Disease burden of cardiovascular conditions complicating pregnancy in Sri Lanka: a protocol

Ayesh Hettiarachchi; Niroshan Lokunarangoda; Thilini Agampodi; Suneth Agampodi

doi:10.12688/f1000research.52539.4

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Study Protocol

Revised

Disease burden of cardiovascular conditions complicating pregnancy in Sri Lanka: a protocol

[version 4; peer review: 2 approved]

Previous Title: Disease burden and adverse pregnancy outcomes due to cardiovascular conditions complicating pregnancy in Sri Lanka: a protocol

Ayesh Hettiarachchi ¹, Niroshan Lokunarangoda², Thilini Agampodi¹, Suneth Agampodi¹

PUBLISHED 29 Feb 2024

Author details Author details

¹ Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, Anuradhapura, 5008, Sri Lanka
² Department of Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, Anuradhapura, 5008, Sri Lanka

Ayesh Hettiarachchi
Roles: Conceptualization, Investigation, Methodology, Project Administration, Resources, Writing – Original Draft Preparation

Niroshan Lokunarangoda
Roles: Investigation, Methodology, Supervision, Writing – Review & Editing

Thilini Agampodi
Roles: Funding Acquisition, Project Administration, Writing – Review & Editing

Suneth Agampodi
Roles: Conceptualization, Methodology, Project Administration, Supervision, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Background

Cardiovascular diseases (CVD) are the commonest indirect medical cause of maternal deaths worldwide, both in high-income and low and middle-income countries. To minimize the effects of CVD in pregnancy, proper risk assessment and appropriate referral is required. In Sri Lanka, cardiovascular disease complicating pregnancy is a significant cause of maternal mortality, second only to postpartum hemorrhage. Screening for CVD in pregnancy in Sri Lanka is limited to a routine clinical assessment. Evidence-based guidelines are yet to be developed, and this deficit may have resulted in a substantial underestimation of the CVD burden. This study aims to determine the burden of CVD in early pregnancy and develop a risk prediction model to be used in field pregnancy clinics in Sri Lanka to reduce CVD effects in pregnancy.

Methods

A prospective cohort study was carried out in the Anuradhapura district, Sri Lanka. Following registration to the antenatal care, pregnant women fulfilling the eligibility criteria were invited to attend a special clinic at their relevant Medical Officer of Health (MOH) area. Risk assessment was done through history and a clinical examination, and suspected/probable cases were referred for an echocardiogram by a consultant cardiologist. All the recruited participants in the first trimester were prospectively followed up and screened again between 24–28 weeks of the period of amenorrhoea (POA). Antenatal ward admissions with CVD complicating pregnancy will be extracted, and a telephone interview will be carried out between 6–12 weeks after the expected delivery date to cover postpartum morbidities.

Discussion

This proposed study will be the largest of its kind carried out in the local setting. The study's findings will be beneficial for policymakers to develop guidelines to reduce maternal cardiovascular disease morbidities and mortalities in Sri Lanka.

Keywords

maternal, heart disease, pregnancy, cardiovascular, Sri Lanka, Anuradhapura

Corresponding author: Ayesh Hettiarachchi

Competing interests: No competing interests were disclosed.

Grant information: The original study (RaPCo) was supported by the Accelerating Higher Education Expansion and Development (AHEAD) Operation of the Ministry of Higher Education, Sri Lanka, funded by the World Bank.

Copyright: © 2024 Hettiarachchi A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Hettiarachchi A, Lokunarangoda N, Agampodi T and Agampodi S. Disease burden of cardiovascular conditions complicating pregnancy in Sri Lanka: a protocol [version 4; peer review: 2 approved]. F1000Research 2024, 10:1028 (https://doi.org/10.12688/f1000research.52539.4) First published: 11 Oct 2021, 10:1028 (https://doi.org/10.12688/f1000research.52539.1) Latest published: 29 Feb 2024, 10:1028 (https://doi.org/10.12688/f1000research.52539.4)

Revised Amendments from Version 3

In this version of the article, the importance of developing innovative screening modalities for detecting subclinical cardiac dysfunction is included. Particularly, the utilization of strain echocardiographic imaging during the antenatal and postnatal periods of pregnancy is emphasized.

See the authors' detailed response to the review by Anish Keepanasseril
See the authors' detailed response to the review by Andrea Sonaglioni

Introduction

In 2017, an estimated 295,000 (uncertainty interval 279,000–340,000) women died due to pregnancy-related complications, with 86% of these deaths occurring in sub-Saharan Africa and south-east Asia¹. The sustainable development goal target 3.1, reducing the global maternal mortality ratio (MMR) to less than 70 per 100,000 live births United Nations: Transforming our world, seems still too far away with an estimated MMR of 211 per 100,000 live births currently. Despite global interventions, obstetric hemorrhage still accounts for 27·1% (19·9–36·2) of all maternal deaths, followed by hypertension (14·0%, 11·1–17·4), sepsis (10·7%, 5·9–18·6) and abortions (7·9%, 4·7–13·2)². While the direct causes are still contributing to most deaths, 27.5% are due to indirect causes, and the proportion is increasing. Despite this increasing trend, there is little focus by the leading international maternal health non-governmental organizations and UN organizations on these causes³.

Cardiovascular diseases (CVD) are the commonest indirect medical cause of maternal deaths worldwide, both in high-income countries (HIC) and low and middle-income countries (LMIC)². Although CVD affects only 1–4% of pregnant women, cardiomyopathy is reported as a leading cause of indirect maternal death⁴. The general hemodynamic changes during pregnancy with 40–45% increase of blood volume, up to 50% increase in cardiac output, 15–30% increase in heart rate together with changes in vascular resistance, renal blood flow, red cell volume, and structural changes⁵ put the system into a state of stress, which can greatly increase the risk of CVD related mortality and morbidity during pregnancy. To minimize the effects of CVD in pregnancy, proper risk assessment and appropriate referral are required⁶. The use of a risk index is always preferred for predicting maternal cardiac risk^7,8. Several risk assessment models have been suggested for this purpose and are being used in many HICs. These include the CARPEG score by the Cardiac Disease in Pregnancy Study^8,9, the Zahara model¹⁰, and the World Health Organization (WHO) risk classification¹¹.

In Sri Lanka, cardiovascular disease complicating pregnancy is a major cause of maternal mortality, second only to postpartum hemorrhage^12,13. National Maternal Mortality Reviews 2016 outcome dissemination¹² shows 120 maternal deaths in 2016, and of those, 24 (20%) were related to cardiovascular disease. These included, complicated congenital heart condition (n=5), rheumatic valvular heart disease (n=3), myocarditis (n=2), cardiomyopathy (n=1), HELLP syndrome (n=3), eclampsia (n=4), and other hypertensive disorders (n=2). In the year 2017, maternal deaths due to cardiovascular diseases were 20 out of 127 total maternal deaths, and it was only second to dengue hemorrhagic fever in that year¹⁴.

Screening for CVD in pregnancy in Sri Lanka is limited to a routine clinical assessment. Evidence-based guidelines are yet to be developed for the screening of cardiovascular disease in pregnancy. Cardiac imaging is not routinely practised in Sri Lanka for cardiovascular risk assessment. It was evident that some of the major cardiovascular changes, particularly cardiac maladaptation with pregnancy conditions are predictable by performing cardiac imaging¹⁵. A study conducted in a population of women with gestational diabetes mellitus(GDM) and assessing them using speckle tracking echocardiography has shown increased left ventricular (LV) mass and impaired LV diastolic function in GDM women¹⁶. The use of serial strain echocardiographic imaging during antenatal and postnatal periods of pregnancy can be utilized to develop innovative screening modalities for detecting subclinical cardiac conditions during pregnancy.

Lack of proper screening in Sri Lanka may lead to a substantial underestimation of the CVD burden. Although it is the second leading cause of maternal deaths, locally available data on cardiovascular conditions complicating pregnancy are limited^13,17, probably due to late diagnosis and underestimation.

Objectives

The present study has two main objectives. The first one is to determine the prevalence of CVD in early pregnancy and the second one is to determine the incidence of CVD/cardiovascular events during pregnancy. The findings of this study will be used to develop a model to predict CVD events during pregnancy, be used in field clinics in Sri Lanka to reduce the effects of CVD in pregnancy.

Methods

This study was conducted as a part of large ongoing cohort study in Anuradhapura district, Sri Lanka, Rajarata Pregnancy Cohort (RaPCo). Details of the study setting, study population, sampling procedure, and the study sample of the RaPCo study are published elsewhere¹⁸. The specific protocol for cardiac disease complicating pregnancy is described here.

Study design

This is a prospective cohort study developed to determine the prevalence and the incidence of common CVD conditions in a cohort of pregnant females in the Anuradhapura district.

Study setting

The present study was carried out in the Anuradhapura district, the largest Sri Lanka district. According to 2017 Department of Census and Statistics data¹⁹, it covers 7,179 km² with a total population of 917,748. The total fertility rate of the district is 2.4 births per woman, one of the highest values in Sri Lanka²⁰.

