Journal of Pregnancy and Neonatal Medicine

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

Opinion Article - Journal of Pregnancy and Neonatal Medicine (2024) Volume 8, Issue 1

Gestational Age Assessment: Tools and Methods in Clinical Practice

Kelly Taylor *

Department of Translational Medicine (DiMeT), University of Eastern Piedmont/Piemonte Orientale (UPO), Italy

*Corresponding Author:
Kelly Taylor
Department of Translational Medicine (DiMeT), University of Eastern Piedmont/Piemonte Orientale (UPO), Italy
E-mail: taylor66@italy.in.edu

Received:27-Jan-2024, Manuscript No. AAPNM-24-126905; Editor assigned: 30-Jan-2024, PreQC No. AAPNM-24-126905 (PQ); Reviewed:13-Feb-2024, QC No. AAPNM-24-126905; Revised:17-Feb-2024, Manuscript No. AAPNM-24-126905(R); Published:24-Feb-2024, DOI:10.35841/aapnm -8.1.186

Citation: Taylor K. Gestational Age Assessment: Tools and Methods in Clinical Practice. J Preg Neonatal Med. 2023;8(1):186

Visit for more related articles at Journal of Pregnancy and Neonatal Medicine

Introduction

Gestational age assessment is a critical aspect of obstetric care, providing essential information for monitoring fetal development, predicting delivery dates, and identifying potential complications. Accurate determination of gestational age is crucial for appropriate management of pregnancy and neonatal care. Various tools and methods are employed in clinical practice to assess gestational age, each with its advantages, limitations, and considerations. This article explores the prominent tools and methods utilized in clinical settings for gestational age assessment [1].

Ultrasound remains the gold standard for gestational age assessment due to its accuracy and non-invasive nature. Transabdominal or transvaginal ultrasound is performed to measure fetal biometric parameters, including crown-rump length (CRL), biparietal diameter (BPD), head circumference (HC), and femur length (FL). These measurements are compared to standardized growth charts to estimate gestational age. Ultrasound is particularly reliable in the first trimester, providing accurate dating within a few days [2].

However, ultrasound accuracy may diminish in late pregnancy due to variations in fetal growth rates and positioning. Additionally, factors like maternal obesity and fetal anomalies can affect measurement precision. Despite these limitations, ultrasound remains an indispensable tool in gestational age assessment [3].

Clinical assessment involves estimating gestational age based on the last menstrual period (LMP) and physical examination findings. The LMP method relies on the assumption of a regular 28-day menstrual cycle, with ovulation occurring on day 14. However, variability in menstrual cycle length and recall errors can lead to inaccuracies, particularly in cases of irregular cycles or contraceptive use [4].

Physical examination indicators such as uterine size, fetal heart rate, and fetal movements can complement LMP dating. Fundal height measurement correlates with gestational age and helps monitor fetal growth. Combining LMP with clinical assessment enhances accuracy, especially when ultrasound dating is unavailable or inconclusive [5].

Fetal biometry charts compile normative data on fetal growth parameters at different gestational ages. These charts serve as reference standards for assessing fetal size and estimating gestational age. Widely used charts include those developed by Hadlock, Robinson, and others, which provide percentile values for CRL, BPD, HC, and FL measurements [6].

Fetal biometry charts are invaluable tools for interpreting ultrasound measurements and identifying deviations from expected growth patterns. They facilitate the diagnosis of intrauterine growth restriction (IUGR) and macrosomia, guiding clinical decision-making regarding fetal surveillance and management [7].

Gestational age assessment continues beyond birth through neonatal examination and scoring systems. The New Ballard Score and the Dubowitz/Ballard Score are commonly used methods for assessing newborn maturity based on physical and neuromuscular characteristics. These scoring systems evaluate parameters such as skin texture, lanugo, plantar creases, and reflexes to estimate gestational age accurately [8].

