exceeding 0.05, indicating the absence of statistical differences in all factors between the two groups except for RDWCV1 (p 0.01), and Table 2 displays p-values exceeding 0.05, which supports the absence of statistical differences in all factors between the two groups except for RDWCV1 (p 0.01) and RDWSD (p = 0.03). The influence of other confounding factors on the two groups of data was successfully excluded using PSM. After PSM, none of the basic characteristics were statistically different, and each of the 420 patients was allocated to either the simple hypertension group or the corresponding control group. After PSM, univariate logistic regression analysis of the uncorrected variables revealed no significant correlation between RDW and gestational or chronic hypertension (Tables 1,3). ROC curve analysis demonstrated that the area under the curve (AUC) of RDWCV was 0.555 and that of RDWSD was 0.513. This suggested that the diagnostic value of RDW for gestational or chronic hypertension was comparatively low (Fig. 2A, Supplementary Table 2).

Table 3. Univariable logistic regression result.

Comparison	Characteristics	Beta	SE	score	OR (95% CI)	p
Control vs. simple hypertension group	RDWCV1	0.12	0.07	1.81	1.13 (0.99, 1.28)	0.07
	Gestation days	0.01	0.00	1.18	1.01 (0.99, 1.01)	0.24
	Length of stay	0.02	0.02	1.10	1.02 (0.99, 1.05)	0.27
Control vs. preeclampsia group	RDWCV1	0.16	0.05	3.00	1.18 (1.06, 1.31)	0.01
	RDWSD	0.05	0.01	3.29	1.05 (1.02, 1.08)	0.01
	Gestation days	0.00	0.00	–0.76	1.00 (1.00, 1.00)	0.45
	Length of stay	0.00	0.01	0.20	1.00 (0.98, 1.02)	0.84

Simple hypertension group: including gestational hypertension and chronic hypertension.

Preeclampsis group: including preeclampsis, severe preeclampsis, chronic hypertension with superimposed preeclampsis.

OR, odds ratio.

Fig. 2.

The receiver operating characteristic (ROC) curve analysis of red blood cell distribution width (RDW) in hypertensive disorders of pregnancy (HDP). (A) In gestational hypertension or chronic hypertension. (B) In severe preeclampsia. (C) In preeclampsia (non-severe preeclampsia). (D) Chronic hypertension with superimposed preeclampsia. RDWCV, red blood cell distribution width coefficient of variation; RDWSD, red blood cell distribution width standard deviation; AUC, area under the curve; TPR, true positive rate; FPR, false positive rate.

Preeclampsia is one of the most serious complications of pregnancy and poses significant risks to both maternal and fetal health. Early detection can enhance prognosis, although exploratory research with samples from established cases has identified potential biomarkers [such as soluble fms-like tyrosine kinase-1 (sFlt1)/placental growth factor (PlGF) ratio, PlGF alone, alpha-fetoprotein (AFP)/pregnancy-associated plasma protein-A (PAPP-A) ratio, placental protein 13 (PP 13), and growth differentiation factor 15 (GDF I5)] [11]. However, no ideal predictive biomarkers have been identified.

Several studies have explored the relationship between RDW and HDP, primarily using case-control designs with limited sample sizes [8, 9, 10], yielding inconsistent conclusions [12]. A meta-analysis indicated that RDW levels correlated with various HDP subtypes except for preeclampsia [13]. Mechanistically, RDWCV, calculated as (standard deviation of red blood cell volume/mean cell volume) $\times$ 100%, reflects both the distribution width and mean cell volume. Consequently, a homogeneous red blood cell population with a low mean corpuscular volume (MCV) may yield an elevated RDWCV, whereas a heterogeneous population with a high MCV may show normal values. In contrast, RDWSD (measured in fL) directly quantifies the RDW independent of the MCV, providing a more precise reflection of anisocytosis. Globally, both indices are used clinically without a consensus, justifying our dual assessment. Although no significant correlation was observed between RDW and non-preeclamptic hypertension (gestational or chronic hypertension), a robust association was observed between RDW and preeclampsia. Critically, our analysis revealed distinct clinical performance trade-offs for severe preeclampsia prediction: RDWCV (cutoff $\ge$14.65%) demonstrated moderate sensitivity (79.0%) but limited specificity (51.0%), suggesting utility in ruling out severe disease when negative, whereas RDWSD (cutoff $\ge$51.85 fL) showed high sensitivity (89.0%), but very low specificity (38.0%), indicating potential value for initial screening despite high false-positive rates. These complementary profiles, where high sensitivity compromises specificity, and vice versa, highlight that neither metric achieves optimal standalone diagnostic performance. Nevertheless, both indices effectively differentiated severe preeclampsia from controls at their respective thresholds, supporting the role of RDW as a component of multivariable risk assessment rather than as a definitive diagnostic tool.