In Sri Lanka, the field maternal and child health services are mainly provided by the public health administrative units named "Medical Officer of Health" (MOH) areas. In each MOH area, a Medical Officer of Health (MOH) is in charge and leads a team of ground-level health care workers, including public health midwives (PHM), public health nursing sisters (PNS), and public health inspectors. In Anuradhapura, this service for pregnant women is provided through 22 MOHs, and currently 17 PNS and more than 250 PHM are working in the area. Spatial distribution of those MOH areas is displayed in Figure 1.

Figure 1. Spatial distribution of Medical Officer of Health (MOH) areas in Anuradhapura district, Sri Lanka.

This figure shows the 22 MOH areas in the district. It has been reproduced with permission from Agampodi TC et al. The Rajarata Pregnancy Cohort (RaPCo): study protocol. BMC Pregnancy Childbirth [Internet]. 2020 Jun 26 [cited 2020 Nov 30];20(1):374. Available from: https://bmcpregnancychildbirth.biomedcentral.com/articles/10.1186/s12884-020-03056-x

Curative services are provided through 56 hospitals/primary care units, including one teaching hospital (tertiary care unit) and three base hospitals (secondary care units). Almost all deliveries (99.5%) take place in government hospitals²⁰. The study was conducted in all 22 MOH areas covering all the antenatal clinics.

Study population

All pregnant females in Anuradhapura district.

Study sample

All pregnant females visiting antenatal clinics in the Anuradhapura district from July to September 2019.

Inclusion criteria

Pregnant women:

1. Registered by field midwives and visiting field antenatal clinics in the Anuradhapura district.

2. Period of amenorrhoea (POA) less than 12 weeks by the time of recruitment.

Exclusion criteria

1. Pregnant women planning to leave the study area for childbirth or after childbirth.

2. Pregnant women who are not registered at field antenatal clinics.

Sample size

All the pregnant females registered at field antenatal clinics in Anuradhapura within three months from the beginning of the study were screened (Figure 2). The usual number of pregnant mothers registered in each quarter is around 4000. However, 15–20% are registered after a POA of 10 weeks. Around 3000 pregnant women were recruited as the sample size. We hypothesized that the incidence of CVD complicating pregnancy among those who were without risk factors would be around 5% compared to 2% among those who did not have risk factors. With a conservative estimate of unexposed to exposed ratio 5:1, power of 80%- and two-sided confidence at 95% a sample of at least 1529 pregnant women (Kelsey formula) were required for the study. With around 15% early pregnancy miscarriages and 10% expected attrition, a minimum of 1911 pregnant women were required, and the number was well within the number recruited. Based on the actual rate of CVD, we will calculate the power of the study to detect the expected outcomes retrospectively.

Figure 2. Flow chart of the study.

The flow chart shows the developed methodology to achieve the study objectives. Following the registration to the antenatal care, pregnant women fulfilling the eligibility criteria were invited to attend a special clinic in their Medical Officer of Health area. Risk assessment was done through a specific interviewer-administered questionnaire, including clinical features of present cardiovascular diseases and a clinical examination. Based on these data and cardiac screening, suspected/probable cases with cardiovascular conditions were referred for an echocardiogram and consultant cardiologist's opinion. All the recruited participants in the first trimester were followed up between 24–28 weeks of the period of amenorrhoea at the routine antenatal clinic visit. They were screened again using a separate short interviewer-administered questionnaire (20) and were subjected to general and cardiac examination, referrals were done using a checklist (20). All antenatal ward admissions with cardiac disease complicating pregnancy and all intensive care unit admissions were also screened during the study period. A telephone interview was conducted during the antenatal period and between 6–12 weeks after the expected delivery date to cover all antenatal and postpartum morbidities.

Study implementation procedure and recruitment of study participants

Following registration to the antenatal care, pregnant women fulfilling the eligibility criteria were invited to attend a special clinic in their relevant MOH area. This invitation was given by way of a leaflet provided to the antenatal women through the PHM. At the special clinic, potential participants were recruited by the data collectors who visit these special antenatal clinics (ANC) in the field. Data collectors visited each field antenatal clinic in all 22 MOH areas on the pre-planned special clinic day. Eligible pregnant mothers were educated about the research purpose and written informed consent was obtained before recruitment. Participants were informed that they might need to visit the Teaching Hospital, Anuradhapura, if the study suggested an echocardiogram. All the other data collection and follow-up was done at the routine antenatal clinics. Recruitment was carried out until the data collection period was over.

Cardiovascular risk assessment

We carried out the risk assessment through a specific interviewer-administered questionnaire, including clinical features of present cardiovascular diseases²¹ and a clinical examination. The examination included a baseline physical examination and referral checklist, including a specific set of variables/signs, each defined previously, to improve the validity and reliability of data²¹. Measurement of blood pressure and CVS examination auscultation was done using standard protocols given to all medical officers doing the clinical assessment²¹. Specially trained medical graduates carried out data collection to use the above equipment using standard guidelines, which was issued in print for each procedure²¹.

According to the baseline data, every recruited mother was classified according to the New York Heart Association (NYHA) classification. Based on that data and cardiac examination screening, suspected/probable cases with cardiovascular conditions were referred to the Professorial Unit, Teaching Hospital, Anuradhapura, for an echocardiogram and consultant cardiologist's opinion (Figure 2).

We developed this checklist with less stringent criteria to improve the sensitivity with low threshold values to develop a more refined screening checklist based on the results of the study. The development of the screening checklist was done after a literature review and expert opinions. We incorporated this checklist into the examination sheet to minimize the duplication of work.

Referral procedure

As the objective was to determine the prevalence of common cardiac conditions in the first trimester of the pregnant female, the referral method was developed to have a low threshold. If any of the above signs or symptoms were positive, the participants were referred to the consultant cardiologist at the Professorial Unit, Teaching Hospital, Anuradhapura.

Performing echocardiogram

All screening positive patients were subject to a two-dimensional (2D) echocardiogram and an electrocardiogram (ECG) to evaluate cardiac electrical activity and rhythm. The ECG was taken using the Zonecare, iMAC 300 Three channel ECG machine, and the 2D echocardiogram using a Philips EPIQ 7.

Patient follow up

All the recruited participants in the first trimester were followed up between 24–28 weeks of POA at the routine antenatal clinic visit. A separate short interviewer-administered questionnaire was used²¹. We also carried out a general and cardiac examination, and referrals were done using a checklist²¹.

Participants were followed up through the routine system, and all maternal morbidities and hospital admissions recorded through a specific hospital surveillance system. All antenatal ward admissions with cardiac disease complicating pregnancy were checked to identify cohort participants to determine whether there were conditions missed through the screening. This was done in two major hospitals with a consultant obstetrician where all pregnant mothers from Anuradhapura districts are transferred. To determine the near misses and severe complications, all intensive care unit admissions were also screened during the study period. We matched all pregnant admissions with the original cohort to identify any cardiac disease complicating pregnancy.

A telephone interview was conducted with all study participants to document all antenatal morbidities in addition to the hospital admission screening. The interviews were carried out between 6–12 weeks after the expected delivery date to cover postpartum morbidities. Records relating to those who reported any hospital admissions were extracted from relevant hospitals. This approach was proposed to minimize unnecessary in-person contacts during the COVID-19 pandemic. In addition, all public health records related to the participants will be traced from public health midwives office to see documented CVD events during the pregnancy.

Bias

To reduce the bias in sample selection and recruitment all the mothers who have registered at the field antenatal clinics were given an equal opportunity to participate in the study. All the participants who fulfilled the inclusion and exclusion criteria were recruited to the study.

When it comes to the examination to reduce the observer bias, digital blood pressure monitors were used with the same method in every clinic. Two readings are taken from both arms with a five-minute gap and the lower value recorded as the blood pressure. If a high blood pressure value is detected (SBP> 135mmHg or DBP >85mmHg), a third reading is taken after a rest period of five minutes. The same procedure is carried out in subsequent blood pressure measurements of the participants.

To reduce the bias when referring participants for further assessment, referrals were initiated based solely on screening positivity at the initial assessment.

To reduce the bias arising due to lost to follow-up, several measures were taken starting from the point of recruitment of participants to the study. All the mothers were provided with a card mentioning the dates which they should attend to the follow-up visit and for the 2D Echocardiogram where necessary. Reminder phone calls were given to the participants day before their allocated day for 2D-Echocardiogram. The coupling of the research follow-up day with the routinely established system follow-up day was done intentionally to minimize the bias arising due to loss to follow up. Telephone calls were given for follow-up visits and also after delivery to collect outcome data. After delivery surveillance was done through the public health system where all the participants are registered and followed up. Separate hospital surveillance was done to identify admissions of pregnant women due to CVD related events and then searched them for cohort participants. However, a certain degree of lost to follow-up is still expected due to a change of residence during and after the pregnancy (a common practice in Sri Lanka to go back to the parents for delivery) and due to frequent changes of mobile numbers. We will analyse the baseline data to see whether those who lost to follow-up are systematically different from those who remain, to estimate the magnitude of bias.

