Evidence map›Paper›PMID 32838187›Full record

ReviewSN comprehensive clinical medicine2020

Protease Inhibitor Use in COVID-19.

Yueqi Song, Wujian Peng, Donge Tang, Yong Dai

Open access · bronzeAbstract readReview
In one paragraph

Review in SN comprehensive clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

4 authors at 2 institutions in 1 country.

Yueqi SongClinical Medical Research Center, The Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), 1017 North Road, Dongmen, Shenzhen, 518020 Guangdong People's Republic of China.
Wujian PengDepartment of Nephrology, National Clinical Research Center for Infectious Diseases, The Second Affiliated Hospital of Southern University of Science and Technology (Shenzhen Third People's Hospital), Shenzhen, 518114 Guangdong People's Republic of China.
Donge TangClinical Medical Research Center, The Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), 1017 North Road, Dongmen, Shenzhen, 518020 Guangdong People's Republic of China.
Yong DaiClinical Medical Research Center, The Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), 1017 North Road, Dongmen, Shenzhen, 518020 Guangdong People's Republic of China.ORCID 0000-0002-6840-9158
Jinan University · CNSouthern University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak of a large plaque, novel coronavirus pneumonia (NCP), which also named Coronavirus Disease 2019 (COVID-19) by the WHO, has detrimentally affected the livelihood and health of people in China. During the spread of COVID-19, colleagues who have been working at the frontline have had to face many new challenges in the treatment and prevention of NCP. Therefore, we have provided suggestions for the diagnosis, treatment, and prevention of the novel coronavirus pneumonia in the current epidemic situation based on the latest reports and the experience of doctors treating COVID-19 in our hospital. We recommend lopinavir/ritonavir as the effective drugs for antiviral treatment according to our experience in administering lopinavir/ritonavir to COVID-19 patients and the successful cases of these drugs in treating MERS and SARS, but need more clinical data to prove their efficacy in treating COVID-19.

Indexed as

DiagnosisLopinavir/ritonavirNovel coronavirus pneumoniaTreatment

Identifiers

PMID32838187
PMCPMC7426163
OpenAlexW3048857167

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.