Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Blood gas measures as predictors for neonatal encephalopathy severity

Abstract

Objective

To correlate arterial umbilical cord gas (aUCG) and infant blood gas with severity of neurological injury.

Study design

Retrospective single-site study of infants evaluated for therapeutic hypothermia. Clinical neurological examination and a validated MRI scoring system were used to assess injury severity.

Results

Sixty-eight infants were included. aUCG base deficit (BD) and lactate correlated with infant blood gas counterparts (r = 0.43 and r = 0.56, respectively). aUCG and infant pH did not correlate. Infant blood gas lactate (RADJ2 = 0.40), infant BD (RADJ2 = 0.26), infant pH (RADJ2 = 0.17), aUCG base deficit (RADJ2 = 0.08), and aUCG lactate (RADJ2 = 0.11) were associated with clinical neurological examination severity. aUCG and infant blood gas measures were not correlated with MRI score.

Conclusion

Metabolic measures from initial infant blood gases were most associated with the clinical neurological examination severity and can be used to evaluate hypoxic-ischemic cerebral injury risk.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Scatterplots demonstrating the relationship between the arterial umbilical cord gas (aUCG), the initial infant blood gas measures, and the clinical neurological examination (NE) score.
Fig. 2: Scatterplots demonstrating the relationship between total MRI score with blood gas measures and the clinical neurological examination (NE) score.

References

  1. 1.

    Executive summary: Neonatal encephalopathy and neurologic outcome, second edition. Report of the American College of Obstetricians and Gynecologists’ Task Force on Neonatal Encephalopathy. Obstet Gynecol. 2014;123:896–901.

    Article  Google Scholar 

  2. 2.

    Jacobs SE, Berg M, Hunt R, Tarnow-Mordi WO, Inder TE, Davis PG. Cooling for newborns with hypoxic ischaemic encephalopathy. Cochrane Database Syst Rev. 2013;2013:CD003311.

  3. 3.

    Malin GL, Morris RK, Khan KS. Strength of association between umbilical cord pH and perinatal and long term outcomes: systematic review and meta-analysis. BMJ. 2010;340:c1471.

    Article  Google Scholar 

  4. 4.

    Westgate J, Garibaldi JM, Greene KR. Umbilical cord blood gas analysis at delivery: a time for quality data. BJOG Int J Obstet Gynaecol. 1994;101:1054–63.

    CAS  Article  Google Scholar 

  5. 5.

    White CRH, Doherty DA, Henderson JJ, Kohan R, Newnham JP, Pennell CE. Benefits of introducing universal umbilical cord blood gas and lactate analysis into an obstetric unit: Universal cord blood gas and lactate analysis. Aust NZ J Obstet Gynaecol. 2010;50:318–28.

    Article  Google Scholar 

  6. 6.

    Armstrong L, Stenson BJ. Use of umbilical cord blood gas analysis in the assessment of the newborn. Arch Dis Child Fetal Neonatal Ed. 2007;92:F430–4.

    CAS  Article  Google Scholar 

  7. 7.

    ACOG Committee on Obstetric Practice. ACOG Committee Opinion No. 348, November 2006: Umbilical cord blood gas and acid-base analysis. Obstet Gynecol. 2006;108:1319–22.

    Article  Google Scholar 

  8. 8.

    Cahill A, Mathur A, Smyser C, et al. Neurologic injury in acidemic term infants. Am J Perinatol. 2016;34:668–75.

    Article  Google Scholar 

  9. 9.

    Casey BM, Goldaber KG, McIntire DD, Leveno KJ. Outcomes among term infants when two-hour postnatal pH is compared with pH at delivery. Am J Obstet Gynecol. 2001;184:447–50.

    CAS  Article  Google Scholar 

  10. 10.

    Andres RL, Saade G, Gilstrap LC, Wilkins I, Witlin A, Zlatnik F, et al. Association between umbilical blood gas parameters and neonatal morbidity and death in neonates with pathologic fetal acidemia. Am J Obstet Gynecol. 1999;181:867–71.

    CAS  Article  Google Scholar 

  11. 11.

    Low JA, Panagiotopoulos C, Derrick EJ. Newborn complications after intrapartum asphyxia with metabolic acidosis in the term fetus. Am J Obstet Gynecol. 1994;170:1081–7.

    CAS  Article  Google Scholar 

  12. 12.

    Knutzen L, Anderson-Knight H, Svirko E, Impey L. Umbilical cord arterial base deficit and arterial pH as predictors of adverse outcomes among term neonates. Int J Gynaecol Obstet. 2018;142:66–70.

    CAS  Article  Google Scholar 

  13. 13.