Outcomes

The main outcome measure is cardiovascular events leading to hospital/ICU admission or death. Outcome measures are carried out through hospital and ICU surveillance, direct interviews with participants and through the surveillance of public health recording system. Any documented CVD related hospital admission and the subsequent event will be defined as an outcome.

The main focus of the project is to describe the actual disease burden of cardiovascular disease in pregnancy in Sri Lanka (prevalence and incidence). With a proper assessment of disease burden, we expect to propose strategies to be included in the national program.

A field model will be developed using the findings for early detection/prediction of cardiovascular conditions during pregnancy at field level. With the appropriate inputs from the stakeholder, this model will be used to propose the required changes in strategies related to control and prevention of CVD complicating pregnancy in Sri Lanka.

Data management

All the data collection will be done using the electronic data collection method using a unique barcode and serial number. The database will be automatically formulated through this data collection platform. Access to the databases will be under restricted access. Access will be granted to principal investigators only. Two-dimensional echocardiogram reports will also be formulated via database management software, and a copy of the report will be provided to the participant. This database will also be accessible by the researchers only, and the data will be stored under the unique serial number.

Data analysis

Data will be analysed using the Statistical Package for Social Sciences (SPSS) version 26 (IBM SPSS Statistics, RRID:SCR_019096). An open-access alternative that can provide an equivalent function is the R stats package (R Project for Statistical Computing, RRID:SCR_001905). Point prevalence of cardiovascular diseases complicating pregnancy will be calculated with 95% confidence intervals (CI). The prevalence of each specific condition will also be presented as proportions. The cumulative incidence of heart disease incidence will be estimated, and the 95% CI will be calculated using a Poisson distribution. We will develop two models; one for the diagnostic algorithm to detect CVD complicating pregnancy early at pregnancy using the baseline data and another to predict CVD related adverse effects in pregnancy through follow-up data. All the variables in the screening checklist will be use as potential predictors. Binary logistic regression will be used with backward selection process to identify the independent predictors of heart conditions during pregnancy. In addition, relevant variables will be combined based on the Variance Inflation Factor (VIF) values of the predictors and combined variables will be included as the predictors in the logistic model. This model will be used to develop a screening checklist for the public health system. We will follow the guidelines given by Prognosis Research Strategy (PROGRESS) for developing, validating and evaluating such models, with suggestions for updating and clinical use.

Ethical considerations

All study procedures were done following the Helsinki declaration. Research was carried out only after the informed written consent of the participant for participation and after agreeing to publication of data collected in an anonymized format. Participants have been provided with the opportunity to withdraw from the study at any time. Participant identification data will be kept under lock and key to protect confidentiality. All identified conditions will be managed and treated by the consultant cardiologists with appropriate investigations and referral without an additional cost to the participant. Ethical clearance for the "Rajarata Pregnancy Cohort" has been obtained from the Ethics Review Committee, Faculty of the Medicine & Allied Sciences, Rajarata University of Sri Lanka under the approval number ERC/2019/07.

Confidentiality

All the recruited participants have been provided with a serial number and a unique bar code. All the material and data belonging to a participant will be labelled with the above serial number and bar code. All the consent forms will be stored separately under lock and key at the Maternal and Child Health Research Unit, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka. The participant has also received an identity card with basic details and a barcode.

Dissemination of findings

Findings will be published as research articles, abstracts, and presentations. Generated knowledge will be communicated with the local health care authorities, and nationally important findings will be published as policy briefs.

Discussion

This study on cardiovascular disease in pregnancy is the largest study conducted of its kind in Sri Lanka. The patterns and associations identified with regard to cardiovascular disease during pregnancy and its distributions among the population will give an idea about the true picture of the disease in the LMICs. As this study focuses on both prevalence and incidence of cardiovascular disease during pregnancy it will provide a wider understanding about risks and predictive symptoms and signs of CVD during pregnancy in Sri Lankans. This will enable development of a model for early CVD risk identification among pregnant females. Also, the findings will have an impact on policy change to go beyond routine screening methods.

This project proposal was developed in June 2019. Recruitment of participants was done from July to September 2019. The first round of referral and cardiovascular assessment and part of the second trimester assessment is already completed. However, the follow-up was interrupted due to the COVID-19 pandemic and lockdown since March 2020. Based on the country’s current situation, delivery and outcome data collection has been initiated through alternative methods. Telephone interviews and data extraction from labor rooms are also in progress. Records relating to those who reported any hospital admissions during the telephone interviews will be extracted from the relevant hospitals.

Data availability

Extended data

Open Science Framework: Generating Evidence for Ending Preventable Maternal Deaths (GEEPMED) in Sri Lanka. Extended data for ‘Disease burden and adverse pregnancy outcomes due to cardiovascular conditions complicating pregnancy in Sri Lanka’, ‘Tools’. https://doi.org/10.17605/OSF.IO/RTDCG²¹

This project contains the following extended data:

1. Baseline questionnaire

2. Baseline physical examination and referral checklist sheet

3. Definition of selected signs and symptoms

4. Guide for blood pressure measurement

5. Guide for CVS examination

6. Follow-up questionnaire

7. Follow-up examination and referral checklist sheet

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0)

Faculty Opinions recommended

References

1. WHO: Trends in maternal mortality 2000 to 2017: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division: executive summary. World Health Organization; 2019. Reference Source
2. Say L, Chou D, Gemmill A, et al.: Global causes of maternal death: A WHO systematic analysis. Lancet Glob Health. 2014; 2(6): e323–33. PubMed Abstract | Publisher Full Text
3. Storm F, Agampodi S, Eddleston M, et al.: Indirect causes of maternal death. Lancet Glob Health. 2014; 2(10): e566. PubMed Abstract | Publisher Full Text
4. Coulter SA, Lew J, Jenny B: Heart Disease in Pregnancy. Valvular Heart Disease. In: Carabello BA, editor. London: Springer London; 2020; 237–83. Publisher Full Text
5. Perales M, Nagpal TS, Barakat R: Physiological Changes During Pregnancy: Main Adaptations, Discomforts, and Implications for Physical Activity and Exercise. Exercise and Sporting Activity During Pregnancy: Evidence-Based Guidelines. In: Santos-Rocha R, editor. Cham: Springer International Publishing, 2019; 45–56. Publisher Full Text
6. Scott NS: Management of cardiovascular disease during pregnancy. US Cardiol Rev. Radcliffe Group, 2018; 12(2): 119–23. Publisher Full Text
7. Drenthen W, Boersma E, Balci A, et al.: Predictors of pregnancy complications in women with congenital heart disease. Eur Heart J. 2010; 31(17): 2124–32. PubMed Abstract | Publisher Full Text
8. Siu SC, Sermer M, Colman JM, et al.: Prospective multicenter study of pregnancy outcomes in women with heart disease. Circulation. 2001; 104(5): 515–21. PubMed Abstract | Publisher Full Text
9. Balci A, Sollie-Szarynska KM, van Der Bijl AG, et al.: Prospective validation and assessment of cardiovascular and offspring risk models for pregnant women with congenital heart disease. Heart. 2014; 100(17): 1373–81. PubMed Abstract | Publisher Full Text
10. Pieper PG: Pre-pregnancy risk assessment and counselling of the cardiac patient. Neth Heart J. 2011; 19(11): 477–81. PubMed Abstract | Publisher Full Text | Free Full Text
11. Ntusi NB, Mayosi BM: Aetiology and risk factors of peripartum cardiomyopathy: A systematic review. Int J Cardiol. 2009; 131(2): 168–79. PubMed Abstract | Publisher Full Text
12. Family Health Bureau Sri Lanka: National Maternal Mortality Reviews - 2016 Outcome Dissemination. 2016; 30. Reference Source
13. Haththotuwa HR, Attygalle D, Jayatilleka AC, et al.: Maternal mortality due to cardiac disease in Sri Lanka. Int J Gynaecol Obstet. 2009; 104(3): 194–8. PubMed Abstract | Publisher Full Text
14. Family Health Bureau Sri Lanka: Annual Report of the Family Health Bureau 2017. Reference Source
15. Buddeberg BS, Sharma R, O’Driscoll JM, et al.: Cardiac maladaptation in obese pregnant women at term. Ultrasound Obstet Gynecol. 2019; 54(3): 344–9. PubMed Abstract | Publisher Full Text
16. Sonaglioni A, Barlocci E, Adda G, et al.: The impact of short-term hyperglycemia and obesity on biventricular and biatrial myocardial function assessed by speckle tracking echocardiography in a population of women with gestational diabetes mellitus. Nutr Metab Cardiovasc Dis. 2022; 32(2): 456–68. PubMed Abstract | Publisher Full Text
17. Stephen SJ: Changing patterns of mitral stenosis in childhood and pregnancy in Sri Lanka. J Am Coll Cardiol. 1992; 19(6): 1276–84. PubMed Abstract | Publisher Full Text
18. Agampodi TC, Wickramasinghe ND, Prasanna RIR, et al.: The Rajarata Pregnancy Cohort (RaPCo): study protocol. BMC Pregnancy Childbirth. 2020; 20(1): 374. PubMed Abstract | Publisher Full Text | Free Full Text
19. Department of Census and Statistics - Sri Lanka: Distict Statistical Handbook Anuradhapura. 2018.
20. Department of Census and Statistics, Ministry of National Policies and Economic Affairs: Sri Lanka Demographic and Health Survey - 2016 (Full Report). Reference Source
21. Hettiarachchi A, Agampodi SB: Tools. 2021. http://www.doi.org/10.17605/OSF.IO/RTDCG

Comments on this article Comments (0)

Version 4

VERSION 4 PUBLISHED 11 Oct 2021

Author details Author details

Ayesh Hettiarachchi
Roles: Conceptualization, Investigation, Methodology, Project Administration, Resources, Writing – Original Draft Preparation

Niroshan Lokunarangoda
Roles: Investigation, Methodology, Supervision, Writing – Review & Editing

Thilini Agampodi
Roles: Funding Acquisition, Project Administration, Writing – Review & Editing

Suneth Agampodi
Roles: Conceptualization, Methodology, Project Administration, Supervision, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The original study (RaPCo) was supported by the Accelerating Higher Education Expansion and Development (AHEAD) Operation of the Ministry of Higher Education, Sri Lanka, funded by the World Bank.

