Evidence map›Paper›PMID 33235612›Full record

ReviewExperimental and therapeutic medicine2021

Treatment and prognosis of COVID-19: Current scenario and prospects (Review).

Xuemei Li, Tao Li, Huihui Wang

Open access · diamondAbstract readReview
In one paragraph

Review in Experimental and therapeutic medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Research progress of traditional Chinese medicine against COVID-19.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2021
    Review
  8. Article
  9. 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

3 authors at 1 institution in 1 country.

Xuemei LiDepartment of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230032, P.R. China.
Tao LiDepartment of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230032, P.R. China.
Huihui WangDepartment of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230032, P.R. China.
Anhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2 is the seventh member of the family of coronaviruses that can cause infections in humans, termed as COVID-19, which is now a global pandemic. Because it is a novel virus, considerable efforts and extensive studies are needed to fully understand its characteristics. Its symptoms and severity range from mild to critical, depending on several factors, such as host susceptibility to the virus and their immune system, with the most common symptoms being fever, fatigue, sore throat and runny nose. There is no clear treatment available yet, though several options are being explored, with research for vaccines being at the forefront. Traditional Chinese Medicine may also be used as a treatment option. Since this virus is similar to the SARS-CoV and MERS viruses, considerable insight can be gained from previous studies. Although many patients recover completely, there are several factors that lead to poor prognosis. This review summarizes the research carried out so far in terms of treatment options and prognosis factors associated with COVID-19.

Indexed as

coronavirusCOVID-19featuresprognosisSARS-CoV-2treatment

Identifiers

PMID33235612
PMCPMC7678645
OpenAlexW3096521880

What OpenQuestion holds

Textmetadata
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.