Integration of suboptimal health status evaluation as a criterion for prediction of preeclampsia is strongly recommended for healthcare management in pregnancy: a prospective cohort study in a Ghanaian population

Abstract

Background

Normotensive pregnancy may develop into preeclampsia (PE) and other adverse pregnancy complications (APCs), for which the causes are still unknown. Suboptimal health status (SHS), a physical state between health and disease, might contribute to the development and progression of PE. By integration of a routine health measure in this Ghanaian Suboptimal Health Cohort Study, we explored the usefulness of a 25-question item SHS questionnaire (SHSQ-25) for early screening and prediction of normotensive pregnant women (NTN-PW) likely to develop PE.

Methods

We assessed the overall health status among a cohort of 593 NTN-PW at baseline (10–20 weeks gestation) and followed them at 21–31 weeks until 32–42 weeks. After an average of 20 weeks follow-up, 498 participants returned and were included in the final analysis. Hematobiochemical, clinical and sociodemographic data were obtained.

Results

Of the 498 participants, 49.8% (248/498) had ‘high SHS’ at baseline (61.7% (153/248) later developed PE) and 38.3% (95/248) were NTN-PW, whereas 50.2% (250/498) had ‘optimal health’ (17.6% (44/250) later developed PE) and 82.4% (206/250) were NTN-PW. At baseline, high SHS score yielded a significantly (p < 0.05) increased adjusted odds ratio, a wider area under the curve (AUC) and a higher sensitivity and specificity for the prediction of PE (3.67; 0.898; 91.9% and 87.8%), PE coexisting with intrauterine growth restriction (2.86, 0.838; 91.5% and 75.9%), stillbirth (2.52; 0.783; 96.6% and 60.0%), hemolysis elevated liver enzymes and low platelet count (HELLP) syndrome (2.08; 0.800; 97.2% and 63.8%), acute kidney injury (2.20; 0.825; 95.3% and 70.0%) and dyslipidaemia (2.80; 0.8205; 95.7% and 68.4%) at 32–42 weeks gestation.

Conclusions

High SHS score is associated with increased incidence of PE; hence, SHSQ-25 can be used independently as a risk stratification tool for adverse pregnancy outcomes thereby creating an opportunity for predictive, preventive and personalized medicine.

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Abbreviations

SHS:

suboptimal health status

OHS:

optimal health status

SHSQ-25:

25-question-based suboptimal health status questionnaire

GHOACS:

Ghanaian Suboptimal Health Cohort Study

PE:

preeclampsia

APCs:

adverse pregnancy complications

PPPM:

preventive, predictive and personalized medicine

IUGR:

intrauterine growth restriction

HELLP:

hemolysis elevated liver enzymes and low platelet count

SBP:

systolic blood pressure

DBP:

diastolic blood pressure

Mg:

magnesium

Ca:

calcium

Na:

sodium

K:

potassium

Cl:

chloride

LDH:

lactate dehydrogenase

UA:

uric acid

RDW:

red cell distribution width

FBG:

fasting blood glucose

TG:

triglyceride

TC:

total cholesterol

HDL-c:

high-density lipoprotein cholesterol

LDL-c:

low-density lipoprotein cholesterol

ALT:

alanine aminotransferase

AST:

aspartate aminotransferase

GGT:

gamma glutamyl transferase

TP:

total protein

ALB:

albumin

ALP:

alkaline phosphatase

aOR:

adjusted odds ratio

CI:

confidence interval

ROC:

receiver’s operating characteristics

AUC:

area under the ROC curve

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Acknowledgements

We wish to thank the biomedical staff of the Department of Biochemistry and Serology, and midwives of the Department of Obstetrics and Gynaecology of the Komfo Anokye Teaching Hospital, Ghana, for their support during the participant’s recruitment and biological sample processing. We also thank the research assistants of the Department of Molecular Medicine, Kwame Nkrumah University of Science and Technology for their support during the biological sample analysis. We finally thank the American Association of Clinical Chemistry (AACC) Academy Research Fellows for selecting our abstract coined from the present study entitled, ‘Algorithm of Suboptimal Health Status, Serum Magnesium and Calcium Levels as a Novel Approach for Prediction and Identification of Pregnant Women Likely to Develop Preeclampsia and Adverse Perinatal Complications in a Ghanaian Population’ for Scientific Excellence in Maternal and Foetal Medicine and AACC Academy’s Distinguished Abstract Award at the 71st AACC Scientific Annual Meeting, Anaheim, CA.

Funding

This work was supported by the Australia-China International Collaborative Grant (NHMRC-APP1112767-NSFC81561120) and Edith Cowan University (ECU)-Collaborative Enhancement Scheme Round 1 (G1003363). Enoch Odame Anto was supported by ECU-International Postgraduate Research Scholarship.

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Contributions

EOA, PR, DC and WW conceived the study. EOA and CAT performed the investigation and collected the data. EOA performed the statistical analysis. EOA, PR, DC, EA, YW and WW wrote the paper. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Wei Wang.

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The authors declare that they have no conflict of interest.

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Ethical approval and consent to participate

Approval for this study was obtained from the Committee on Human Research Publication and Ethics (CHRPE) of the School of Medical Science (SMS) /KNUST and Komfo Anokye Teaching Hospital (KATH) (CHRPE/AP/146/17) and the Human Research Ethics Committee of Edith Cowan University (ECU) (17509). This study was conducted in accordance with the guidelines of the Helsinki Declaration. Written informed consent in the form of a signature and fingerprint was obtained from all participants and legally authorized representatives after the protocol of the study was explained to them in plain English language and native Ghanaian language where appropriate.

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Anto, E.O., Roberts, P., Coall, D. et al. Integration of suboptimal health status evaluation as a criterion for prediction of preeclampsia is strongly recommended for healthcare management in pregnancy: a prospective cohort study in a Ghanaian population. EPMA Journal 10, 211–226 (2019). https://doi.org/10.1007/s13167-019-00183-0

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Keywords

  • Suboptimal health status
  • Preeclampsia
  • Pregnancy complications
  • Patient stratification
  • Primary healthcare
  • Risk assessment
  • Population screening
  • Education
  • Predictive preventive personalized medicine