Article Versions (4)

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© 2024 Hettiarachchi A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Hettiarachchi A, Lokunarangoda N, Agampodi T and Agampodi S. Disease burden of cardiovascular conditions complicating pregnancy in Sri Lanka: a protocol [version 4; peer review: 2 approved]. F1000Research 2024, 10:1028 (https://doi.org/10.12688/f1000research.52539.4)

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Reviewer Report 18 Mar 2024

Andrea Sonaglioni, MultiMedica IRCCS, Sesto San Giovanni MI, Italy

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https://doi.org/10.5256/f1000research.163166.r251735

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Reviewer Report 21 Feb 2024

Andrea Sonaglioni, MultiMedica IRCCS, Sesto San Giovanni MI, Italy

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https://doi.org/10.5256/f1000research.122032.r226942

The manuscript describes an elegant modality of cardiovascular risk assessment in pregnancy in Sri Lanka.
The screening modality is mainly based on two-dimensional echocardiography and electrocardiography.
I congratulate the Authors for their work.

I have only one suggestion for the Authors.

In the Introduction section, after the following sentence "Screening for CVD in pregnancy in Sri Lanka is limited to a routine clinical assessment. Given that evidence-based guidelines are yet to be developed for the screening of cardiovascular disease in pregnancy", I suggest the Authors to describe an innovative screening modality for detecting subclinical myocardial dysfunction, that is employed in Europe since one decade, i.e. the speckle tracking echocardiography.
The Authors could add a short paragraph for describing strain echocardiographic imaging in pregnancy, They could cite and discuss following references ref [1,2]

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

References

1. Buddeberg BS, Sharma R, O'Driscoll JM, Kaelin Agten A, et al.: Cardiac maladaptation in obese pregnant women at term.Ultrasound Obstet Gynecol. 2019; 54 (3): 344-349 PubMed Abstract | Publisher Full Text
2. Sonaglioni A, Barlocci E, Adda G, Esposito V, et al.: The impact of short-term hyperglycemia and obesity on biventricular and biatrial myocardial function assessed by speckle tracking echocardiography in a population of women with gestational diabetes mellitus.Nutr Metab Cardiovasc Dis. 2022; 32 (2): 456-468 PubMed Abstract | Publisher Full Text

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Cardiology, Echocardiography

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 13 Apr 2024

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

13 Apr 2024

Author Response

Dear Dr. Andrea Sonaglioni,
Thank you very much for taking the time to review my paper. It's truly appreciated that you emphasized the importance of including the use of strain ... Continue reading Dear Dr. Andrea Sonaglioni,
Thank you very much for taking the time to review my paper. It's truly appreciated that you emphasized the importance of including the use of strain echocardiographic imaging during pregnancy for screening cardiac conditions. I have updated the introduction section as you advised and added references accordingly. Thank you for approving my article.
Sincerely,
Ayesh Hettiarachchi.
Dear Dr. Andrea Sonaglioni,
Thank you very much for taking the time to review my paper. It's truly appreciated that you emphasized the importance of including the use of strain echocardiographic imaging during pregnancy for screening cardiac conditions. I have updated the introduction section as you advised and added references accordingly. Thank you for approving my article.
Sincerely,
Ayesh Hettiarachchi.
Competing Interests: None Close
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COMMENTS ON THIS REPORT

Author Response 13 Apr 2024

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

13 Apr 2024

Author Response

Dear Dr. Andrea Sonaglioni,
Thank you very much for taking the time to review my paper. It's truly appreciated that you emphasized the importance of including the use of strain ... Continue reading Dear Dr. Andrea Sonaglioni,
Thank you very much for taking the time to review my paper. It's truly appreciated that you emphasized the importance of including the use of strain echocardiographic imaging during pregnancy for screening cardiac conditions. I have updated the introduction section as you advised and added references accordingly. Thank you for approving my article.
Sincerely,
Ayesh Hettiarachchi.
Dear Dr. Andrea Sonaglioni,
Thank you very much for taking the time to review my paper. It's truly appreciated that you emphasized the importance of including the use of strain echocardiographic imaging during pregnancy for screening cardiac conditions. I have updated the introduction section as you advised and added references accordingly. Thank you for approving my article.
Sincerely,
Ayesh Hettiarachchi.
Competing Interests: None Close
Report a concern

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Reviewer Report 16 Mar 2022

Anish Keepanasseril, Department of Obstetrics and Gynaecology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, Tamil Nadu, India

Approved

https://doi.org/10.5256/f1000research.122032.r127630

Thank you for revising the ... Continue reading

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Version 2

VERSION 2

PUBLISHED 20 Jan 2022

Revised

Views

Reviewer Report 28 Jan 2022

Anish Keepanasseril, Department of Obstetrics and Gynaecology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, Tamil Nadu, India

Approved with Reservations

https://doi.org/10.5256/f1000research.118272.r120418

Thank you for revising the manuscript and the opportunity to review again.

The following points are not clear again in the revision.

Please give under the subheading definitions of the outcome. How they

Thank you for revising the manuscript and the opportunity to review again.

The following points are not clear again in the revision.

Please give under the subheading definitions of the outcome. How they will be identified, with references if they are already described elsewhere? This is required to avoid misclassification of the outcomes.
The aim is to develop a predictive model for the development of cardiovascular complications and some of the outcomes which you have described might have been already present but not yet identified. So they are not incidence of the outcomes described (as it is explained in the responses). So how will the factors (which might be prevalent before the pregnancy) be addressed in the model?
As it is given,k two models (probably) will be developed: one for the diagnostic algorithm and the other suggesting the adverse outcomes. Please separate both of them as they have different interpretations and usefulness for clinicians.
Please refer to the PROGRESS group website detailing the development of the prediction model and the analysis. You can revise the methods as well as the analysis based on them.
How do you intend to minimise the bias arising from lost to follow up?

Competing Interests: No competing interests were disclosed.

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Author Response 15 Mar 2022

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

15 Mar 2022

Author Response
Many thanks for reviewing my article again. Please see the following clarifications for the points raised.
1. Please give under the subheading definitions of the outcome. How they will
... Continue reading
Many thanks for reviewing my article again. Please see the following clarifications for the points raised.

Please give under the subheading definitions of the outcome. How they will be identified, with references if they are already described elsewhere? This is required to avoid misclassification of the outcomes.

Thank you for the comment. Definitions are included. See the response below as well.

The aim is to develop a predictive model for the development of cardiovascular complications and some of the outcomes which you have described might have been already present but not yet identified. So they are not incidence of the outcomes described (as it is explained in the responses). So how will the factors (which might be prevalent before the pregnancy) be addressed in the model?

Thank you very much for the comments. The way we presented the “outcome” was slightly confusing as you pointed out. We are looking at the CVD related events (mentioned as incidence) leading to hospital admissions and adverse pregnancy outcomes (previously mentioned as pregnancy outcomes). Since the way it was presented was not clear (thank you for the question), have edited the title and relevant places. As you have pointed out, we will have data on previous conditions (prevalence) during the baseline assessment. However, the outcome we are interested in is what really predicts the CVD events in pregnancy (with or without knowledge on pre-existing CVDs).

As it is given, two models (probably) will be developed: one for the diagnostic algorithm and the other suggesting the adverse outcomes. Please separate both of them as they have different interpretations and usefulness for clinicians.

Agree and added to the methods.

Please refer to the PROGRESS group website detailing the development of the prediction model and the analysis. You can revise the methods as well as the analysis based on them.

Thank again. We have included that we will adhere to the PROGRESS group suggestions given in developing, validating and evaluating the model.

How do you intend to minimise the bias arising from lost to follow up?