Neonatal assessment is particularly valuable when gestational age is uncertain or when discrepancies exist between clinical and ultrasound estimates. It aids in determining the need for specialized care and monitoring for potential complications associated with prematurity or postmaturity [9].

Biochemical markers, such as levels of certain hormones or proteins in maternal serum or amniotic fluid, have been explored for their potential in gestational age determination. Examples include human chorionic gonadotropin (hCG), alpha-fetoprotein (AFP), and pregnancy-associated plasma protein-A (PAPP-A). These markers exhibit temporal changes during pregnancy and may serve as adjuncts to ultrasound or clinical assessment in specific clinical scenarios. While biochemical markers show promise, their clinical utility in routine gestational age assessment remains limited. Research continues to evaluate their accuracy and reliability, especially in cases where conventional methods are inconclusive or unavailable [10].

Conclusion

Gestational age assessment in clinical practice relies on a combination of tools and methods, each contributing to a comprehensive understanding of fetal development and maturity. While ultrasound imaging remains the cornerstone of gestational age determination, clinical assessment, fetal biometry charts, neonatal examination, and biochemical markers complement and enhance accuracy. A multi-modal approach ensures robust and reliable gestational age assessment, facilitating optimal obstetric and neonatal care. Continuous research and refinement of techniques strive to further improve the precision and utility of gestational age assessment in clinical practice.

References

  1. Willis GR, Kourembanas S, Mitsialis SA. Therapeutic applications of extracellular vesicles: perspectives from newborn medicine. Methods Mol Biol. 2017:409-32.
  2. Indexed at, Google Scholar, Cross Ref

  3. Lucas E, Bevan A. Nurses’ underuse of non-pharmacological pain relief interventions in preterm infants. Nurs Child Young People. 2020;32(1).
  4. Indexed at, Google Scholar, Cross Ref

  5. Landon MB, Gabbe SG. Fetal surveillance and timing of delivery in pregnancy complicated by diabetes mellitus. Clin Obstet Gynecol. 1996;23(1):109-23.
  6. Indexed at, Google Scholar, Cross Ref

  7. van Kammen CM, van Woudenberg SJ, Schiffelers R, et al. Nanomedicines: An approach to treat placental insufficiency and the current challenges. J Control Release. 2023;360:57-68.
  8. Indexed at, Google Scholar, Cross Ref

  9. Rodgers SK, Chang C, DeBardeleben JT, et al. Normal and abnormal US findings in early first-trimester pregnancy: review of the society of radiologists in ultrasound 2012 consensus panel recommendations. Radiographics. 2015;35(7):2135-48.
  10. Indexed at, Google Scholar, Cross Ref

  11. Kamath-Rayne BD, Smith HC, Muglia LJ, et al. Amniotic fluid: the use of high-dimensional biology to understand fetal well-being. Reprod Sci. 2014;21(1):6-19.
  12. Indexed at, Google Scholar, Cross Ref

  13. Meads CA, Cnossen JS, Meher S, et al. Methods of prediction and prevention of pre-eclampsia: systematic reviews of accuracy and effectiveness literature with economic modelling.
  14. Indexed at, Google Scholar, Cross Ref

  15. Achola KA, Kajjo D, Santos N, et al. Implementing the WHO Safe Childbirth Checklist modified for preterm birth: lessons learned and experiences from Kenya and Uganda. BMC Health Serv Res. 2022;22(1):1-3.
  16. Indexed at, Google Scholar, Cross Ref

  17. Vigod S, Hussain-Shamsy N, Grigoriadis S, et al. A patient decision aid for antidepressant use in pregnancy: study protocol for a randomized controlled trial. Trials. 2016;17(1):1-9.
  18. Indexed at, Google Scholar, Cross Ref

  19. Kannieappan LM, Deussen AR, Grivell RM, et al. Developing a tool for obtaining maternal skinfold thickness measurements and assessing inter-observer variability among pregnant women who are overweight and obese. BMC Pregnancy Childbirth. 2013;13:1-6.
  20. Indexed at, Google Scholar, Cross Ref

Get the App