Evidence map›Paper›PMID 37987459›Full record

ArticleNeurology international2023

Analysis of Post-COVID-19 Guillain-Barré Syndrome over a Period of One Year in the University Hospital of Split (Croatia).

Niko Dunkić, Marija Nazlić, Valerija Dunkić, Ivica Bilić

Open access · goldAbstract read
In one paragraph

Article in Neurology international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Niko DunkićPractice of General Medicine, A.G. Matoša 2, 21000 Split, Croatia.
Marija NazlićFaculty of Science, University of Split, Ruđera Boškovića 33, 21000 Split, Croatia.ORCID 0000-0002-4976-5392
Valerija DunkićFaculty of Science, University of Split, Ruđera Boškovića 33, 21000 Split, Croatia.ORCID 0000-0001-9372-7337
Ivica BilićSchool of Medicine, University of Split, Šoltanska 2, 21000 Split, Croatia.
University of Split · HR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The virus SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is capable of attacking the nervous system in several ways and leading to neurological diseases such as GBS (Guillain-Barré syndrome) through the resulting neurotropism and immune response. The aim of this study is to show the relationship between Coronavirus disease (COVID-19) and GBS and to better understand the clinical symptoms to prevent poor outcomes. Data from 15 patients were extracted from the Department of Neurology, University Hospital of Split, Croatia, for the year 2021. The age of the patients ranged from 26 to 89 years, of whom 27% were women. Sixty seven percent of all GBS patients recovered from COVID-19 infection, whereas post-vaccinal polyradiculoneuritis was detected in 6%. Forty four percent of the patients who developed GBS had a severe form of COVID-19 infection. Forty percent of patients were treated with intravenous immunoglobulins (IVIG), followed by therapeutic plasma exchange (PLEX) in 27%. After the therapy, improvement was observed in 13 patients, while two patients died. The results suggest that SARS-CoV-2 triggers GBS because it follows a similar pattern of infection as the other viral and bacterial agents that contribute to the onset of GBS. There is no evidence that prior infection with COVID-19 worsens the clinical presentation of GBS.

Indexed as

Guillain–Barré syndromeimmune responseneurotropismSARS-CoV-2

Identifiers

PMID37987459
PMCPMC10661271
OpenAlexW4388415387

What OpenQuestion holds

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LicenceCC BY
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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.