Early Prediction of Hypertensive Diseases of Pregnancy by Using Combined Screening Methods in a Rural Population

Abstract

Introduction: The most frequent medical issue during pregnancy is hypertension, which can complicate up to 10% to 15% of pregnancies worldwide. An estimated 14% of all maternal fatalities worldwide are thought to be caused by hypertensive disease of pregnancy, one of the main causes of maternal and fetal morbidity and mortality. Despite the fact that maternal mortality is substantially lower in high-income countries than in low- and middle-income countries, hypertension is still one of the leading causes of maternal death globally. Maternal mortality associated with hypertension fluctuated between 0.08 and 0.42 per 100,000 births between 2009 and 2015. In India, the estimated overall pooled prevalence of HDP was determined to be one out of 11 women, or 11% (95% CI, 5%-17%). Despite various government programs, there is still a high prevalence of hypertension, which calls for stakeholders and healthcare professionals to focus on providing both therapeutic and preventive care. The best solution is to concentrate more on the early detection of pregnancy-related hypertension and to guarantee its universal application so that proper care can be carried out to prevent maternal and fetal morbidity.

Aim: To estimate the predictive value of the combination of maternal characteristics, i.e., mean arterial pressure (MAP), biophysical evaluation (uterine artery Doppler), and biochemical markers (pregnancy-associated plasma protein A (PAPP-A)), in the first trimester of pregnancy for hypertensive diseases of pregnancy.

Methodology: It was a prospective observational study of longitudinal variety that took over 18 months in a tertiary care rural hospital. The number of women admitted to the hospital for labor care during 2019 was 5261. A total of 513 were diagnosed with hypertensive illnesses during pregnancy. At a prevalence rate of 10%, we calculated a sample size of 350 to achieve a sensitivity of 85% with an absolute error of 12.5% at a 95% CI. Maternal histories, such as age, education, socio-economic status, gravidity, and BMI, were taken along with three parameters, i.e., MAP, which was significant above 90 mmHg, uterine artery Doppler, which was taken significant above 1.69, and serum PAPP-A, which was significant at less than 0.69 ml/IU.

Observation and results: We have found that the following are associated with the prediction of hypertension: among the maternal characteristics are advanced age >35 years, presence of body edema, and urine proteins along with MAP, uterine artery pulsatility index (UtA-PI), and PAPP-A are significant. The predictive accuracy of the combination of MAP, UtA-PI, and PAPP-A is also significant. We also found that there is a significant increase in cesarean sections and NICU admissions in hypertensive patients.

Conclusion: A combination of screening parameters, including MAP, UtA-PI, and PAPP-A, to predict early hypertensive disease of pregnancy is developed and tested.

Keywords: doppler ultrasonography; gestational hypertension pregnancy; mean arterial pressure; papp a; predictive model; rural population.

Figure 1. Age-wise distribution

Figure 2. Education-wise distribution

Figure 3. Occupation-wise distribution

Figure 4. Socioeconomic distribution

Figure 5. Gravidity-wise distribution

Figure 6. Marriage duration-wise distribution

Figure 7. BMI-wise distribution

Figure 8. Mean arterial pressure-wise distribution

Figure 9. Pregnancy-associated plasma protein-A-wise distribution (graphical)

Figure 10. Uterine artery pulsatility index-wise distribution (graphical)

Figure 11. ROC curve

ROC: receiver operating characteristic; MAP: mean arterial pressure; PAPP-A: pregnancy-associated plasma protein-A; PI: pulsatility index.

Figure 12. Distribution of systolic blood pressure in normotensive women

Figure 13. Distribution of diastolic blood pressure in normotensive women

Figure 14. Distribution of systolic blood pressure in hypertensive women

Figure 15. Distribution of diastolic blood pressure in hypertensive women

Figure 16. Body edema-wise distribution (graphical)

Figure 17. Urine protein-wise distribution (graphical)