Evidence map›Paper›PMID 38934169›Full record

ArticleNeuroepidemiology2025

The National Institutes of Health COVID-19 Neuro Databank/Biobank: Creation and Evolution.

Sharon B Meropol, Cecile J Norris, Jennifer A Frontera, Adenike Adeagbo, Andrea B Troxel, COVID-19 Neuro Databank/Biobank Consortium

Abstract read
In one paragraph

Article in Neuroepidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Sharon B MeropolDivision of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA.
Cecile J NorrisDivision of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA, cecile.norris@nyulangone.org.
Jennifer A FronteraDepartment of Neurology, NYU Grossman School of Medicine, New York, New York, USA.
Adenike AdeagboDivision of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA.
Andrea B TroxelDivision of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA.
COVID-19 Neuro Databank/Biobank Consortium

Funding

Statistical Methods to Jointly Model Multiple Pain Outcome MeasuresU24NS113844 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI TROXEL, ANDREA B, YU, CHANG · 2019 to 2024
$25.9M
NINDS NIH HHS U24 NS113844
6 · The paper itself

Abstract

introductionDiverse neurological conditions are reported associated with the SARS-CoV-2 virus; neurological symptoms are the most common conditions to persist after the resolution of acute infection, affecting 20% of patients 6 months after acute illness. The COVID-19 Neuro Databank (NeuroCOVID) was created to overcome the limitations of siloed small local cohorts to collect detailed, curated, and harmonized de-identified data from a large diverse cohort of adults with new or worsened neurological conditions associated with COVID-19 illness, as a scientific resource.

methodsA Steering Committee including US and international experts meets quarterly to provide guidance. Initial study sites were recruited to include a wide US geographic distribution; academic and non-academic sites; urban and non-urban locations; and patients of different ages, disease severity, and comorbidities seen by a variety of clinical specialists. The NeuroCOVID REDCap database was developed, incorporating input from professional guidelines, existing common data elements, and subject matter experts. A cohort of eligible adults is identified at each site; inclusion criteria are: a new or worsened neurological condition associated with a COVID-19 infection confirmed by testing. De-identified data are abstracted from patients' medical records, using standardized common data elements and five case report forms. The database was carefully enhanced in response to feedback from site investigators and evolving scientific interest in post-acute conditions and their timing. Additional US and international sites were added, focusing on diversity and populations not already described in published literature. By early 2024, NeuroCOVID included over 2,700 patient records, including data from 16 US and 5 international sites. Data are being shared with the scientific community in compliance with NIH requirements. The program has been invited to share case report forms with the National Library of Medicine as an ongoing resource for the scientific community.

conclusionThe NeuroCOVID database is a unique and valuable source of comprehensive de-identified data on a wide variety of neurological conditions associated with COVID-19 illness, including a diverse patient population. Initiated early in the pandemic, data collection has been responsive to evolving scientific interests. NeuroCOVID will continue to contribute to scientific efforts to characterize and treat this challenging illness and its consequences.

Indexed as

COVID-19Databases, FactualNervous System DiseasesAdultHumansNational Institutes of Health (U.S.)SARS-CoV-2United StatesAdult COVID-19 databaseEpidemiological methodsNeurological diseasesNeurological disordersObservational studies

Identifiers

PMID38934169
PMCPMC11669729

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.