Authors: Rijo M Choorakuttil, Shilpa Satarkar, Anjali Gupta, Devarajan P, Lalit K Sharma, Akanksha Baghel, Neelam Jain, Bavaharan R, Praveen K Nirmalan for Team Samrakshan
Author Affiliations
- Rijo M Choorakuttil, National Chairperson for Samrakshan IRIA, AMMA Center for Diagnosis and Preventive Medicine, Kochi, Kerala, India
- Shilpa R Satarkar, Antarang Sonography and Colour Doppler Center, Satarkar Hospital, Plot 20, Tilaknagar, Aurangabad, Maharashtra, India
- Anjali Gupta, Anjali Ultrasound and Colour Doppler centre, 2nd floor, Shanti Madhuban Plaza, Delhi Gate, Agra, Uttar Pradesh, India
- Devarajan P, Nethra Scans and Genetic Clinic, Tiruppur, Tamil Nadu, India
- Lalit K Sharma, Raj Sonography & X- Ray Clinic, Baiju Choraha, Nayapura, Guna, Madhya Pradesh, India
- Akanksha Baghel, Baghel Sonography Center. Front of Janpat Office, near District Hospital, Harda, Madhya Pradesh, India
- Neelam Jain, Jain Ultrasound centre, C-112, B block, Dispensary road Sonari, Jamshedpur Jharkhand, India
- Bavaharan R, Fetocare Magnum Imaging and Diagnostics, Trichy, Tamil Nadu, India
- Praveen K Nirmalan, Chief Research Mentor, AMMA ERF, AMMA Center for Diagnosis and Preventive Medicine, Kochi, Kerala, India
Corresponding Author: Rijo M Choorakuttil, National Chairperson for Samrakshan IRIA, AMMA Center for Diagnosis and Preventive Medicine, Kochi, Kerala, India. E-mail: samrakshaniria@gmail.com
Abstract
Aim: To compare the screen positivity rates in the first trimester using clinic-demographic factors with an algorithm including mean arterial pressure (MAP) and mean uterine artery (UtA) pulsatility index (PI) for early identification of pregnant women at risk for preterm preeclampsia (PE).
Methods: An opportunistic screening program determined clinico-demographic details, MAP and mean UtA PI in the first trimester of pregnancy. Pregnant women were categorized as at high or moderate risk for preterm PE based on the presence of at least one clinico-demographic risk factor. Customized risk estimates derived from the algorithm that included MAP and UtA PI were used to categorize women as at risk for preterm PE based on three cutoff criteria- 1 in 150, 1 in 100 and 1 in 50.
Results: The data of 1,456 pregnant women between 11-13+6 gestation weeks from 7 states in India were analyzed. Two hundred and sixty-seven (18.34%, 95% CI: 16.35, 20.33) women were identified as at risk for preterm PE based on clinico-demographic factors including 87 (5.98%, 95% CI: 4.76, 7.19) women at high risk and 181 (12.43%, 95% CI: 10.73, 14.13) women at moderate risk for preterm PE. The addition of MAP & mean UtA PI identified 495 (34.00%, 95% CI: 31.56, 36.43) women at risk for preterm PE based on a 1 in 150 cutoff and 318 (21.84%, 95% CI: 19.72, 23.97) and 153 (10.51%, 8.93, 12.08) women as at risk based on a 1 in 100 and 1 in 50 cut-offs respectively.
Conclusion: The addition of MAP and mean UtA PI besides clinico-demographic details identify significantly more screen positive pregnant women at risk for preterm PE in this population.
Keywords: Preeclampsia, Screening, Fetal Doppler, Blood Pressure, Uterine Artery
Introduction
Pre-eclampsia (PE) remains a leading cause for maternal morbidity including severe acute maternal morbidity (SAMM) and mortality worldwide.(1) PE affects 2–8% of pregnancies worldwide with a systematic review covering 40 countries and 39 million women reporting an incidence of 4.6% of all deliveries for preeclampsia and 1.4% for eclampsia, while a secondary analysis of WHO data found the combined PE/E prevalence to be 4%. (2,3) PE is associated with 10–15% of direct maternal deaths and up to 25% of stillbirths and newborn deaths in developing countries. (2) Annually, approximately 76,000 mothers die worldwide from PE in the perinatal period.(1) An estimated 500,000 perinatal fetal deaths worldwide are attributed to PE each year.(1) The prevalence of PE is higher in lower resource countries and may be attributed partly to the quality of perinatal care in these countries.(4) Countries with greater resources have a different set of risk factors for PE that include chronic diseases like hypertension, diabetes mellitus, chronic kidney diseases, obesity, advanced maternal age, and artificial modes of conception. Countries in an epidemiological transition like India have an increased prevalence of PE linked to the quality of antenatal care and changing risk factors including metabolic syndromes, elderly mothers, and artificial conception.
