Literature DB >> 19938127

Clinical utility of an automated pupillometer for assessing and monitoring recipients of liver transplantation.

Sheng Yan1, Zhenhua Tu, Weifeng Lu, Qiyi Zhang, Jiangjuan He, Zhiwei Li, Yi Shao, Weilin Wang, Min Zhang, Shusen Zheng.   

Abstract

Pupil examination has been used as a basic measure in critically ill patients and has great importance for the prognosis and management of disease. An automated pupillometer is a computer-based infrared digital video system by which the accuracy and precision of the pupil examination are markedly improved. We conducted an observational study of pupil assessment with automated pupillometry in clinical liver transplantation settings, including pretransplant evaluations and posttransplant surveillance. Our results showed that unconscious patients (grade 4 hepatic encephalopathy) had a prolonged latency phase (left side: 283 +/- 80 milliseconds; right side: 295 +/- 96 milliseconds) and a reduced pupillary constrictive ratio (left direct response: 0.23 +/- 0.10; left indirect response: 0.21 +/- 0.07; right direct response: 0.20 +/- 0.08; right indirect response: 0.21 +/- 0.08) in comparison with normal and conscious patients. After liver transplantation, the recovery of pupillography in these patients was slower than that in conscious patients. However, the surviving recipients without major complications all had a gradual recovery of pupillary responses, which occurred on the first or second posttransplant day. We also reported 4 cases of futile LT in the absence of pretransplant pupillary responses and other pupillary abnormalities revealed by automated pupillometry in our study. In conclusion, patients with grade 4 hepatic encephalopathy had a sluggish pupil response and a delayed recovery pattern after LT. An automated pupillometer is potentially a supplementary device for pretransplant screening and posttransplant monitoring in patients undergoing LT, but further prospective studies are required.

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Year:  2009        PMID: 19938127     DOI: 10.1002/lt.21924

Source DB:  PubMed          Journal:  Liver Transpl        ISSN: 1527-6465            Impact factor:   5.799


  6 in total

1.  Automated quantitative pupillometry for the prognostication of coma after cardiac arrest.

Authors:  Tamarah Suys; Pierre Bouzat; Pedro Marques-Vidal; Nathalie Sala; Jean-François Payen; Andrea O Rossetti; Mauro Oddo
Journal:  Neurocrit Care       Date:  2014-10       Impact factor: 3.210

2.  The effects of anesthetic agents on pupillary function during general anesthesia using the automated infrared quantitative pupillometer.

Authors:  Kazuhiro Shirozu; Hidekazu Setoguchi; Kentaro Tokuda; Yuji Karashima; Mizuko Ikeda; Makoto Kubo; Katsuya Nakamura; Sumio Hoka
Journal:  J Clin Monit Comput       Date:  2016-02-08       Impact factor: 2.502

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.  Reliability of standard pupillometry practice in neurocritical care: an observational, double-blinded study.

Authors:  David Couret; Delphine Boumaza; Coline Grisotto; Thibaut Triglia; Lionel Pellegrini; Philippe Ocquidant; Nicolas J Bruder; Lionel J Velly
Journal:  Crit Care       Date:  2016-03-13       Impact factor: 9.097

5.  Clinical Utility of an Automated Pupillometer in Patients with Acute Brain Lesion.

Authors:  Jeong Goo Park; Chang Taek Moon; Dong Sun Park; Sang Woo Song
Journal:  J Korean Neurosurg Soc       Date:  2015-10-30

6.  The Clinical Course of Cirrhosis Patients Hospitalized for Acute Hepatic Deterioration: A Prospective Bicentric Study.

Authors:  Yu Shi; Huadong Yan; Zhibo Zhou; Hong Fang; Jiawei Li; Honghua Ye; Wenjie Sun; Wenhong Zhou; Jingfen Ye; Qiao Yang; Ying Yang; Yaoren Hu; Zhi Chen; Jifang Sheng
Journal:  Medicine (Baltimore)       Date:  2015-11       Impact factor: 1.817

  6 in total

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