Evidence map›Paper›PMID 36147043›Full record

ArticleFrontiers in neurology2022

EEG background frequency is associated with discharge outcomes in non-ICU hospitalized patients with COVID-19.

Kaitlin M Seibert, Wonhee Lee, Alexandra Eid, Amy E Espinal, Sara A Klein, Sumayyah K Abumurad, James X Tao, Naoum P Issa

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Kaitlin M SeibertDepartment of Neurology, University of Chicago, Chicago, IL, United States.
Wonhee LeeDepartment of Neurology, University of Chicago, Chicago, IL, United States.
Alexandra EidDepartment of Neurology, University of Chicago, Chicago, IL, United States.
Amy E EspinalDepartment of Neurology, University of Chicago, Chicago, IL, United States.
Sara A KleinDepartment of Neurology, University of Chicago, Chicago, IL, United States.
Sumayyah K AbumuradDepartment of Neurology, University of Chicago, Chicago, IL, United States.
James X TaoDepartment of Neurology, University of Chicago, Chicago, IL, United States.
Naoum P IssaDepartment of Neurology, University of Chicago, Chicago, IL, United States.
University of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess risk factors for encephalopathy in non-ICU hospitalized patients with COVID-19 and the effect of encephalopathy on short-term outcomes. Methods: We collected clinical and electrophysiological characteristics of fifty patients with COVID-19 infection admitted to a ward service and who had an electroencephalogram (EEG) performed. Associations with short-term outcomes including hospital length of stay and discharge disposition were determined from univariate and multivariate statistical analysis. Results: Clinical delirium was associated with encephalopathy on EEG, cefepime use was associated with increased length of stay, and of all factors analyzed, background frequency on EEG alone was correlated with discharge disposition. Conclusion: Encephalopathy is one of the major determinants of short-term outcomes in hospitalized non-ICU patients with COVID-19.

Indexed as

background frequencyCOVID-19discharge outcomeencephalopathySARS-CoV-2

Identifiers

PMID36147043
PMCPMC9487016
OpenAlexW4293531228

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.