The diagnosis of PE is a challenge with several operating definitions applied across populations or even within countries. The International Society for the Study of Hypertension in Pregnancy (ISSHP) definition of PE is recognized for global practice(1) and may lead to standardization of the diagnosis and estimates. Accurate prediction of PE, Early identification of women at risk for PE and uniform access to preventive care are challenges in pregnancy and screening for PE at a community or population level remains disjointed with several approaches and strategies at the national and regional levels.
Samrakshan is a national program of the Indian Radiological and Imaging Association (IRIA) that aims to reduce perinatal mortality in India through an opportunistic screening program focused on PE and Fetal Growth Restriction (FGR) that integrates mean arterial blood pressure measurements (MAP) and fetal doppler studies in the risk estimates.(5) In this manuscript, we compare the screen positivity rate between the conventionally used clinical and demographic risk history profile and a protocol that integrates MAP and mean uterine artery (UtA) pulsatility index (PI) in the 1st trimester, for the early identification of pregnant women at risk for preterm PE.
Methods
Opportunistic screening is offered to pregnant women at Radiology Units as part of Samrakshan either as a walk-in option or as referrals from other medical disciplines. Each woman is assigned a centre specific unique identification number. A detailed personal, medical, and obstetric history is collected from each pregnant woman. The first-trimester screening protocol is offered to pregnant women between 11 and 13+6 gestational weeks. (6) The last menstrual period is ascertained by a recall from the woman and an ultrasound dating scan, and an estimated date of delivery (EDD) is assigned and documented. The EDD, once assigned is not changed thereafter, and forms the basis for further assessments of fetal growth. The fetal crown-rump length (CRL) is measured and fetuses with a CRL <45mm and >84mm are excluded from the program. The MAP is measured using two digital blood pressure reading apparatus, one for each upper arm. Both arms are measured simultaneously and twice with a minimum interval of 1 minute between measurements. The MAP is measured with the woman seated comfortably, feet placed on the ground, in a silent environment. Fetal ultrasound studies focused on the number of fetuses, viability of fetus, fetal growth, fetal environment, and structure are carried out using a transabdominal or transvaginal approach. Fetal Doppler studies are performed simultaneously with a specific focus on the PI of the right and left uterine arteries and a mean uterine artery PI and percentile is determined for each woman. (7)
The clinico-demographic details are transcribed into an online free risk estimator developed by the Fetal Medicine Foundation, UK, to determine individual risk estimates for preterm PE and FGR for each woman.(8) A 1 in 150 cutoff is considered as high risk for the development of preterm PE. Additionally, we considered a 1 in 50 cutoff for severe risk and a 1 in 100 cutoff for moderate risk for the subsequent development of preterm PE. We considered the presence of anyone of PE in a past pregnancy, chronic hypertension, diabetes mellitus, chronic kidney disease, systemic lupus erythematosus and anti-phospholipid syndrome, and artificial conception as high risk for PE. The presence of any one of obesity (body mass index >30kg/m2), family history of PE and maternal age >35 years were considered as moderate risk factors for PE. Multiple pregnancies were not included in this analysis.
The data were transcribed into a secure online google form and converted in real-time to a google spreadsheet. The data was exported into STATA version 12.0 (Stata Corp, Tx, USA) for further analysis. The screen positivity rates, using the clinico-demographic history in isolation and after integration of MAP and mean UtA PI are presented as point estimates and 95% confidence intervals and compared using the test of proportions.
Results
The study included data from 1,456 first trimester pregnant women with a singleton live fetus at gestation ages from 11 to 13+6 weeks from Jharkhand, Kerala, Madhya Pradesh, Maharashtra, Rajasthan, Tamil Nadu, and Uttar Pradesh states of India. The mean age (SD) of women in the study was 27.45 (4.75) years and ranged from 18 to 43 years. The distribution of clinico-demographic factors is presented in Table-1. The screen positivity rates are presented in Table-2.
