CC BY 4.0 · Journal of Child Science 2021; 11(01): e125-e132
DOI: 10.1055/s-0041-1731074
Case Report

Automated Infrared Pupillometer Use in Assessing the Neurological Status in Pediatric Neurocritical Care Patients: Case Reports and Literature Review

1   Division of Critical Care, Department of Pediatrics, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
,
Nathan Schneider
2   The University of Texas Southwestern ODL Brain Institute, Dallas, Texas, United States
3   Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
,
3   Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
4   Department of Neurosurgery, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
,
3   Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
4   Department of Neurosurgery, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
,
1   Division of Critical Care, Department of Pediatrics, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
› Author Affiliations

Abstract

Automated infrared pupillometry (AIP) is rapidly becoming an accepted standard for the evaluation of pupil size and reactivity in adult neurocritical care. Recently, pediatric centers are increasingly utilizing this technology, but data supporting its use in children are limited. Our pediatric intensive care unit instituted AIP as a standard of care for pupillary light assessments in neurocritical care patients in early 2020. In this article, we describe four cases highlighting the advantage of using objective assessments of the pupillary light reactivity response measured by the Neurological Pupil index (NPi) to detect early changes in the patient's neurological status. These cases support the applicability of AIP in pediatric neurocritical care as a noninvasive neurologic monitoring tool. The NPi may be superior to manual pupil assessments by providing a numerical scale for accurate trending clinical status of a patient's neurologic condition.



Publication History

Received: 22 January 2021

Accepted: 31 March 2021

Article published online:
22 June 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 
  • References

  • 1 Fink EL, Kochanek PM, Tasker RC. et al; Prevalence of acute critical neurological disease in children: a Global Epidemiological Assessment (PANGEA) Investigators. International survey of critically ill children with acute neurologic insults: the prevalence of acute critical neurological disease in children: a global epidemiological assessment study. Pediatr Crit Care Med 2017; 18 (04) 330-342
  • 2 Miller KD, Fidler-Benaoudia M, Keegan TH, Hipp HS, Jemal A, Siegel RL. Cancer statistics for adolescents and young adults, 2020. CA Cancer J Clin 2020; 70 (06) 443-459
  • 3 Cheng P, Li R, Schwebel DC, Zhu M, Hu G. Traumatic brain injury mortality among U.S. children and adolescents ages 0-19 years, 1999-2017. J Safety Res 2020; 72: 93-100
  • 4 Olson DM, Stutzman S, Saju C, Wilson M, Zhao W, Aiyagari V. Interrater reliability of pupillary assessments. Neurocrit Care 2016; 24 (02) 251-257
  • 5 Phillips SS, Mueller CM, Nogueira RG, Khalifa YM. A systematic review assessing the current state of automated pupillometry in the NeuroICU. Neurocrit Care 2019; 31 (01) 142-161
  • 6 Lee MH, Mitra B, Pui JK, Fitzgerald M. The use and uptake of pupillometers in the intensive care unit. Aust Crit Care 2018; 31 (04) 199-203
  • 7 Shah SS, Ranaivo HR, Mets-Halgrimson RB, Rychlik K, Kurup SP. Establishing a normative database for quantitative pupillometry in the pediatric population. BMC Ophthalmol 2020; 20 (01) 121
  • 8 Riker RR, Sawyer ME, Fischman VG. et al. Neurological pupil index and pupillary light reflex by pupillometry predict outcome early after cardiac arrest. Neurocrit Care 2020; 32 (01) 152-161
  • 9 Obling L, Hassager C, Illum C. et al. Prognostic value of automated pupillometry: an unselected cohort from a cardiac intensive care unit. Eur Heart J Acute Cardiovasc Care 2020; 9 (07) 779-787
  • 10 Oddo M, Sandroni C, Citerio G. et al. Quantitative versus standard pupillary light reflex for early prognostication in comatose cardiac arrest patients: an international prospective multicenter double-blinded study. Intensive Care Med 2018; 44 (12) 2102-2111
  • 11 Mader MM, Piffko A, Dengler NF. et al. Initial pupil status is a strong predictor for in-hospital mortality after aneurysmal subarachnoid hemorrhage. Sci Rep 2020; 10 (01) 4764
  • 12 Ortega-Perez S, Shoyombo I, Aiyagari V. et al. Pupillary light reflex variability as a predictor of clinical outcomes in subarachnoid hemorrhage. J Neurosci Nurs 2019; 51 (04) 171-175
  • 13 Weerakoon SM, Stutzman SE, Atem FD, Kuchenbecker KS, Olson DM, Aiyagari V. Investigation of pupillary changes after carotid endarterectomy and carotid stent placement using automated pupillometry. J Stroke Cerebrovasc Dis 2020; 29 (05) 104693
  • 14 Kim TJ, Park SH, Jeong HB. et al. Neurological pupil index as an indicator of neurological worsening in large hemispheric strokes. Neurocrit Care 2020; 33 (02) 575-581
  • 15 Papangelou A, Zink EK, Chang WW. et al. Automated pupillometry and detection of clinical transtentorial brain herniation: a case series. Mil Med 2018; 183 (1–2): e113-e121
  • 16 Al-Obaidi SZ, Atem FD, Stutzman SE, Olson DM. Impact of increased intracranial pressure on pupillometry: a replication study. Crit Care Explor 2019; 1 (10) e0054
  • 17 McNett M, Moran C, Grimm D, Gianakis A. Pupillometry trends in the setting of increased intracranial pressure. J Neurosci Nurs 2018; 50 (06) 357-361
  • 18 Stevens AR, Su Z, Toman E, Belli A, Davies D. Optical pupillometry in traumatic brain injury: neurological pupil index and its relationship with intracranial pressure through significant event analysis. Brain Inj 2019; 33 (08) 1032-1038
  • 19 Chen JW, Gombart ZJ, Rogers S, Gardiner SK, Cecil S, Bullock RM. Pupillary reactivity as an early indicator of increased intracranial pressure: The introduction of the Neurological Pupil index. Surg Neurol Int 2011; 2: 82
  • 20 Jahns FP, Miroz JP, Messerer M. et al. Quantitative pupillometry for the monitoring of intracranial hypertension in patients with severe traumatic brain injury. Crit Care 2019; 23 (01) 155
  • 21 Godau J, Bierwirth C, Rösche J, Bösel J. Quantitative infrared pupillometry in nonconvulsive status epilepticus. Neurocrit Care 2020; DOI: 10.1007/s12028-020-01149-1.
  • 22 Hasan S, Peluso L, Ferlini L. et al. Correlation between electroencephalography and automated pupillometry in critically ill patients: a pilot study. J Neurosurg Anesthesiol 2021; 33 (02) 161-166
  • 23 Freeman AD, McCracken CE, Stockwell JA. Automated pupillary measurements inversely correlate with increased intracranial pressure in pediatric patients with acute brain injury or encephalopathy. Pediatr Crit Care Med 2020; 21 (08) 753-759
  • 24 El Ahmadieh TY, Bedros N, Stutzman SE. et al. Automated pupillometry as a triage and assessment tool in patients with traumatic brain injury. World Neurosurg 2021; 145: e163-e169
  • 25 Holmberg MJ, Wiberg S, Ross CE. et al. Trends in survival after pediatric in-hospital cardiac arrest in the United States. Circulation 2019; 140 (17) 1398-1408