Many thanks for pointing out this deficit. We have included a comprehensive, methodology to minimize the lost to follow up. I’ve added a paragraph under the subheading of Bias.
Many thanks for reviewing my article again. Please see the following clarifications for the points raised.

Please give under the subheading definitions of the outcome. How they will be identified, with references if they are already described elsewhere? This is required to avoid misclassification of the outcomes.

Thank you for the comment. Definitions are included. See the response below as well.

The aim is to develop a predictive model for the development of cardiovascular complications and some of the outcomes which you have described might have been already present but not yet identified. So they are not incidence of the outcomes described (as it is explained in the responses). So how will the factors (which might be prevalent before the pregnancy) be addressed in the model?

Thank you very much for the comments. The way we presented the “outcome” was slightly confusing as you pointed out. We are looking at the CVD related events (mentioned as incidence) leading to hospital admissions and adverse pregnancy outcomes (previously mentioned as pregnancy outcomes). Since the way it was presented was not clear (thank you for the question), have edited the title and relevant places. As you have pointed out, we will have data on previous conditions (prevalence) during the baseline assessment. However, the outcome we are interested in is what really predicts the CVD events in pregnancy (with or without knowledge on pre-existing CVDs).

As it is given, two models (probably) will be developed: one for the diagnostic algorithm and the other suggesting the adverse outcomes. Please separate both of them as they have different interpretations and usefulness for clinicians.

Agree and added to the methods.

Please refer to the PROGRESS group website detailing the development of the prediction model and the analysis. You can revise the methods as well as the analysis based on them.

Thank again. We have included that we will adhere to the PROGRESS group suggestions given in developing, validating and evaluating the model.

How do you intend to minimise the bias arising from lost to follow up?

Many thanks for pointing out this deficit. We have included a comprehensive, methodology to minimize the lost to follow up. I’ve added a paragraph under the subheading of Bias.
Competing Interests: None Close
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COMMENTS ON THIS REPORT

Author Response 15 Mar 2022

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

15 Mar 2022

Author Response
Many thanks for reviewing my article again. Please see the following clarifications for the points raised.
1. Please give under the subheading definitions of the outcome. How they will
... Continue reading
Many thanks for reviewing my article again. Please see the following clarifications for the points raised.

Please give under the subheading definitions of the outcome. How they will be identified, with references if they are already described elsewhere? This is required to avoid misclassification of the outcomes.

Thank you for the comment. Definitions are included. See the response below as well.

The aim is to develop a predictive model for the development of cardiovascular complications and some of the outcomes which you have described might have been already present but not yet identified. So they are not incidence of the outcomes described (as it is explained in the responses). So how will the factors (which might be prevalent before the pregnancy) be addressed in the model?

Thank you very much for the comments. The way we presented the “outcome” was slightly confusing as you pointed out. We are looking at the CVD related events (mentioned as incidence) leading to hospital admissions and adverse pregnancy outcomes (previously mentioned as pregnancy outcomes). Since the way it was presented was not clear (thank you for the question), have edited the title and relevant places. As you have pointed out, we will have data on previous conditions (prevalence) during the baseline assessment. However, the outcome we are interested in is what really predicts the CVD events in pregnancy (with or without knowledge on pre-existing CVDs).

As it is given, two models (probably) will be developed: one for the diagnostic algorithm and the other suggesting the adverse outcomes. Please separate both of them as they have different interpretations and usefulness for clinicians.

Agree and added to the methods.

Please refer to the PROGRESS group website detailing the development of the prediction model and the analysis. You can revise the methods as well as the analysis based on them.

Thank again. We have included that we will adhere to the PROGRESS group suggestions given in developing, validating and evaluating the model.

How do you intend to minimise the bias arising from lost to follow up?

Many thanks for pointing out this deficit. We have included a comprehensive, methodology to minimize the lost to follow up. I’ve added a paragraph under the subheading of Bias.
Many thanks for reviewing my article again. Please see the following clarifications for the points raised.

Please give under the subheading definitions of the outcome. How they will be identified, with references if they are already described elsewhere? This is required to avoid misclassification of the outcomes.

Thank you for the comment. Definitions are included. See the response below as well.

The aim is to develop a predictive model for the development of cardiovascular complications and some of the outcomes which you have described might have been already present but not yet identified. So they are not incidence of the outcomes described (as it is explained in the responses). So how will the factors (which might be prevalent before the pregnancy) be addressed in the model?

Thank you very much for the comments. The way we presented the “outcome” was slightly confusing as you pointed out. We are looking at the CVD related events (mentioned as incidence) leading to hospital admissions and adverse pregnancy outcomes (previously mentioned as pregnancy outcomes). Since the way it was presented was not clear (thank you for the question), have edited the title and relevant places. As you have pointed out, we will have data on previous conditions (prevalence) during the baseline assessment. However, the outcome we are interested in is what really predicts the CVD events in pregnancy (with or without knowledge on pre-existing CVDs).

As it is given, two models (probably) will be developed: one for the diagnostic algorithm and the other suggesting the adverse outcomes. Please separate both of them as they have different interpretations and usefulness for clinicians.

Agree and added to the methods.

Please refer to the PROGRESS group website detailing the development of the prediction model and the analysis. You can revise the methods as well as the analysis based on them.

Thank again. We have included that we will adhere to the PROGRESS group suggestions given in developing, validating and evaluating the model.

How do you intend to minimise the bias arising from lost to follow up?

Many thanks for pointing out this deficit. We have included a comprehensive, methodology to minimize the lost to follow up. I’ve added a paragraph under the subheading of Bias.
Competing Interests: None Close
Report a concern

Version 1

VERSION 1

PUBLISHED 11 Oct 2021

Views

Reviewer Report 11 Nov 2021

Anish Keepanasseril, Department of Obstetrics and Gynaecology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, Tamil Nadu, India

Not Approved

https://doi.org/10.5256/f1000research.55834.r96617

The study aims to assess the burden of CVD among women in the first trimester of pregnancy and to develop a risk prediction model to be used in Sri Lankan hospitals.

Even though the study has already ... Continue reading

It needs to be more specific about the study. The incidence of CVD may be difficult to determine unless we have a pre pregnancy check up and have the details available. It may be better to use the prevalence, as it will include the cases which are there in pre pregnancy as well as those who develop during the pregnancy.
Kindly mention the outcome for which the predictive models are being developed. Is it to identify people with the CVS or for identifying those who are at risk of adverse outcomes. Risk models can stratify and you might need to consider a future study or a subset wherein this stratification is useful either by a temporal or an external validation of the model.

Methodology

The design of the study, inclusion and exclusion criteria are well presented and helpful for performing/guiding a study to be planned else where. However, further reading it was unclear about the study design as well as about the intention of adding matched controls which is highlighted in point 3. If any secondary objective is planned please provide the details in the objectives section of the protocol.
It is unclear which are the diseases that are included as CVD. As heart disease, hypertension, stroke etc. could be taken as CVD. More clarity is required on the outcomes.
How and why was the matching performed under patient follow up? Did the matched controls also undergo the same procedure? How did you avoid the selection bias in choosing controls? Did you look at any nested case control design? If so all these need to be more clarified in the text. Being an observational study, this is the main area of interest to the reader.
Detail about how the model will be built needs to be included.

Is the rationale for, and objectives of, the study clearly described?

No
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Partly
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Maternal medicine

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Report a concern

Author Response 20 Jan 2022

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

20 Jan 2022

Author Response

Thank you reviewing this paper. Please find a point by point response for the comments below.

Comment 1 - The study aims to assess the burden of CVD among ... Continue reading Thank you reviewing this paper. Please find a point by point response for the comments below.

Comment 1 - The study aims to assess the burden of CVD among women in the first trimester of pregnancy and to develop a risk prediction model to be used in Sri Lankan hospitals.

Response 1 - To clarify the confusion, this study aims to develop a risk prediction model to be used in Sri Lanka field health care setup not in the Sri Lankan hospitals.

Comment 2 - It needs to be more specific about the study. The incidence of CVD may be difficult to determine unless we have a pre pregnancy check up and have the details available. It may be better to use the prevalence, as it will include the cases which are there in pre pregnancy as well as those who develop during the pregnancy.

Response 2 - Thank you for the comment. And I’m sorry for the confusion. This study recruit first trimester pregnant females and screen them for CVD conditions. As you mentioned, we determine the prevalence of CVD conditions during the first trimester pregnant females. This change was done in the first objective.

In addition, we do follow up the same cohort of pregnant females at the second trimester of their pregnancy. Then at the post-partum period. This follow up section of the study is planned to determine the incidence of CVD among the same cohort of pregnant females. This part is clearly shown in the flow diagram provided and at the outcomes section. To avoid the confusion, I’ve changed the first sentence under the subheading “objectives”.

Comment 3 - Kindly mention the outcome for which the predictive models are being developed. Is it to identify people with the CVS or for identifying those who are at risk of adverse outcomes. Risk models can stratify and you might need to consider a future study or a subset wherein this stratification is useful either by a temporal or an external validation of the model.

Response 3 -Thank you for the comment. This predictive model is being developed to identify pregnant women with adverse pregnancy outcomes due to existing or an emerging CVD condition. The objective is edited as suggested.

