Pregnancy introduces major physiological changes that also alter biochemical analytes. Maternal and perinatal health can be optimized by early intervention and therefore, pregnancy-specific reference intervals (RIs) for the local population are warranted. While the second and third trimester-specific changes are well described, the first trimester is less well characterized. We therefore wanted to facilitate early detection of abnormalities by generating first trimester reference values for 29 common analytes.
In a prospective early pregnancy (PEP) cohort (2016–2017), 203 pregnant women were recruited from 4 to 8 weeks’ gestation. Consecutive blood samples were drawn every 2 weeks until an ongoing second trimester pregnancy (n = 164) or a miscarriage (n = 39) occurred. After exclusion of women with complicated pregnancies or deliveries (n = 42), 122 women were included. The serum samples collected at <6, 6–8, 8–10, 10–12 and >12 weeks’ gestation were analyzed for 29 common analytes. Subsequently the RIs were calculated according to the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) recommendations (2.5–97.5th percentiles) and compared with the conventional RIs for non-pregnant women.
Human chorionic gonadotropin (hCG), progesterone (P4), estradiol (E2), pregnancy-associated plasma protein A (PAPP-A), cancer antigen 125 (CA125), thyroid stimulating hormone (TSH), creatinine (CREA) and albumin (ALB) showed an early pregnancy-dependent change compared with conventional limits. For ALB the change was seen at 5.5 weeks’ gestation.
We report gestational age-specific RIs available from the early part of the first trimester applicable to everyday clinical care of pregnant women. Well-known alterations of RIs seen in later trimesters are also observed in the first.
This study received invaluable practical assistance from the staff of the Departments of Clinical Biochemistry and Clinical Research at North Zealand Hospital, and from the data management of Steen Rasmussen, MSC.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: Grants from the North Zealand Hospital Research Council, the Gangsted Foundation, the Foundation for Development of Danish Private Practice, the Tvergaard Foundation, the AP Møller Foundation, the Foundation from Danish Doctors Pension and Copenhagen University made this research possible. No funders were involved in the design, acquisition, analysis or interpretation of data prior to submission.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
1. Poon LC, McIntyre HD, Hyett JA, da Fonseca EB, Hod M. The first-trimester of pregnancy – a window of opportunity for prediction and prevention of pregnancy complications and future life. Diabetes Res Clin Pract 2018;145:20–30.10.1016/j.diabres.2018.05.002Search in Google Scholar PubMed
2. Rolnik DL, Wright D, Poon LCY, Syngelaki A, O’Gorman N, de Paco Matallana C, et al. ASPRE trial: performance of screening for preterm pre-eclampsia. Ultrasound Obstet Gynecol 2017;50:492–5.10.1002/uog.18816Search in Google Scholar PubMed
3. Tan MY, Poon LC, Rolnik DL, Syngelaki A, de Paco Matallana C, Akolekar R, et al. Prediction and prevention of small-for-gestational-age neonates: evidence from SPREE and ASPRE. Ultrasound Obstet Gynecol 2018;52:52–9.10.1002/uog.19077Search in Google Scholar PubMed
4. Halscott TL, Ramsey PS, Reddy UM. First trimester screening cannot predict adverse pregnancy outcomes. Prenat Diagn 2014;34:668–76.Search in Google Scholar
5. Kane SC, Da Silva Costa F, Brennecke S. First trimester biomarkers in the prediction of later pregnancy complications. Biomed Res Int 2014;2014(i).10.1155/2014/807196Search in Google Scholar PubMed PubMed Central
6. Wortelboer EJ, Koster MP, Kuc S, Eijkemans MJ, Bilardo CM, Schielen PC, et al. Longitudinal trends in fetoplacental biochemical markers, uterine artery pulsatility index and maternal blood pressure during the first trimester of pregnancy. Ultrasound Obstet Gynecol 2011;38:383–8.10.1002/uog.9029Search in Google Scholar PubMed
7. WHO | Millennium Development Goals (MDGs). WHO [Internet]. 2017 [cited 2019 Feb 27]; Available from: https://www.who.int/topics/millennium_development_goals/en/.Search in Google Scholar
8. Klajnbard A, Szecsi PB, Colov NP, Andersen MR, Jørgensen M, Bjørngaard B, et al. Laboratory reference intervals during pregnancy, delivery and the early postpartum period. Clin Chem Lab Med 2010;48:237–48.10.1515/CCLM.2010.033Search in Google Scholar PubMed
9. Larsson A, Palm M, Hansson L-O, Axelsson O. Reference values for clinical chemistry tests during normal pregnancy. BJOG Int J Obstet Gynaecol 2008;115:874–81.10.1111/j.1471-0528.2008.01709.xSearch in Google Scholar PubMed
