Literature DB >> 31033624

Comparison of 2 Automated Pupillometry Devices in Critically III Patients.

Chiara Robba1,2, Bedrana Moro Salihovic3, Selene Pozzebon3, Jacques Creteur3, Mauro Oddo4, Jean-Louis Vincent3, Fabio S Taccone3.   

Abstract

BACKGROUND: Automated pupillometry may help detect early cerebral disturbances in critically ill patients. It remains unclear whether different automated pupillometry devices can detect pupillary abnormalities with similar accuracy. The aim of this study was to compare the performance of 2 commercially available automated pupillometry devices-Neurolight Algiscan (NL) and NPi-200 (NP) versus standard pupillary light reflex (PLR) examination in an unselected cohort of critically ill patients.
MATERIALS AND METHODS: This prospective study included all adult (>18 y) patients admitted to the intensive care unit of a university hospital over a 20-day period. Measurements were made consecutively with each method once during the intensive care unit stay in each patient. To assess sensitivity and specificity, we calculated areas under the curve of the receiver operating characteristic curve.
RESULTS: A total of 112 patients were included in the study. There was a significant correlation between the 2 automated pupillometry devices for pupil size, constriction to light stimulation, and constriction velocity but not for pupillary latency. The mean bias for pupil size measured by the NL and the NP devices was -0.12 (limit of agreement [LoA], -1.29 to 1.06) mm, for pupil constriction -1.0% (LoA, -9.3% to 7.2%), and for latency 0.02 (LoA, -0.22 to 0.25) ms. There was a significant correlation between pupil size evaluated by clinical examination and that using the NL or NP. The areas under the curves for pupil constriction measured by NL and NP were 0.93 and 0.91, respectively, to detect clinically reactive pupils.
CONCLUSIONS: Although there was a significant correlation between NL and NP values as well as with clinical examination of the PLR, the 2 devices were not always interchangeable, especially for the evaluation of pupillary latency.

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Mesh:

Year:  2020        PMID: 31033624     DOI: 10.1097/ANA.0000000000000604

Source DB:  PubMed          Journal:  J Neurosurg Anesthesiol        ISSN: 0898-4921            Impact factor:   3.956


  4 in total

Review 1.  Automated Pupillometry in Neurocritical Care: Research and Practice.

Authors:  Bethany L Lussier; DaiWai M Olson; Venkatesh Aiyagari
Journal:  Curr Neurol Neurosci Rep       Date:  2019-08-23       Impact factor: 5.081

2.  Neurological Complications and Noninvasive Multimodal Neuromonitoring in Critically Ill Mechanically Ventilated COVID-19 Patients.

Authors:  Denise Battaglini; Gregorio Santori; Karthikka Chandraptham; Francesca Iannuzzi; Matilde Bastianello; Fabio Tarantino; Lorenzo Ball; Daniele Roberto Giacobbe; Antonio Vena; Matteo Bassetti; Matilde Inglese; Antonio Uccelli; Patricia Rieken Macedo Rocco; Nicolò Patroniti; Iole Brunetti; Paolo Pelosi; Chiara Robba
Journal:  Front Neurol       Date:  2020-11-27       Impact factor: 4.003

3.  Superior reproducibility and repeatability in automated quantitative pupillometry compared to standard manual assessment, and quantitative pupillary response parameters present high reliability in critically ill cardiac patients.

Authors:  Benjamin Nyholm; Laust Obling; Christian Hassager; Johannes Grand; Jacob Møller; Marwan Othman; Daniel Kondziella; Jesper Kjaergaard
Journal:  PLoS One       Date:  2022-07-28       Impact factor: 3.752

4.  Identification of abnormal pupil dilation velocity as a biomarker of cerebral injury in neurocritically ill patients.

Authors:  Prachi Singh; Sonia E Stutzman; Aardhra Venkatachalam; DaiWai M Olson; Arianna Barnes; Folefac D Atem
Journal:  Rev Bras Ter Intensiva       Date:  2021 Jul-Sep
  4 in total

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