    Tuuli MG, Stout MJ, Shanks A, Odibo AO, Macones GA, Cahill AG. Umbilical cord arterial lactate compared with pH for predicting neonatal morbidity at term. Obstet Gynecol. 2014;124:756–61.

    CAS  Article  Google Scholar 

  14. 14.

    Wiberg N, Källén K, Herbst A, Olofsson P. Relation between umbilical cord blood pH, base deficit, lactate, 5-minute Apgar score and development of hypoxic ischemic encephalopathy. Acta Obstet Gynecol Scand. 2010;89:1263–9.

    CAS  Article  Google Scholar 

  15. 15.

    Ambalavanan N, Carlo WA, Shankaran S, Bann CM, Emrich SL, Higgins RD, et al. Predicting outcomes of neonates diagnosed with hypoxemic-ischemic encephalopathy. Pediatrics. 2006;118:2084–93.

    Article  Google Scholar 

  16. 16.

    Vesoulis ZA, Liao SM, Rao R, Trivedi SB, Cahill AG, Mathur AM. Re-examining the arterial cord blood gas pH screening criteria in neonatal encephalopathy. Arch Dis Child Fetal Neonatal Ed. 2018;103:F377–82.

    Article  Google Scholar 

  17. 17.

    Sarnat HB, Sarnat MS. Neonatal encephalopathy following fetal distress. A clinical and electroencephalographic study. Arch Neurol. 1976;33:696–705.

    CAS  Article  Google Scholar 

  18. 18.

    Thompson C, Puterman A, Linley L, Hann F, Elst C, Molteno C, et al. The value of a scoring system for hypoxic ischaemic encephalopathy in predicting neurodevelopmental outcome. Acta Paediatr. 1997;86:757–61.

    CAS  Article  Google Scholar 

  19. 19.

    Miller SP, Latal B, Clark H, Barnwell A, Glidden D, Barkovich AJ, et al. Clinical signs predict 30-month neurodevelopmental outcome after neonatal encephalopathy. Am J Obstet Gynecol. 2004;190:93–9.

    Article  Google Scholar 

  20. 20.

    Benninger KL, Inder TE, Goodman AM, Cotten CM, Nordli DR, Shah TA, et al. Perspectives from the Society for Pediatric Research. Neonatal encephalopathy clinical trials: developing the future. Pediatr Res. 2020. http://www.nature.com/articles/s41390-020-0859-9.

  21. 21.

    Shankaran S, Laptook AR, Ehrenkranz RA, Tyson JE, McDonald SA, Donovan EF, et al. Whole-body hypothermia for neonates with hypoxic-ischemic encephalopathy. N Engl J Med. 2005;353:1574–84.

    CAS  Article  Google Scholar 

  22. 22.

    Shankaran S, Laptook AR, Tyson JE, Ehrenkranz RA, Bann CM, Das A, et al. Evolution of encephalopathy during whole body hypothermia for neonatal hypoxic-ischemic encephalopathy. J Pediatr. 2012;160:567–72.e3.

    Article  Google Scholar 

  23. 23.

    Inder TE, Volpe JJ. Chapter 20—Hypoxic-ischemic injury in the term infant: clinical-neurological features, diagnosis, imaging, prognosis, therapy. In: Volpe JJ, Inder TE, Darras BT, de Vries LS, du Plessis AJ, Neil JJ, et al., editors. Volpe’s neurology of the newborn. 6th ed. Elsevier; 2018. p. 510–563.e15.

  24. 24.

    Perez JMR, Golombek SG, Sola A, et al. Clinical hypoxic-ischemic encephalopathy score of the Iberoamerican Society of Neonatology (Siben): a new proposal for diagnosis and management. Rev Assoc Med Bras. 2017;63:64–9.

    Article  Google Scholar 

  25. 25.

    Perez JMR, Golombek SG, Alpan G, Sola A. Using a novel laminar flow unit provided effective total body hypothermia for neonatal hypoxic encephalopathy. Acta Paediatr. 2015;104:e483–8.

    Article  Google Scholar 

  26. 26.

    Groenendaal F, de Vries LS. Fifty years of brain imaging in neonatal encephalopathy following perinatal asphyxia. Pediatr Res. 2017;81:150–5.

    Article  Google Scholar 

  27. 27.

    Weeke LC, Groenendaal F, Mudigonda K, Blennow M, Lequin MH, Meiners LC, et al. A novel magnetic resonance imaging score predicts neurodevelopmental outcome after perinatal asphyxia and therapeutic hypothermia. J Pediatr. 2018;192:33–40.e2.

    Article  Google Scholar 

  28. 28.

    Gunn AJ, Wyatt JS, Whitelaw A, Barks J, Azzopardi D, Ballard R, et al. Therapeutic hypothermia changes the prognostic value of clinical evaluation of neonatal encephalopathy. J Pediatr. 2008;152:55–58.e1.https://doi.org/10.1016/C2010-0-68825-0.

