Data_Sheet_1_Non-Invasive Multimodal Neuromonitoring in Non-Critically Ill Hospitalized Adult Patients With COVID-19: A Systematic Review and Meta-Ana.docx (81.08 kB)
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Data_Sheet_1_Non-Invasive Multimodal Neuromonitoring in Non-Critically Ill Hospitalized Adult Patients With COVID-19: A Systematic Review and Meta-Analysis.docx

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posted on 14.04.2022, 05:20 by Denise Battaglini, Lavienraj Premraj, Samuel Huth, Jonathon Fanning, Glenn Whitman, Rakesh C. Arora, Judith Bellapart, Diego Bastos Porto, Fabio Silvio Taccone, Jacky Y. Suen, Gianluigi Li Bassi, John F. Fraser, Rafael Badenes, Sung-Min Cho, Chiara Robba, the COVID-19 Critical Care Consortium
Introduction

Neurological complications are frequent in patients with coronavirus disease-2019 (COVID-19). The use of non-invasive neuromonitoring in subjects without primary brain injury but with potential neurological derangement is gaining attention outside the intensive care unit (ICU). This systematic review and meta-analysis investigates the use of non-invasive multimodal neuromonitoring of the brain in non-critically ill patients with COVID-19 outside the ICU and quantifies the prevalence of abnormal neuromonitoring findings in this population.

Methods

A structured literature search was performed in MEDLINE/PubMed, Scopus, Cochrane, and EMBASE to investigate the use of non-invasive neuromonitoring tools, including transcranial doppler (TCD); optic nerve sheath diameter (ONSD); near-infrared spectroscopy (NIRS); pupillometry; and electroencephalography (EEG) inpatients with COVID-19 outside the ICU. The proportion of non-ICU patients with CVOID-19 and a particular neurological feature at neuromonitoring at the study time was defined as prevalence.

Results

A total of 6,593 records were identified through literature searching. Twenty-one studies were finally selected, comprising 368 non-ICU patients, of whom 97 were considered for the prevalence of meta-analysis. The pooled prevalence of electroencephalographic seizures, periodic and rhythmic patterns, slow background abnormalities, and abnormal background on EEG was.17 (95% CI 0.04–0.29), 0.42 (95% CI 0.01–0.82), 0.92 (95% CI 0.83–1.01), and.95 (95% CI 0.088–1.09), respectively. No studies investigating NIRS and ONSD outside the ICU were found. The pooled prevalence for abnormal neuromonitoring findings detected using the TCD and pupillometry were incomputable due to insufficient data.

Conclusions

Neuromonitoring tools are non-invasive, less expensive, safe, and bedside available tools with a great potential for both diagnosis and monitoring of patients with COVID-19 at risk of brain derangements. However, extensive literature searching reveals that they are rarely used outside critical care settings.

Systematic Review Registration:www.crd.york.ac.uk/prospero/display_record.php?RecordID=265617, identifier: CRD42021265617.

History

References