Evidence map›Paper›PMID 36597538›Full record

ArticleResearch square2023

Neurophenotypes of COVID-19: risk factors and recovery outcomes.

Divya Prabhakaran, Gregory S Day, Bala Munipalli, Beth K Rush, Lauren Pudalov, Shehzad K Niazi, Emily Brennan, Harry R Powers, Ravi Durvasula, Arjun Athreya and 1 more

Abstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Divya Prabhakaran
Gregory S DayMayo Clinic.ORCID 0000-0001-5133-5538
Bala MunipalliMayo Clinic.
Beth K RushMayo Clinic.
Lauren PudalovMayo Clinic.
Shehzad K NiaziMayo Clinic.
Emily BrennanMayo Clinic.
Harry R PowersMayo Clinic.
Ravi DurvasulaMayo Clinic.
Arjun Athreya
Karen BlackmonMayo Clinic.ORCID 0000-0002-2665-7807

Funding

Early Onset AD Consortium - the LEAD Study (LEADS)U01AG057195 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI APOSTOLOVA, LIANA G, CARRILLO, MARIA C · 2018 to 2023
$70.3M
Imaging CoreU19AG032438 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2010 to 2025
$53.9M
Rapidly Progressive Dementia: Moving Beyond CJDK23AG064029 · NIA · WASHINGTON UNIVERSITY · PI DAY, GREGORY SCOTT · 2019 to 2023
$811k
NIA NIH HHS K23 AG064029NIA NIH HHS U01 AG057195NIA NIH HHS U19 AG032438
6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) infection is associated with risk of persistent neurocognitive and neuropsychiatric complications, termed "long COVID". It is unclear whether the neuropsychological manifestations of COVID-19 present as a uniform syndrome or as distinct neurophenotypes with differing risk factors and recovery outcomes. We examined post-acute neuropsychological profiles following SARS-CoV-2 infection in 205 patients recruited from inpatient and outpatient populations, using an unsupervised machine learning cluster analysis, with objective and subjective measures as input features. This resulted in three distinct post-COVID clusters. In the largest cluster (69%), cognitive functions were within normal limits, although mild subjective attention and memory complaints were reported. Vaccination was associated with membership in this "normal cognition" phenotype. Cognitive impairment was present in the remaining 31% of the sample but clustered into two differentially impaired groups. In 16% of participants, memory deficits, slowed processing speed, and fatigue were predominant. Risk factors for membership in the "memory-speed impaired" neurophenotype included anosmia and more severe COVID-19 infection. In the remaining 15% of participants, executive dysfunction was predominant. Risk factors for membership in this milder "dysexecutive" neurophenotype included disease-nonspecific factors such as neighborhood deprivation and obesity. Recovery outcomes at 6-month follow-up differed across neurophenotypes, with the normal cognition group showing improvement in verbal memory and psychomotor speed, the dysexecutive group showing improvement in cognitive flexibility, and the memory-speed impaired group showing no objective improvement and relatively worse functional outcomes compared to the other two clusters. These results indicate that there are multiple post-acute neurophenotypes of long COVID, with different etiological pathways and recovery outcomes. This information may inform phenotype-specific approaches to treatment.

Identifiers

PMID36597538
PMCPMC9810229

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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.