Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jun 25;26(13):6115.
doi: 10.3390/ijms26136115.

Evaluating an Early Risk Model for Uncomplicated Hypertension in Pregnancy Based on Nighttime Blood Pressure, Uric Acid, and Angiogenesis-Related Factors

Affiliations

Evaluating an Early Risk Model for Uncomplicated Hypertension in Pregnancy Based on Nighttime Blood Pressure, Uric Acid, and Angiogenesis-Related Factors

Isabel Fernandez-Castro et al. Int J Mol Sci. .

Abstract

Uncomplicated hypertension (UH) during pregnancy represents a common condition, worsening maternal and fetal prognosis. However, no single biomarker has proven optimal for determining the risk of UH. We developed an early risk multivariate model for UH, integrating hemodynamics with biochemistry, focusing on the relationship between blood pressure (BP) indices, uric acid (UA), and angiogenesis-related factors (AF). We collected and analyzed data on 24 h ambulatory BP monitoring, demographic, epidemiological, clinical, and laboratory variables from 132 pregnancies. The main predictors were BP indices and serum UA and AF levels. Uncomplicated hypertension, defined as the presence of gestational hypertension or worsening of essential hypertension beyond the 20th week, was the main outcome. The combined second-degree polynomial transformation of UA and the AF (sFlt-1/PIGF) ratio, called the UA-AF Index, consistently showed a positive association with UH. The models incorporating nighttime BP indices combined with the UA-AF Index outperformed the others, with the best-performing model based on the nocturnal systolic BP (SBP). Specifically, in the best-fitting model (nighttime SBP + UA-AF Index as predictors), each 1 mmHg increase in nocturnal SBP was associated with a 10% higher risk of UH, while each one-unit increase in the UA-AF Index raised the likelihood of UH by more than twofold (accuracy: 0.830, AUC 0. 874, SE 0.032, p-value < 0.001, 95%CI 0.811-0.938). The combination of nighttime blood pressure indices, serum uric acid, and angiogenesis-related factors may provide added value in the assessment of uncomplicated hypertension during pregnancy.

Keywords: angiogenesis; blood pressure; gestational; hypertension; monitoring; nighttime; pregnancy; uric acid.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Comparison of blood pressure indices between patients with uncomplicated hypertension: no (blue) and yes (green). (a) Office and out-of-office blood pressure indices; (b) nighttime blood pressure dipping. Results marked with ** reached a p-value of less than 0.05. The numerical values of all indices are shown in Supplementary Table S1. UH—uncomplicated hypertension; BP—blood pressure; SBP—systolic BP; off-SBP—office SBP; 24-hSBP—24 h SBP; dSBP—daytime SBP; nSBP—nighttime SBP; DBP—diastolic BP; off-BDP—office DBP; 24-hDBP—24 h DBP; dDBP—daytime DBP; nDBP—nighttime DBP; mmHg—millimeter of mercury; %—percentage.
Figure 2
Figure 2
Visual representation of the combined polynomial transformations based on uric acid (UA) and the angiogenesis-related factors (AF) ratio (the UA-AF Index) for UH according to AUC and accuracy metrics. All performance metrics (Accuracy, AUC, and Log loss) correspond to the mean out-of-fold results obtained through fivefold stratified cross-validation. Note that the model based on the second-order polynomial transformation achieved the closest match between train and test accuracy. AUC—area under the curve; UH—uncomplicated hypertension; UA-AF Index—uric acid and angiogenesis-related factors ratio index.
Figure 3
Figure 3
ROC curves for the logistic regression models based on blood pressure indices and the UA-AF Index (Table 3) for predicting UH. (a) Office and nighttime SBP indices: Off-SBP: AUC 0.731, SE 0.044, p-value < 0.001, 95%CI 0.644–0.817; off-SBP + UA-AF index: AUC 0.800, SE 0.038, p-value < 0.001 95%CI 0.725–0.875; nSBP: AUC 0.831, SE 0.037, p-value < 0.001, 95%CI 0.757–0.904; nSBP + UA-AF index: AUC 0.874, SE 0.032, p-value < 0.001, 95%CI 0.811–0.938; (b) office and nighttime DBP indices: Off-DBP: AUC 0.752, SE 0.042, p-value < 0.001, 95%CI 0.670–0.835; off-DBP + UA-AF index: AUC 0.818, SE 0.036, p-value < 0.001, 95%CI 0.747–0.888; nDBP: AUC 0.824, SE 0.037, p-value < 0.001, 95%CI 0.753–0.896; nDBP + UA-AF index: AUC 0.866, SE 0.032, p-value < 0.001, 95%CI 0.804–0.929. Results marked with ** reached a p-value of less than 0.05. ROC—receiver operating characteristics; UA-AF Index—uric acid and angiogenesis-related factors ratio index; UH—uncontrolled hypertension. AUC—area under the curve; SE—standard error; CI—confidence interval; BP—blood pressure; SBP—systolic blood pressure; off-SBP—office SBP; nSBP—nighttime SBP; DBP—diastolic blood pressure; off-DBP—office DBP; nDBP—nighttime DBP.
Figure 4
Figure 4
Bayesian inference on the models’ accuracy comparing (a) nighttime SBP + UA-AF Index (accuracy 0.83, 95% credible interval [0.760–0.887]) versus office SBP (Accuracy 0.69, 95% credible interval [0.605–0.762]), posterior probability that Model 1 > Model 2: 0.997, 95% credible interval for the accuracy difference [0.040–0.242]; (b) nighttime DBP + UA-AF Index (accuracy 0.80, 95% credible interval [0.726–0.861]) versus office SBP (accuracy 0.68, 95% credible interval [0.597–0.755]), posterior probability that Model 1 > Model 2: 0.988, 95% credible interval for the accuracy difference [0.014–0.223]; SBP—systolic blood pressure; DBP—diastolic blood pressure; Off-SBP—office SBP; Off-DBP—office DBP; nSBP—nighttime SBP; nDBP—nighttime DBP; UA-AF = uric acid and angiogenesis-related factors ratio index.

Similar articles

References

    1. Wu P., Green M., Myers J.E. Hypertensive disorders of pregnancy. BMJ. 2023;381:e071653. doi: 10.1136/bmj-2022-071653. - DOI - PubMed
    1. Agrawal A., Wenger N.K. Hypertension During Pregnancy. Curr. Hypertens. Rep. 2020;22:64. doi: 10.1007/s11906-020-01070-0. - DOI - PubMed
    1. Sanghavi M., Rutherford J.D. Cardiovascular physiology of pregnancy. Circulation. 2014;130:1003–1008. doi: 10.1161/CIRCULATIONAHA.114.009029. - DOI - PubMed
    1. Qu H., Khalil R.A. Vascular mechanisms and molecular targets in hypertensive pregnancy and preeclampsia. Am. J. Physiol. Heart Circ. Physiol. 2020;319:H661–H681. doi: 10.1152/ajpheart.00202.2020. - DOI - PMC - PubMed
    1. Penny J.A., Halligan A.W., Shennan A.H., Lambert P.C., Jones D.R., de Swiet M., Taylor D.J. Automated, ambulatory, or conventional blood pressure measurement in pregnancy: Which is the better predictor of severe hypertension? Am. J. Obstet. Gynecol. 1998;178:521–526. doi: 10.1016/S0002-9378(98)70432-6. - DOI - PubMed

LinkOut - more resources