    Article  Google Scholar 

  29. 29.

    Kaufman SA, Miller SP, Ferriero DM, Glidden DH, Barkovich AJ, Partridge JC. Encephalopathy as a predictor of magnetic resonance imaging abnormalities in asphyxiated newborns. Pediatr Neurol. 2003;28:342–6.

    Article  Google Scholar 

  30. 30.

    Walsh BH, Neil J, Morey J, Yang E, Silvera MV, Inder TE, et al. The frequency and severity of magnetic resonance imaging abnormalities in infants with mild neonatal encephalopathy. J Pediatr. 2017;187:26–33.e1.

    Article  Google Scholar 

  31. 31.

    Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.

    Article  Google Scholar 

  32. 32.

    Olsen IE, Groveman SA, Lawson ML, Clark RH, Zemel BS. New intrauterine growth curves based on United States data. Pediatrics. 2010;125:e214–24.

    Article  Google Scholar 

  33. 33.

    Holzmann M, Cnattingius S, Nordström L. Lactate production as a response to intrapartum hypoxia in the growth-restricted fetus: hypoxia and lactate production in the IUGR fetus. BJOG Int J Obstet Gynaecol. 2012;119:1265–9.

    CAS  Article  Google Scholar 

  34. 34.

    Milsom I, Ladfors L, Thiringer K, Niklasson A, Odeback A, Thornberg E. Influence of maternal, obstetric and fetal risk factors on the prevalence of birth asphyxia at term in a Swedish urban population. Acta Obstet Gynecol Scand. 2002;81:909–17.

  35. 35.

    Inder TE, Volpe JJ. Chapter 17—Intrauterine, Intrapartum Assessments in the Term Infant. In: Volpe JJ, Inder TE, Darras BT, de Vries LS, du Plessis AJ, Neil JJ, et al., editors. Volpe’s neurology of the newborn. 6th ed. Elsevier; 2018. p. 458–483.e458.

  36. 36.

    Cahill AG, Macones GA, Smyser CD, López JD, Inder TE, Mathur AM. Umbilical artery lactate correlates with brain lactate in term infants. Am J Perinatol. 2017;34:535–40.

    PubMed  Google Scholar 

  37. 37.

    Low JA, Lindsay BG, Derrick EJ. Threshold of metabolic acidosis associated with newborn complications. Am J Obstet Gynecol. 1997;177:1391–4.

    CAS  Article  Google Scholar 

  38. 38.

    Fauchère J-C, Bauschatz A, Arlettaz R, Zimmermann-Bär U, Bucher H. Agreement between capillary and arterial lactate in the newborn. Acta Paediatr. 2007;91:78–81.

    Article  Google Scholar 

  39. 39.

    Al Balushi A, Guilbault M-P, Wintermark P. Secondary increase of lactate levels in asphyxiated newborns during hypothermia treatment: reflect of suboptimal hemodynamics (A case series and review of the literature). Am J Perinatol Rep. 2015;06:e48–58.

    Article  Google Scholar 

  40. 40.

    Cousineau J, Anctil S, Carceller A, Gonthier M, Delvin EE. Neonate capillary blood gas reference values. Clin Biochem. 2005;38:905–7.

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank Elizabeth Singh, Kirsten Thiim, and Song Ha Lee, our research assistants at BWH, for their assistance in collecting data.

Funding

This study was undertaken with local departmental funding support.

Author information

Affiliations

Authors

Contributions

KS: had substantial contributions to conception and design, acquisition of data, analysis and interpretation of data, drafted the article, and had final approval of the version to be published. KJS: had substantial contributions to conception, acquisition of data, analysis and interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. MEl-D: had substantial contributions to conception and design, acquisition of data, interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. ES: had substantial contributions to acquisition of data, interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. EY: had substantial contributions to acquisition of data, interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. BHW: had substantial contributions to conception and design, acquisition of data, interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. JNR: had substantial contributions to conception and interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. SC: had substantial contributions to acquisition of data, analysis and interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. JJV: had substantial contributions to conception and interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published. TEI: had substantial contributions to conception and design, acquisition and interpretation of data, contributed to revising it critically for important intellectual content, and had final approval of the version to be published.

Corresponding author

Correspondence to Terrie E. Inder.

Ethics declarations

Conflict of interest

The author declares no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sakpichaisakul, K., Supapannachart, K.J., El-DIb, M. et al. Blood gas measures as predictors for neonatal encephalopathy severity. J Perinatol (2021). https://doi.org/10.1038/s41372-021-01075-w

Download citation

Search

Quick links