10. Abbassi-Ghanavati M, Greer LG, Cunningham FG. Pregnancy and laboratory studies: a reference table for clinicians. Obstet Gynecol 2009;114:1326–31.10.1097/AOG.0b013e3181c2bde8Search in Google Scholar PubMed
11. Solberg HE. International Federation of Clinical Chemistry. Scientific committee, clinical section. Expert Panel on Theory of Reference Values and International Committee for Standardization in Haematology, Standing Committee on Reference Values. Approved Recommendation. Ann Biol Clin (Paris) 1987;45:237–41.Search in Google Scholar
12. Jin Y, Lu J, Jin H, Fei C, Xie X, Zhang J. Reference intervals for biochemical, haemostatic and haematological parameters in healthy Chinese women during early and late pregnancy. Clin Chem Lab Med 2018;56:973–9.10.1515/cclm-2017-0804Search in Google Scholar PubMed
13. Dai Y, Liu J, Yuan E, Li Y, Wang Q, Jia L, et al. Gestational age-specific reference intervals for 15 biochemical measurands during normal pregnancy in China. Ann Clin Biochem 2018;55:446–52.10.1177/0004563217738801Search in Google Scholar PubMed
14. Van Buul EJ, Steegers EA, Jongsma HW, Eskes TK, Thomas CM, Hein PR. Haematological and biochemical profile of uncomplicated pregnancy in nulliparous women ; a longitudinal study. Neth J Med 1995;46:73–85.10.1016/0300-2977(94)00104-HSearch in Google Scholar
15. Solberg HE. The theory of reference values Part 5. Statistical treatment of collected reference values. Determination of reference limits. J Clin Chem Clin Biochem 1983;21:749–60.10.1016/0009-8981(84)90319-XSearch in Google Scholar
16. Hadlock FP, Shah YP, Kanon DJ, Lindsey JV. Fetal crown-rump length: reevaluation of relation to menstrual age (5–18 weeks) with high-resolution real-time US. Radiology 1992;182:501–5.10.1148/radiology.182.2.1732970Search in Google Scholar PubMed
18. R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2017.Search in Google Scholar
19. Rigby RA, Stasinopoulos DM. Generalized Additive Models for Location, Scale and Shape [Internet]. Vol. 54, Journal of the Royal Statistical Society. Series C (Applied Statistics). Wiley Royal Statistical Society; 2005 [cited 2019 May 14]. p. 507–54. Available from: https://www.jstor.org/stable/3592732.10.1111/j.1467-9876.2005.00510.xSearch in Google Scholar
23. Donders AR, van der Heijden GJ, Stijnen T, Moons KG. Review: a gentle introduction to imputation of missing values. J Clin Epidemiol 2006;59:1087–91.10.1016/j.jclinepi.2006.01.014Search in Google Scholar PubMed
25. Nepomnaschy PA, Weinberg CR, Wilcox AJ, Baird DD. Urinary hCG patterns during the week following implantation. Hum Reprod 2008;23:271–7.10.1093/humrep/dem397Search in Google Scholar PubMed PubMed Central
31. Lejeune B, Bourdoux P, Lemone M, de Nayer P, Kinthaert J, Steirteghem A Van, et al. Regulation of maternal thyroid during pregnancy. J Clin Endocrinol Metab 2009;71:276–87.10.1210/jcem-71-2-276Search in Google Scholar
32. Devroey P, Camus M, Palermo G, Smitz J, Van Waesberghe L, Wisanto A, et al. Placental production of estradiol and progesterone after oocyte donation in patients with primary ovarian failure. Am J Obstet Gynecol 1990;162:66–70.10.1016/0002-9378(90)90822-OSearch in Google Scholar
34. Gziri MM, Han SN, Hanssens M, Lotgerink A, Amant F, Van Calsteren K. Physiologic variations of serum tumor markers in gynecological malignancies during pregnancy: a systematic review. BMC Med 2012;10:86.10.1186/1741-7015-10-86Search in Google Scholar PubMed PubMed Central
35. Pillai RN, Konje JC, Tincello DG, Potdar N. Role of serum biomarkers in the prediction of outcome in women with threatened miscarriage: a systematic review and diagnostic accuracy meta-analysis. Hum Reprod Update 2016;22:228–39.10.1093/humupd/dmv054Search in Google Scholar PubMed
37. Soma-Pillay P, Soma-Pillay P, Nelson-Piercy C, Tolppanen H, Mebazaa A, Mebazaa A. Physiological changes in pregnancy: review articles. Cardiovasc J Afr 2016;27:89–94.10.5830/CVJA-2016-021Search in Google Scholar
39. Rustad P, Felding P, Franzson L, Kairisto V, Lahti A, Mårtensson A, et al. The Nordic Reference Interval Project 2000: Recommended reference intervals for 25 common biochemical properties. Scand J Clin Lab Invest 2004;64:271–83.10.1080/00365510410006324Search in Google Scholar
43. Belo L, Santos-Silva A, Rocha S, Caslake M, Cooney J, Pereira-Leite L, et al. Fluctuations in C-reactive protein concentration and neutrophil activation during normal human pregnancy. Eur J Obstet Gynecol Reprod Biol 2005;123:46–51.10.1016/j.ejogrb.2005.02.022Search in Google Scholar PubMed
44. Elliott P, Peakman TC. The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int J Epidemiol 2008;37:234–44.10.1093/ije/dym276Search in Google Scholar PubMed
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2019-0495).
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