Comment 4 - The design of the study, inclusion and exclusion criteria are well presented and helpful for performing/guiding a study to be planned else where. However, further reading it was unclear about the study design as well as about the intention of adding matched controls which is highlighted in point 3. If any secondary objective is planned please provide the details in the objectives section of the protocol.

Response 4 - Thank you for the kind comment. There are no matched controls in this study. This is a cohort study where a selected group of individuals recruited, screening and then follow-up throughout the pregnancy and the post-partum period. It is unclear from where this confusion is arising. Probably the misunderstanding is about the sentence “All antenatal ward admissions with cardiac disease complicating pregnancy were extracted and cross-matched with the initial cohort”. This was not a matched control group. To make sure we are not missing data, we separately looked at hospital admissions during the period and confirmed whether there are patients from our cohort who are having CVD related complications, but not captured during the follow up. We have edited the sentence.

Comment 5 - It is unclear which are the diseases that are included as CVD. As heart disease, hypertension, stroke etc. could be taken as CVD. More clarity is required on the outcomes.

Response 5 - Thank you for the valuable comment. I have included a statement under the cardiovascular risk assessment section. All the acquired or congenital heart conditions and other related cardiovascular conditions including hypertension, heart failure and pulmonary hypertension and arrythmias considered as CVD related to this study. History Cerebrovascular events were taken during the data collection for the risk prediction of related CVD condition.

Comment 6 - How and why was the matching performed under patient follow up? Did the matched controls also undergo the same procedure? How did you avoid the selection bias in choosing controls? Did you look at any nested case control design? If so all these need to be more clarified in the text. Being an observational study, this is the main area of interest to the reader.

Response 6 - Kindly see my reply under your comment number 1 of methodology part.

Comment 7 - Detail about how the model will be built needs to be included.

Response 7 - Thank you for the comment. Details included under the data analysis section.
Thank you reviewing this paper. Please find a point by point response for the comments below.

Comment 1 - The study aims to assess the burden of CVD among women in the first trimester of pregnancy and to develop a risk prediction model to be used in Sri Lankan hospitals.

Response 1 - To clarify the confusion, this study aims to develop a risk prediction model to be used in Sri Lanka field health care setup not in the Sri Lankan hospitals.

Comment 2 - It needs to be more specific about the study. The incidence of CVD may be difficult to determine unless we have a pre pregnancy check up and have the details available. It may be better to use the prevalence, as it will include the cases which are there in pre pregnancy as well as those who develop during the pregnancy.

Response 2 - Thank you for the comment. And I’m sorry for the confusion. This study recruit first trimester pregnant females and screen them for CVD conditions. As you mentioned, we determine the prevalence of CVD conditions during the first trimester pregnant females. This change was done in the first objective.

In addition, we do follow up the same cohort of pregnant females at the second trimester of their pregnancy. Then at the post-partum period. This follow up section of the study is planned to determine the incidence of CVD among the same cohort of pregnant females. This part is clearly shown in the flow diagram provided and at the outcomes section. To avoid the confusion, I’ve changed the first sentence under the subheading “objectives”.

Comment 3 - Kindly mention the outcome for which the predictive models are being developed. Is it to identify people with the CVS or for identifying those who are at risk of adverse outcomes. Risk models can stratify and you might need to consider a future study or a subset wherein this stratification is useful either by a temporal or an external validation of the model.

Response 3 -Thank you for the comment. This predictive model is being developed to identify pregnant women with adverse pregnancy outcomes due to existing or an emerging CVD condition. The objective is edited as suggested.

Comment 4 - The design of the study, inclusion and exclusion criteria are well presented and helpful for performing/guiding a study to be planned else where. However, further reading it was unclear about the study design as well as about the intention of adding matched controls which is highlighted in point 3. If any secondary objective is planned please provide the details in the objectives section of the protocol.

Response 4 - Thank you for the kind comment. There are no matched controls in this study. This is a cohort study where a selected group of individuals recruited, screening and then follow-up throughout the pregnancy and the post-partum period. It is unclear from where this confusion is arising. Probably the misunderstanding is about the sentence “All antenatal ward admissions with cardiac disease complicating pregnancy were extracted and cross-matched with the initial cohort”. This was not a matched control group. To make sure we are not missing data, we separately looked at hospital admissions during the period and confirmed whether there are patients from our cohort who are having CVD related complications, but not captured during the follow up. We have edited the sentence.

Comment 5 - It is unclear which are the diseases that are included as CVD. As heart disease, hypertension, stroke etc. could be taken as CVD. More clarity is required on the outcomes.

Response 5 - Thank you for the valuable comment. I have included a statement under the cardiovascular risk assessment section. All the acquired or congenital heart conditions and other related cardiovascular conditions including hypertension, heart failure and pulmonary hypertension and arrythmias considered as CVD related to this study. History Cerebrovascular events were taken during the data collection for the risk prediction of related CVD condition.

Comment 6 - How and why was the matching performed under patient follow up? Did the matched controls also undergo the same procedure? How did you avoid the selection bias in choosing controls? Did you look at any nested case control design? If so all these need to be more clarified in the text. Being an observational study, this is the main area of interest to the reader.

Response 6 - Kindly see my reply under your comment number 1 of methodology part.

Comment 7 - Detail about how the model will be built needs to be included.

Response 7 - Thank you for the comment. Details included under the data analysis section.
Competing Interests: No competing interests were disclosed. Close
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COMMENTS ON THIS REPORT

Author Response 20 Jan 2022

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

20 Jan 2022

Author Response

Thank you reviewing this paper. Please find a point by point response for the comments below.

Comment 1 - The study aims to assess the burden of CVD among ... Continue reading Thank you reviewing this paper. Please find a point by point response for the comments below.

Comment 1 - The study aims to assess the burden of CVD among women in the first trimester of pregnancy and to develop a risk prediction model to be used in Sri Lankan hospitals.

Response 1 - To clarify the confusion, this study aims to develop a risk prediction model to be used in Sri Lanka field health care setup not in the Sri Lankan hospitals.

Comment 2 - It needs to be more specific about the study. The incidence of CVD may be difficult to determine unless we have a pre pregnancy check up and have the details available. It may be better to use the prevalence, as it will include the cases which are there in pre pregnancy as well as those who develop during the pregnancy.

Response 2 - Thank you for the comment. And I’m sorry for the confusion. This study recruit first trimester pregnant females and screen them for CVD conditions. As you mentioned, we determine the prevalence of CVD conditions during the first trimester pregnant females. This change was done in the first objective.

In addition, we do follow up the same cohort of pregnant females at the second trimester of their pregnancy. Then at the post-partum period. This follow up section of the study is planned to determine the incidence of CVD among the same cohort of pregnant females. This part is clearly shown in the flow diagram provided and at the outcomes section. To avoid the confusion, I’ve changed the first sentence under the subheading “objectives”.

Comment 3 - Kindly mention the outcome for which the predictive models are being developed. Is it to identify people with the CVS or for identifying those who are at risk of adverse outcomes. Risk models can stratify and you might need to consider a future study or a subset wherein this stratification is useful either by a temporal or an external validation of the model.

Response 3 -Thank you for the comment. This predictive model is being developed to identify pregnant women with adverse pregnancy outcomes due to existing or an emerging CVD condition. The objective is edited as suggested.

Comment 4 - The design of the study, inclusion and exclusion criteria are well presented and helpful for performing/guiding a study to be planned else where. However, further reading it was unclear about the study design as well as about the intention of adding matched controls which is highlighted in point 3. If any secondary objective is planned please provide the details in the objectives section of the protocol.

Response 4 - Thank you for the kind comment. There are no matched controls in this study. This is a cohort study where a selected group of individuals recruited, screening and then follow-up throughout the pregnancy and the post-partum period. It is unclear from where this confusion is arising. Probably the misunderstanding is about the sentence “All antenatal ward admissions with cardiac disease complicating pregnancy were extracted and cross-matched with the initial cohort”. This was not a matched control group. To make sure we are not missing data, we separately looked at hospital admissions during the period and confirmed whether there are patients from our cohort who are having CVD related complications, but not captured during the follow up. We have edited the sentence.

Comment 5 - It is unclear which are the diseases that are included as CVD. As heart disease, hypertension, stroke etc. could be taken as CVD. More clarity is required on the outcomes.

Response 5 - Thank you for the valuable comment. I have included a statement under the cardiovascular risk assessment section. All the acquired or congenital heart conditions and other related cardiovascular conditions including hypertension, heart failure and pulmonary hypertension and arrythmias considered as CVD related to this study. History Cerebrovascular events were taken during the data collection for the risk prediction of related CVD condition.

Comment 6 - How and why was the matching performed under patient follow up? Did the matched controls also undergo the same procedure? How did you avoid the selection bias in choosing controls? Did you look at any nested case control design? If so all these need to be more clarified in the text. Being an observational study, this is the main area of interest to the reader.

Response 6 - Kindly see my reply under your comment number 1 of methodology part.