HDP is among the most frequent complications during pregnancy, with preeclampsia affecting 3–5% of pregnancies [14, 15, 16]. Currently, it is widely acknowledged that the placenta plays a pivotal role in preeclampsia development. The infiltration of trophoblast cells into the uterine wall during early pregnancy leads to the remodeling of the uterine spiral arteries. If arterial infiltration is impaired or incomplete, hypoxia or reperfusion injury may occur, exacerbating the production of reactive oxygen species and triggering oxidative stress in the placenta. When oxidative stress is initiated, it leads to increased synthesis of pro-inflammatory factors, ultimately resulting in an intensified inflammatory response and endothelial dysfunction, contributing to preeclampsia development [17, 18, 19, 20, 21].

RDW is an easily obtainable and cost-effective hematological parameter that reflects variations in red blood cell volume. A growing body of research has identified a correlation between RDW and hypertension, as well as its severity. Additionally, an elevated RDW is associated with a poorer prognosis in various cardiovascular disorders, including acute myocardial infarction and heart failure. The association between RDW and preeclampsia can be attributed to heightened inflammation and oxidative stress. Inflammation can disrupt iron metabolism, potentially shortening the lifespan of red blood cells and consequently increasing RDW [22, 23]. Inflammation might also hinder erythropoietin production, leading to the release of immature red blood cells into the bloodstream [24, 25]. Additionally, oxidative stress and damage, the key characteristics of preeclampsia, may also contribute to an increase in RDW [26]. Elevated RDW values can reflect disease severity.

This study had certain limitations. First, as a PSM study, unmatched cases from each group were excluded, thereby reducing the overall sample size. Second, this study did not examine the relationship between RDW and patient prognosis. Third, this study was based on a single-center Chinese Han population, which limits the generalizability of our findings. RDW cutoffs may vary across ethnicities owing to genetic differences in erythropoiesis or inflammatory responses. External validation of multiethnic cohorts is essential prior to clinical adoption.

RDW was significantly associated with severe preeclampsia. However, its standalone diagnostic accuracy (AUC 0.661–0.696) remains moderate. Although the low cost, speed, and availability of RDW are advantageous, its primary clinical utility is likely to be as an auxiliary component within combinatorial risk models or multi-marker panels, augmenting rather than replacing established predictors. Future research must prioritize validating the additive prognostic value of RDW in such integrated approaches compared with current standards.

RDW, red blood cell distribution width; HDP, hypertensive disorders of pregnancy; PSM, propensity score-matching; ROC, receiver operating characteristic; AUC, area under the curve; BMI, body mass index; IQR, interquartile range; RDWCV, red blood cell distribution width coefficient of variation; RDWSD, red cell distribution width standard deviation; WBC, white blood cell; SLE, systemic lupus erythematosus; APS, antiphospholipid syndrome; GDM, gestational diabetes mellitus; ICP, intrahepatic cholestasis of pregnancy; OR, odds ratio; FGR, fetal growth restriction; sFlt1, soluble fms-like tyrosine kinase-1; PlGF, placental growth factor; AFP, alpha-fetoprotein; PAPP-A, pregnancy-associated plasma protein-A; GDF I5, growth differentiation factor 15; MCV, mean corpuscular volume; TPR, true positive rate; FPR, false positive rate; PP 13, placental protein 13; NEUT, neutrophil granulocyte; LYMPH, lymphocyte; HGB, hemoglobin; PLT, platelet.

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

BL and HC planned the cohort. BL collected the data. BL, LH, YC, XL, HC analyzed and interpreted the data. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

The study was conducted in accordance with the Declaration of Helsinki. The research protocol was approved by the Ethics Committee of West China Second University Hospital (Ethic Approval Number: 2023154), and all of the participants provided signed informed consent.

Not applicable.

This research received no external funding.

The authors declare no conflict of interest.

Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.31083/CEOG39720.