Evidence map›Paper›PMID 34858037›Full record

ReviewInfection and drug resistance2021

SARS-CoV-2-Associated Cerebrovascular Disease Amid the COVID-19 Pandemic: A Systematic Review.

Tao Yu, Hongquan Wang, Shuhan Zheng, Liang Huo

Open access · goldAbstract readReview
In one paragraph

Review in Infection and drug resistance, 2021. 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
0.2field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Extracellular Vesicles: The Invisible Heroes and Villains of COVID-19 Central Neuropathology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  2. Stroke and COVID-19: An Umbrella Review.Archives of academic emergency medicine · 2024
    Review
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 2 institutions in 1 country.

Tao Yu *Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, People's Republic of China.
Hongquan Wang *Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, People's Republic of China.
Shuhan ZhengDepartment of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, People's Republic of China.
Liang HuoDepartment of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, People's Republic of China.
China Medical University · CNTianjin Medical University Cancer Institute and Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCerebrovascular diseases associated with SARS-CoV-2 are being increasingly reported in the literature as the coronavirus disease 2019 (COVID-19) pandemic continues. However, a case-based retrospective analysis of the literature about SARS-CoV-2-cerebrovascular disease (SCVD) is not yet well established. Thus, we reviewed the literature on SCVD covering a comprehensive range of topics spanning the clinical features, mechanism, treatment, and outcomes of patients with SCVD.

methodsWe searched PubMed

resultsWe included all 51 articles indexed in PubMed

conclusionThis summary of patient characteristics may help clinicians better anticipate SCVD outcomes and complications in their COVID-19 patients.

Indexed as

cerebral hemorrhagecerebral venous thrombosiscerebrovascular diseaseCOVID-19stroke

Identifiers

PMID34858037
PMCPMC8631829
OpenAlexW3215755669

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.