Comment 7 - Detail about how the model will be built needs to be included.

Response 7 - Thank you for the comment. Details included under the data analysis section.
Thank you reviewing this paper. Please find a point by point response for the comments below.

Comment 1 - The study aims to assess the burden of CVD among women in the first trimester of pregnancy and to develop a risk prediction model to be used in Sri Lankan hospitals.

Response 1 - To clarify the confusion, this study aims to develop a risk prediction model to be used in Sri Lanka field health care setup not in the Sri Lankan hospitals.

Comment 2 - It needs to be more specific about the study. The incidence of CVD may be difficult to determine unless we have a pre pregnancy check up and have the details available. It may be better to use the prevalence, as it will include the cases which are there in pre pregnancy as well as those who develop during the pregnancy.

Response 2 - Thank you for the comment. And I’m sorry for the confusion. This study recruit first trimester pregnant females and screen them for CVD conditions. As you mentioned, we determine the prevalence of CVD conditions during the first trimester pregnant females. This change was done in the first objective.

In addition, we do follow up the same cohort of pregnant females at the second trimester of their pregnancy. Then at the post-partum period. This follow up section of the study is planned to determine the incidence of CVD among the same cohort of pregnant females. This part is clearly shown in the flow diagram provided and at the outcomes section. To avoid the confusion, I’ve changed the first sentence under the subheading “objectives”.

Comment 3 - Kindly mention the outcome for which the predictive models are being developed. Is it to identify people with the CVS or for identifying those who are at risk of adverse outcomes. Risk models can stratify and you might need to consider a future study or a subset wherein this stratification is useful either by a temporal or an external validation of the model.

Response 3 -Thank you for the comment. This predictive model is being developed to identify pregnant women with adverse pregnancy outcomes due to existing or an emerging CVD condition. The objective is edited as suggested.

Comment 4 - The design of the study, inclusion and exclusion criteria are well presented and helpful for performing/guiding a study to be planned else where. However, further reading it was unclear about the study design as well as about the intention of adding matched controls which is highlighted in point 3. If any secondary objective is planned please provide the details in the objectives section of the protocol.

Response 4 - Thank you for the kind comment. There are no matched controls in this study. This is a cohort study where a selected group of individuals recruited, screening and then follow-up throughout the pregnancy and the post-partum period. It is unclear from where this confusion is arising. Probably the misunderstanding is about the sentence “All antenatal ward admissions with cardiac disease complicating pregnancy were extracted and cross-matched with the initial cohort”. This was not a matched control group. To make sure we are not missing data, we separately looked at hospital admissions during the period and confirmed whether there are patients from our cohort who are having CVD related complications, but not captured during the follow up. We have edited the sentence.

Comment 5 - It is unclear which are the diseases that are included as CVD. As heart disease, hypertension, stroke etc. could be taken as CVD. More clarity is required on the outcomes.

Response 5 - Thank you for the valuable comment. I have included a statement under the cardiovascular risk assessment section. All the acquired or congenital heart conditions and other related cardiovascular conditions including hypertension, heart failure and pulmonary hypertension and arrythmias considered as CVD related to this study. History Cerebrovascular events were taken during the data collection for the risk prediction of related CVD condition.

Comment 6 - How and why was the matching performed under patient follow up? Did the matched controls also undergo the same procedure? How did you avoid the selection bias in choosing controls? Did you look at any nested case control design? If so all these need to be more clarified in the text. Being an observational study, this is the main area of interest to the reader.

Response 6 - Kindly see my reply under your comment number 1 of methodology part.

Comment 7 - Detail about how the model will be built needs to be included.

Response 7 - Thank you for the comment. Details included under the data analysis section.
Competing Interests: No competing interests were disclosed. Close
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Version 4

VERSION 4 PUBLISHED 11 Oct 2021

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Version 3 (revision) 15 Mar 22	read	read
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Version 1 11 Oct 21	read

Anish Keepanasseril, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, India
Andrea Sonaglioni, MultiMedica IRCCS, Sesto San Giovanni MI, Italy

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Andrea Sonaglioni, MultiMedica IRCCS, Sesto San Giovanni MI, Italy

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Approved

The Authors have exhaustively answered to my suggestions. I do not have any other suggestions.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Cardiology, Echocardiography

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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19 Views

21 Feb 2024 | for Version 3

Andrea Sonaglioni, MultiMedica IRCCS, Sesto San Giovanni MI, Italy

19 Views Cite this report Responses(1)

Approved With Reservations

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

References

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No competing interests were disclosed.

Reviewer Expertise

Cardiology, Echocardiography

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14 Views

16 Mar 2022 | for Version 3

Anish Keepanasseril, Department of Obstetrics and Gynaecology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, Tamil Nadu, India

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Approved

Thank you for revising the manuscript based on the comments.

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No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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25 Views

28 Jan 2022 | for Version 2

Anish Keepanasseril, Department of Obstetrics and Gynaecology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, Tamil Nadu, India

25 Views Cite this report Responses(1)

Approved With Reservations

Thank you for revising the manuscript and the opportunity to review again.

The following points are not clear again in the revision.

Please give under the subheading definitions of the outcome. How they will be identified, with references if they are already described elsewhere? This is required to avoid misclassification of the outcomes.
The aim is to develop a predictive model for the development of cardiovascular complications and some of the outcomes which you have described might have been already present but not yet identified. So they are not incidence of the outcomes described (as it is explained in the responses). So how will the factors (which might be prevalent before the pregnancy) be addressed in the model?
As it is given,k two models (probably) will be developed: one for the diagnostic algorithm and the other suggesting the adverse outcomes. Please separate both of them as they have different interpretations and usefulness for clinicians.
Please refer to the PROGRESS group website detailing the development of the prediction model and the analysis. You can revise the methods as well as the analysis based on them.
How do you intend to minimise the bias arising from lost to follow up?

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Author Response

15 Mar 2022

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

Many thanks for reviewing my article again. Please see the following clarifications for the points raised.

Please give under the subheading definitions of the outcome. How they will be identified, with references if they are already described elsewhere? This is required to avoid misclassification of the outcomes.
- Thank you for the comment. Definitions are included. See the response below as well.
The aim is to develop a predictive model for the development of cardiovascular complications and some of the outcomes which you have described might have been already present but not yet identified. So they are not incidence of the outcomes described (as it is explained in the responses). So how will the factors (which might be prevalent before the pregnancy) be addressed in the model?
- Thank you very much for the comments. The way we presented the “outcome” was slightly confusing as you pointed out. We are looking at the CVD related events (mentioned as incidence) leading to hospital admissions and adverse pregnancy outcomes (previously mentioned as pregnancy outcomes). Since the way it was presented was not clear (thank you for the question), have edited the title and relevant places. As you have pointed out, we will have data on previous conditions (prevalence) during the baseline assessment. However, the outcome we are interested in is what really predicts the CVD events in pregnancy (with or without knowledge on pre-existing CVDs).
As it is given, two models (probably) will be developed: one for the diagnostic algorithm and the other suggesting the adverse outcomes. Please separate both of them as they have different interpretations and usefulness for clinicians.
- Agree and added to the methods.
Please refer to the PROGRESS group website detailing the development of the prediction model and the analysis. You can revise the methods as well as the analysis based on them.
- Thank again. We have included that we will adhere to the PROGRESS group suggestions given in developing, validating and evaluating the model.
How do you intend to minimise the bias arising from lost to follow up?
- Many thanks for pointing out this deficit. We have included a comprehensive, methodology to minimize the lost to follow up. I’ve added a paragraph under the subheading of Bias.

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31 Views

11 Nov 2021 | for Version 1

Anish Keepanasseril, Department of Obstetrics and Gynaecology, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry, Tamil Nadu, India

31 Views Cite this report Responses(1)

Not Approved

It needs to be more specific about the study. The incidence of CVD may be difficult to determine unless we have a pre pregnancy check up and have the details available. It may be better to use the prevalence, as it will include the cases which are there in pre pregnancy as well as those who develop during the pregnancy.
Kindly mention the outcome for which the predictive models are being developed. Is it to identify people with the CVS or for identifying those who are at risk of adverse outcomes. Risk models can stratify and you might need to consider a future study or a subset wherein this stratification is useful either by a temporal or an external validation of the model.

Methodology

The design of the study, inclusion and exclusion criteria are well presented and helpful for performing/guiding a study to be planned else where. However, further reading it was unclear about the study design as well as about the intention of adding matched controls which is highlighted in point 3. If any secondary objective is planned please provide the details in the objectives section of the protocol.
It is unclear which are the diseases that are included as CVD. As heart disease, hypertension, stroke etc. could be taken as CVD. More clarity is required on the outcomes.
How and why was the matching performed under patient follow up? Did the matched controls also undergo the same procedure? How did you avoid the selection bias in choosing controls? Did you look at any nested case control design? If so all these need to be more clarified in the text. Being an observational study, this is the main area of interest to the reader.
Detail about how the model will be built needs to be included.

Is the rationale for, and objectives of, the study clearly described?

