Validation of a Novel NeurOs Cerebral Oximetry Monitor Against the INVOS Monitor During Cardiac Surgery.

INVOS NeurOs cardiac surgery cerebral oximetry cerebral oxygenation comparison near-infrared spectroscopy

Journal

Journal of cardiothoracic and vascular anesthesia
ISSN: 1532-8422
Titre abrégé: J Cardiothorac Vasc Anesth
Pays: United States
ID NLM: 9110208

Informations de publication

Date de publication:
Jul 2021
Historique:
received: 22 07 2020
revised: 23 10 2020
accepted: 24 10 2020
pubmed: 22 11 2020
medline: 2 7 2021
entrez: 21 11 2020
Statut: ppublish

Résumé

To compare the performance of a novel NeurOs cerebral oximetry monitor against the INVOS monitor during the entire intraoperative phase of cardiac surgery, including periods of known fluctuation in brain oxygenation, such as preoxygenation, induction, cannulation, and cardiopulmonary bypass. This study was a prospective, nonrandomized, healthcare-provider and outcome-assessor blinded study. Tertiary care university hospital; single institutional study. Twenty-three patients who underwent cardiac surgery with cardiopulmonary bypass. Both self-adhesive INVOS sensors and the assembled NeurOs sensors were placed accordingly when the patient arrived in the operating room. Ten out of 13 cases under the normal mode and eight out of the 10 cases under the high- sensitivity mode showed significant correlations between the NeurOs and INVOS groups (p < 0.05, r value from 0.24-0.88). When all cases were combined, NeurOs demonstrated significant correlation with INVOS (r = 0.5, 95% confidence interval [CI] 0.44-0.56, p < 0.01 for normal mode; r = 0.69, 95% CI 0.64 to 0.74, p < 0.01 for high-sensitivity mode) in both modes. To evaluate the data diversity, the authors performed a cluster analysis and found much less variation existed in the NeurOs normal mode when compared with INVOS (standard deviation [SD] 16.6% in INVOS, 4% in NeurOs normal mode) but similar patterns in the high-sensitivity mode (SD 17.6% in INVOS, 15.2% in NeurOs high-sensitivity mode). Bland-Altman plot analysis showed that most of the data fell between ± 1.96 SD lines, which demonstrated good consistency between these two methods under both modes of NeurOs (-28.8 to 30.8 in the normal mode; -36.6 to 32.7 in high-sensitivity mode). In the normal mode of NeurOs monitoring, receiver operating characteristic analysis suggested a 2% cutoff point was most optimal from the baseline for detecting hyperoxia (sensitivity 73%; specificity 66%) and minus 1% (sensitivity 66%; specificity 67%) for detecting hypoxia. Whereas in the high-sensitivity mode, the optimal cutoff point was 3% from baseline for detecting hyperoxia (sensitivity 75%; specificity 68%), and minus 3% for detecting hypoxia (sensitivity 90%; specificity 45%). In conclusion, the novel NeurOs system was found to correlate with INVOS cerebral oximetry measurements during cardiac surgery.

Identifiants

pubmed: 33218956
pii: S1053-0770(20)31157-5
doi: 10.1053/j.jvca.2020.10.043
pii:
doi:

Substances chimiques

Oxygen S88TT14065

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2009-2018

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Kaicheng Song (K)

Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY; Department of Anesthesiology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, PR China.

Qian Xu (Q)

Department of Bioinformatics and Biostatistics, SPHIS, University of Louisville, Louisville, KY.

Heidi M Koenig (HM)

Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY.

Maiying Kong (M)

Department of Bioinformatics and Biostatistics, SPHIS, University of Louisville, Louisville, KY.

Mark S Slaughter (MS)

Department of Cardiovascular & Thoracic Surgery, University of Louisville, Louisville, KY.

Yuguang Huang (Y)

Department of Anesthesiology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, PR China.

Sean P Clifford (SP)

Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY.

Jiapeng Huang (J)

Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY; Department of Cardiovascular & Thoracic Surgery, University of Louisville, Louisville, KY. Electronic address: jiapeng.huang@louisville.edu.

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Classifications MeSH