Prediction of adverse maternal outcomes associated with preeclampsia in twin pregnancies – BMC Pregnancy and Childbirth

Report on a Retrospective Cohort Study of Preeclampsia and its Contribution to Sustainable Development Goals

Objective: Advancing Maternal Health in Line with SDG 3

This report outlines the methodology of a retrospective cohort study conducted at the Fujian Maternal and Child Health Hospital between January 2014 and December 2021. The primary objective was to analyze adverse maternal outcomes in pregnant women with preeclampsia. This research directly supports the United Nations Sustainable Development Goal 3 (Good Health and Well-being), specifically targeting the reduction of maternal mortality (Target 3.1) by improving the prediction and management of high-risk pregnancies.

Methodological Framework for Achieving Health-Related SDGs

Study Population and Alignment with SDG 3 and SDG 5

The study focused on a critical demographic for achieving SDG 3 (Good Health and Well-being) and SDG 5 (Gender Equality) by investigating maternal health. The cohort included:

• Total participants: Pregnant women with preeclampsia (N=3029)
• Singleton pregnancies: 2570
• Twin pregnancies: 459

Twin pregnancies were further stratified into groups with and without adverse maternal outcomes to identify risk factors, a crucial step in developing targeted interventions that promote the health and well-being of women.

Diagnostic Framework and Contribution to SDG 10

The diagnostic criteria were established using internationally recognized models, ensuring the study’s relevance to global health initiatives and contributing to SDG 10 (Reduced Inequalities) by utilizing tools applicable in diverse healthcare settings.

Adverse Maternal Outcomes

Defined according to the fullPIERS and miniPIERS models, which are vital for risk assessment in both high- and low-resource settings. An adverse outcome was identified by the presence of one or more of the following:

1. Maternal death
2. Cardiovascular and respiratory complications
3. Central nervous system complications (e.g., eclampsia, stroke)
4. Abnormal liver function
5. Acute renal insufficiency
6. Hematological complications (e.g., platelet count 9/L, DIC)
7. Obstetric complications (e.g., HELLP syndrome, placental abruption, severe postpartum hemorrhage)

Condition-Specific Criteria

• Preeclampsia: Diagnosed based on new-onset hypertension after 20 weeks of gestation, accompanied by proteinuria or other systemic signs such as thrombocytopenia, renal insufficiency, or impaired liver function.
• HELLP Syndrome: Defined by hemolysis, elevated liver enzymes (AST ≥ 70 U/L), and low platelets (9/L).
• Disseminated Intravascular Coagulation (DIC): Characterized as a widespread activation of the coagulation system secondary to obstetric complications.

Exclusion Criteria

To ensure data integrity, the study excluded cases with pre-existing adverse outcomes, incomplete information, abortions before 28 weeks, or postpartum preeclampsia.

Data Collection and Analysis for Evidence-Based Health Policy

A comprehensive data collection strategy was employed to generate robust evidence, a prerequisite for effective health interventions under SDG 3. Information gathered included:

• General and Clinical Information: Demographics (age, BMI), clinical symptoms, and medical history.
• Treatment Information: Use of medications such as magnesium sulfate and antihypertensives.
• Laboratory Indicators: Blood parameters, liver/renal function, coagulation profiles, and novel inflammatory biomarkers (SIRI, SII, NHR, MHR, LHR, PHR).
• Maternal Complications: Co-existing conditions like gestational diabetes, placenta previa, and others.

Statistical Approach

Advanced statistical methods were utilized to ensure the reliability of the findings. The R software package was used for all analyses, which involved:

1. Multiple imputation for missing data (≤ 30%).
2. Appropriate statistical tests (t-test, Mann-Whitney U test, χ2 test) for group comparisons.
3. Least absolute shrinkage and selection operator (LASSO) regression for variable selection to identify key predictors.
4. Development and validation of a predictive nomogram using multivariate logistic regression, bootstrap resampling, and performance assessment via AUC and DCA.

Ethical Governance in Health Research

Ethical Approval

The study adhered to ethical principles fundamental to achieving the SDGs. It received approval from the ethical committee of the Fujian Maternity and Child Health Hospital (2024KY049). As a retrospective analysis of existing medical records with no patient intervention, the requirement for written informed consent was waived, ensuring patient care was not affected.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 3: Good Health and Well-being

  The article is fundamentally centered on health, specifically maternal health. It investigates preeclampsia, a serious pregnancy complication, and aims to predict “adverse maternal outcomes,” including mortality and severe morbidity. This directly aligns with the overarching goal of ensuring healthy lives and promoting well-being for all, with a particular focus on a vulnerable population group (pregnant women).

2. What specific targets under those SDGs can be identified based on the article’s content?

1. Target 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births.

   The research is explicitly designed to study and predict “adverse maternal outcomes,” with the most severe outcome listed being “maternal death.” By developing a predictive model for these outcomes in women with preeclampsia, the research contributes directly to the knowledge base needed to prevent maternal deaths and thus reduce the maternal mortality ratio.

2. Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being.

   Preeclampsia is a non-communicable hypertensive disorder of pregnancy. The article details numerous severe complications (“serious central nervous system, cardiorespiratory, renal, hepatic, haematological or other morbidity”) that can lead to premature mortality or long-term health issues. The study’s goal of creating a predictive model is a form of prevention and a tool to improve treatment strategies for this specific non-communicable disease.

3. Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all.

   The study is conducted in a hospital setting (“Fujian Maternal and Child Health Hospital”) and relies on a wide range of “quality essential health-care services.” This includes the collection of clinical information, use of specific medications (“magnesium sulfate, antihypertensive drugs”), and advanced “laboratory indicators at admission, such as routine blood parameters, liver function, renal function and coagulation function.” The research itself, by aiming to improve diagnostic and predictive capabilities (e.g., using the fullPIERS and miniPIERS models), contributes to enhancing the quality of healthcare provided.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• For Target 3.1 (Reduce maternal mortality):
  • Incidence of Maternal Death: The article explicitly lists “maternal death” as a primary adverse outcome being studied. The count of such events within the study cohort is a direct indicator.
  • Incidence of Severe Maternal Morbidity: The article provides a comprehensive list of conditions that constitute an adverse maternal outcome, such as “eclampsia,” “coma,” “myocardial ischemia,” “acute renal insufficiency,” “HELLP syndrome,” and “placental abruption.” The rate at which these complications occur serves as a key indicator of maternal health status and the effectiveness of care.
• For Target 3.4 (Reduce premature mortality from NCDs):
  • Prevalence and Complication Rate of Preeclampsia: The entire study is based on a cohort of pregnant women with preeclampsia. The rates of specific complications listed, such as “abnormal liver function,” “acute renal insufficiency,” and “cardiovascular and respiratory complications,” are direct measures of the burden of this non-communicable disease.
• For Target 3.8 (Achieve universal health coverage):
  • Use of Essential Medicines: The article mentions tracking the “use [of] medication for treatment: magnesium sulfate, antihypertensive drugs.” The proportion of patients receiving these essential, life-saving drugs is an indicator of access to quality care.
  • Availability and Use of Diagnostic Services: The research relies on extensive laboratory tests, including “routine blood parameters, liver function, renal function and coagulation function.” The ability to perform these tests for patients is an implicit indicator of the availability of essential diagnostic services.

4. Table of SDGs, Targets, and Indicators

Source: bmcpregnancychildbirth.biomedcentral.com