No
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Partly
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Maternal medicine

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Author Response

20 Jan 2022

Ayesh Hettiarachchi, Department of Community Medicine, Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, 5008, Sri Lanka

Thank you reviewing this paper. Please find a point by point response for the comments below.

Comment 1 - The study aims to assess the burden of CVD among women in the first trimester of pregnancy and to develop a risk prediction model to be used in Sri Lankan hospitals.

Response 1 - To clarify the confusion, this study aims to develop a risk prediction model to be used in Sri Lanka field health care setup not in the Sri Lankan hospitals.

Comment 2 - It needs to be more specific about the study. The incidence of CVD may be difficult to determine unless we have a pre pregnancy check up and have the details available. It may be better to use the prevalence, as it will include the cases which are there in pre pregnancy as well as those who develop during the pregnancy.

Response 2 - Thank you for the comment. And I’m sorry for the confusion. This study recruit first trimester pregnant females and screen them for CVD conditions. As you mentioned, we determine the prevalence of CVD conditions during the first trimester pregnant females. This change was done in the first objective.

In addition, we do follow up the same cohort of pregnant females at the second trimester of their pregnancy. Then at the post-partum period. This follow up section of the study is planned to determine the incidence of CVD among the same cohort of pregnant females. This part is clearly shown in the flow diagram provided and at the outcomes section. To avoid the confusion, I’ve changed the first sentence under the subheading “objectives”.

Comment 3 - Kindly mention the outcome for which the predictive models are being developed. Is it to identify people with the CVS or for identifying those who are at risk of adverse outcomes. Risk models can stratify and you might need to consider a future study or a subset wherein this stratification is useful either by a temporal or an external validation of the model.

Response 3 -Thank you for the comment. This predictive model is being developed to identify pregnant women with adverse pregnancy outcomes due to existing or an emerging CVD condition. The objective is edited as suggested.

Comment 4 - The design of the study, inclusion and exclusion criteria are well presented and helpful for performing/guiding a study to be planned else where. However, further reading it was unclear about the study design as well as about the intention of adding matched controls which is highlighted in point 3. If any secondary objective is planned please provide the details in the objectives section of the protocol.

Response 4 - Thank you for the kind comment. There are no matched controls in this study. This is a cohort study where a selected group of individuals recruited, screening and then follow-up throughout the pregnancy and the post-partum period. It is unclear from where this confusion is arising. Probably the misunderstanding is about the sentence “All antenatal ward admissions with cardiac disease complicating pregnancy were extracted and cross-matched with the initial cohort”. This was not a matched control group. To make sure we are not missing data, we separately looked at hospital admissions during the period and confirmed whether there are patients from our cohort who are having CVD related complications, but not captured during the follow up. We have edited the sentence.

Comment 5 - It is unclear which are the diseases that are included as CVD. As heart disease, hypertension, stroke etc. could be taken as CVD. More clarity is required on the outcomes.

Response 5 - Thank you for the valuable comment. I have included a statement under the cardiovascular risk assessment section. All the acquired or congenital heart conditions and other related cardiovascular conditions including hypertension, heart failure and pulmonary hypertension and arrythmias considered as CVD related to this study. History Cerebrovascular events were taken during the data collection for the risk prediction of related CVD condition.

Comment 6 - How and why was the matching performed under patient follow up? Did the matched controls also undergo the same procedure? How did you avoid the selection bias in choosing controls? Did you look at any nested case control design? If so all these need to be more clarified in the text. Being an observational study, this is the main area of interest to the reader.

Response 6 - Kindly see my reply under your comment number 1 of methodology part.

Comment 7 - Detail about how the model will be built needs to be included.

Response 7 - Thank you for the comment. Details included under the data analysis section.

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Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] 1. WHO: Trends in maternal mortality 2000 to 2017: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division: executive summary. World Health Organization; 2019. Reference Source

[2] 2. Say L, Chou D, Gemmill A, et al.: Global causes of maternal death: A WHO systematic analysis. Lancet Glob Health. 2014; 2(6): e323–33. PubMed Abstract | Publisher Full Text

[3] 3. Storm F, Agampodi S, Eddleston M, et al.: Indirect causes of maternal death. Lancet Glob Health. 2014; 2(10): e566. PubMed Abstract | Publisher Full Text

[4] 4. Coulter SA, Lew J, Jenny B: Heart Disease in Pregnancy. Valvular Heart Disease. In: Carabello BA, editor. London: Springer London; 2020; 237–83. Publisher Full Text

[5] 5. Perales M, Nagpal TS, Barakat R: Physiological Changes During Pregnancy: Main Adaptations, Discomforts, and Implications for Physical Activity and Exercise. Exercise and Sporting Activity During Pregnancy: Evidence-Based Guidelines. In: Santos-Rocha R, editor. Cham: Springer International Publishing, 2019; 45–56. Publisher Full Text

[6] 6. Scott NS: Management of cardiovascular disease during pregnancy. US Cardiol Rev. Radcliffe Group, 2018; 12(2): 119–23. Publisher Full Text

[7] 7. Drenthen W, Boersma E, Balci A, et al.: Predictors of pregnancy complications in women with congenital heart disease. Eur Heart J. 2010; 31(17): 2124–32. PubMed Abstract | Publisher Full Text

[8] 8. Siu SC, Sermer M, Colman JM, et al.: Prospective multicenter study of pregnancy outcomes in women with heart disease. Circulation. 2001; 104(5): 515–21. PubMed Abstract | Publisher Full Text

[9] 9. Balci A, Sollie-Szarynska KM, van Der Bijl AG, et al.: Prospective validation and assessment of cardiovascular and offspring risk models for pregnant women with congenital heart disease. Heart. 2014; 100(17): 1373–81. PubMed Abstract | Publisher Full Text

[10] 10. Pieper PG: Pre-pregnancy risk assessment and counselling of the cardiac patient. Neth Heart J. 2011; 19(11): 477–81. PubMed Abstract | Publisher Full Text | Free Full Text

[11] 11. Ntusi NB, Mayosi BM: Aetiology and risk factors of peripartum cardiomyopathy: A systematic review. Int J Cardiol. 2009; 131(2): 168–79. PubMed Abstract | Publisher Full Text

[12] 12. Family Health Bureau Sri Lanka: National Maternal Mortality Reviews - 2016 Outcome Dissemination. 2016; 30. Reference Source

[13] 13. Haththotuwa HR, Attygalle D, Jayatilleka AC, et al.: Maternal mortality due to cardiac disease in Sri Lanka. Int J Gynaecol Obstet. 2009; 104(3): 194–8. PubMed Abstract | Publisher Full Text

[14] 14. Family Health Bureau Sri Lanka: Annual Report of the Family Health Bureau 2017. Reference Source

[15] 15. Buddeberg BS, Sharma R, O’Driscoll JM, et al.: Cardiac maladaptation in obese pregnant women at term. Ultrasound Obstet Gynecol. 2019; 54(3): 344–9. PubMed Abstract | Publisher Full Text

[16] 16. Sonaglioni A, Barlocci E, Adda G, et al.: The impact of short-term hyperglycemia and obesity on biventricular and biatrial myocardial function assessed by speckle tracking echocardiography in a population of women with gestational diabetes mellitus. Nutr Metab Cardiovasc Dis. 2022; 32(2): 456–68. PubMed Abstract | Publisher Full Text

[17] 17. Stephen SJ: Changing patterns of mitral stenosis in childhood and pregnancy in Sri Lanka. J Am Coll Cardiol. 1992; 19(6): 1276–84. PubMed Abstract | Publisher Full Text

[18] 18. Agampodi TC, Wickramasinghe ND, Prasanna RIR, et al.: The Rajarata Pregnancy Cohort (RaPCo): study protocol. BMC Pregnancy Childbirth. 2020; 20(1): 374. PubMed Abstract | Publisher Full Text | Free Full Text

[19] 19. Department of Census and Statistics - Sri Lanka: Distict Statistical Handbook Anuradhapura. 2018.

[20] 20. Department of Census and Statistics, Ministry of National Policies and Economic Affairs: Sri Lanka Demographic and Health Survey - 2016 (Full Report). Reference Source

[21] 21. Hettiarachchi A, Agampodi SB: Tools. 2021. http://www.doi.org/10.17605/OSF.IO/RTDCG

Disease burden of cardiovascular conditions complicating pregnancy in Sri Lanka: a protocol

Abstract

Background

Methods

Discussion

Keywords

Revised Amendments from Version 3

Introduction

Objectives

Methods

Study design

Study setting

Figure 1. Spatial distribution of Medical Officer of Health (MOH) areas in Anuradhapura district, Sri Lanka.

Study population

Study sample

Inclusion criteria

Exclusion criteria

Sample size

Figure 2. Flow chart of the study.

Study implementation procedure and recruitment of study participants

Cardiovascular risk assessment

Referral procedure

Performing echocardiogram

Patient follow up

Bias

Outcomes

Data management

Data analysis

Ethical considerations

Confidentiality

Dissemination of findings

Discussion

Data availability

Extended data

References

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