Table-1: Clinico-demographic factors of the 1,456 first trimester pregnant women screened in Samrakshan
| Factor | N, % |
| Maternal Age >35 years | 110 (7.55%) |
| Maternal Smoking | 19 (1.30%) |
| Family History of PE | 9 (0.62%) |
| In Vitro Fertilization | 30 (2.06%) |
| Ovulation Induction | 8 (0.55%) |
| Chronic Hypertension | 22 (1.51%) |
| Diabetes Mellitus | 8 (0.55%) |
| Systemic Lupus Erythematosus | 3 (0.21%) |
| Anti-phospholipid Syndrome | 3 (0.21%) |
| Obesity | 143 (11.64%) |
| Nulliparous | 843 (57.90%) |
| Preeclampsia in a previous delivery | 23 (3.75%) |
| Mean arterial pressure >95th percentile | 63 (4.33%) |
| Mean Uterine Artery PI >95th percentile | 71 (4.88%) |
Table-2: Screen positivity rates based on the 1,456 first trimester pregnant women screened in the Samrakshan Program
| Bayesian Algorithm | Screen positivity rate, %, | 95% confidence Intervals |
| 1 in 150 cut off | 495 (34.00%) | 31.56, 36.43 |
| 1 in 100 cut off | 318 (21.84%) | 19.72, 23.97 |
| 1 in 50 cut off | 153 (10.51%) | 8.93, 12.09 |
| Clinico-Demographics | ||
| Any Risk | 267 (18.34%) | 16.35, 20.33 |
| High Risk* | 87 (5.98%) | 4.76, 7.19 |
| Moderate Risk** | 181 (12.43%) | 10.73, 14.13 |
* Anyone of PE in a past pregnancy, chronic hypertension, diabetes mellitus, chronic kidney disease, systemic lupus erythematosus and anti-phospholipid syndrome, and artificial conception
** Anyone of obesity (body mass index >30kg/m2), family history of PE and maternal age >35 years
The use of the Bayesian algorithm identified significantly more screen-positive women at risk for preterm PE compared to the use of the clinico-demographic details without MAP and mean uterine artery PI (p<0.001). The use of the 1 in 50 cut off for high risk identified significantly more screen-positive women compared to the high-risk category based on clinico-demographics alone (P<0.001).
Discussion
The management of PE must consider several challenges including progression to eclampsia, development of placental abruption and HELLP syndrome. The decisions about the timing of childbirth must balance fetal maturity, survival, distress, and maternal wellbeing. PE is associated with higher perinatal mortality rates, infant mortality rates, thrombocytopenia, bronchopulmonary dysplasia, cerebral palsy and an increased risk of type 2 diabetes, cardiovascular disease, and obesity in adult life. (1) PE is also associated with health problems in later in the life of the woman, including increased risk of death from future cardiovascular disease, hypertension, stroke, renal impairment, metabolic syndrome and diabetes and a reduced life expectancy. (1) The reported rates of PE in India vary from 8% to 10%. and an estimated 1 to 3 million pregnant women are at risk for adverse events from PE in India annually. (9) PE is a major clinical and public health problem for India and is a priority for the Samrakshan program.
It is currently possible to scale up screening for PE as tools to predict risk and medications to minimize risk are available. The ASPRE trial showed evidence that 150 mg of low dose aspirin at bedtime can minimize the development of preterm PE.(10) A Bayesian competing risk algorithm available online as a free resource allows for the estimation of risk for preterm PE for individuals across most settings and populations.(8) Conventional approaches to identify risk for PE focused on clinico-demographic factors and the presence of at least one high-risk factor or at least two moderate risk factors for PE. Samrakshan, using the competing risk algorithm that included MAP and mean UtA PI in the model, identified significantly more women as screen positive. This is not surprising as the use of clinical history by recall is a subjective measure that may not be reliable in populations with poor health literacy and access to medical documentation.
There are several aspects to consider in the scale-up to screen all pregnant women for risk of PE using the algorithm. The scale-up needs an improved uptake of first-trimester screening of pregnant women between 11 and 14 weeks for early identification of women at risk for PE and to initiate therapy with low dose aspirin. The current uptake of 1st trimester Antenatal care and ultrasound uptake is suboptimal in India. The National Family Health Survey (NFHS)-4 reported a first-trimester antenatal service uptake of 58% and an overall 60% uptake of ultrasound assessments in pregnancy. (11) The screening should incorporate MAP measurement and fetal doppler studies for mean UtA PI. The paradigm of fetal and antenatal assessments must shift from a focus on structural and congenital abnormalities to a more inclusive model that includes fetal growth and environment besides structure. Fetal Doppler assessments must become a routine assessment during pregnancy rather than an on-demand examination. Conventional Blood pressure measurements must be standardized to include estimates of mean arterial blood pressure.
The definition of PE used in clinical settings must be standardized across India. There are several definitions based on several society guidelines in use in India. It is recommended that a single operational definition applicable across different healthcare settings is used. This helps to determine accurate estimates of the incidence of PE and the effectiveness of the screening tools. Guidelines to start low dose aspirin must be standardized across India. The guidelines by FIGO and ISUOG on screening pregnant women are a start in this direction.(1,7) Training programs to standardize fetal ultrasound and doppler studies are important. The training must focus on post-graduate residents and practicing radiologists to ensure supply of high-quality services.
Further studies on detection rates, compliance to low dose aspirin and reduction in incidence and risk for preterm PE are needed from different settings and regions within India. These will help establish the effectiveness of the screening tool and the need to possibly refine parameters of risk used in the algorithm with specific reference to an Asian Indian population.
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