Evidence map›Paper›PMID 38627327›Full record

ArticleImmunologic research2024

Cluster analysis of long COVID symptoms for deciphering a syndrome and its long-term consequence.

J Niewolik, M Mikuteit, S Klawitter, D Schröder, A Stölting, K Vahldiek, S Heinemann, F Müller, Gmn Behrens, F Klawonn and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Immunologic research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

12 citing papers in PubMed, 15 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

J Niewolik *Department of Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany. niewolik.jacqueline@mh-hannover.de.ORCID 0000-0001-7367-9286
M Mikuteit *Department of Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
S Klawitter *Institute for Information Engineering, Ostfalia University of Applied Sciences, Wolfenbüttel, Germany.
D SchröderDepartment of General Practice, University Medical Center Göttingen, Göttingen, Germany.
A StöltingDepartment of Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
K VahldiekInstitute for Information Engineering, Ostfalia University of Applied Sciences, Wolfenbüttel, Germany.
S HeinemannDepartment of General Practice, University Medical Center Göttingen, Göttingen, Germany.
F MüllerDepartment of General Practice, University Medical Center Göttingen, Göttingen, Germany.
Gmn BehrensDepartment of Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
F Klawonn *Institute for Information Engineering, Ostfalia University of Applied Sciences, Wolfenbüttel, Germany.
A Dopfer-Jablonka *Department of Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
S Steffens *Department of Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
Medizinische Hochschule Hannover · DEOstfalia University of Applied Sciences · DEUniversitätsmedizin Göttingen · DE

Funding

European Regional Development Fund ZW7-85152953
6 · The paper itself

Abstract

The long-term symptoms of COVID-19 are the subject of public and scientific discussions. Understanding how those long COVID symptoms co-occur in clusters of syndromes may indicate the pathogenic mechanisms of long COVID. Our study objective was to cluster the different long COVID symptoms. We included persons who had a COVID-19 and assessed long-term symptoms (at least 4 weeks after first symptoms). Hierarchical clustering was applied to the symptoms as well as to the participants based on the Euclidean distance h of the log-values of the answers on symptom severity. The distribution of clusters within our cohort is shown in a heat map.From September 2021 to November 2023, 2371 persons with persisting long COVID symptoms participated in the study. Self-assessed long COVID symptoms were assigned to three symptom clusters. Cluster A unites rheumatological and neurological symptoms, cluster B includes neuro-psychological symptoms together with cardiorespiratory symptoms, and a third cluster C shows an association of general infection signs, dermatological and otology symptoms. A high proportion of the participants (n = 1424) showed symptoms of all three clusters. Clustering of long COVID symptoms reveals similarities to the symptomatology of already described syndromes such as the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) or rheumatological autoinflammatory diseases. Further research may identify serological parameters or clinical risk factors associated with the shown clusters and might improve our understanding of long COVID as a systemic disease. Furthermore, multimodal treatments can be developed and scaled for symptom clusters and associated impairments.

Indexed as

COVID-19Post-Acute COVID-19 SyndromeSARS-CoV-2AdultAgedCluster AnalysisFemaleHumansMaleMiddle AgedSeverity of Illness IndexCluster analysisCOVID-19Long COVID symptoms

Identifiers

PMID38627327
PMCPMC11347473
OpenAlexW4394840815

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.