Evidence map›Paper›PMID 33313272›Full record

ArticleAnnals of translational medicine2020

Current therapeutic options for coronavirus disease 2019 (COVID-19)-lessons learned from severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) therapy: a systematic review protocol.

Zai-Li Zhang, Han Zhong, Yang-Xi Liu, Ke-Jia Le, Min Cui, Yue-Tian Yu, Zhi-Chun Gu, Yuan Gao, Hou-Wen Lin

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational 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
0.1field-weighted citation impact, top 44% 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, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

9 authors at 2 institutions in 1 country.

Zai-Li ZhangDepartment of Pharmacy, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Han ZhongDepartment of Pharmacy, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yang-Xi LiuDepartment of Pharmacy, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Ke-Jia LeDepartment of Pharmacy, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Min CuiDepartment of Pharmacy, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yue-Tian YuDepartment of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Zhi-Chun GuDepartment of Pharmacy, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yuan GaoDepartment of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Hou-Wen LinDepartment of Pharmacy, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Renji Hospital · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19), also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, first manifested in December 2019, and spread rapidly worldwide. Facing this lethal disease, there is an urgent need to develop potent therapies against SARS-CoV-2 infection. SARS-CoV-2 phylogenetically and symptomatically resembles SARS-CoV and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). Numerous agents have been utilised during the severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) epidemics, which may show some benefit against SARS-CoV-2.

methodsMEDLINE, EMBASE, Cochrane Library, CBM Disc, China National Knowledge Infrastructure, Wanfang Data, and the China Science and Technology Journal Database will be searched. Manual searches will be conducted by searching pre-printing websites, clinical trial registers, and screening the reference lists of inclusive studies. The screening of all citations and the selection of inclusive articles will be conducted by two reviewers. Randomised controlled trials (RCTs) and controlled cohort studies reporting antiviral therapies, including ribavirin, remdesivir, lopinavir/ritonavir, arbidol, chloroquine, hydroxychloroquine, and interferon, for SARS, MERS, and COVID-19 will be included. The primary outcomes will be mortality, incidence of acute respiratory distress syndrome, and utilisation of mechanical ventilation and intensive care unit admission. The secondary outcomes will be improvement in symptoms and chest radiography results, virus clearance, changes in blood test results, and serum tests. The quality of the retrieved RCTs and observational studies will be appraised according to the Cochrane risk of bias tool and the Newcastle-Ottawa Scale, respectively. If feasible, we will perform a fixed- or random-effects meta-analysis. DISCUSSION: This systematic review and meta-analysis will summarise all the available evidence for the efficacy and safety of current therapeutic options in SARS-CoV, MERS-CoV, or SARS-CoV-2-infected patients. The findings of this study may inform subsequent antiviral interventions for patients with COVID-19. STUDY REGISTRATION: The protocol of this study has been submitted to the PROSPERO platform (https://www.crd.york.ac.uk/PROSPERO/), and the registration number is CRD42020168639.

Indexed as

Coronavirus disease 2019 (COVID-19)efficacyMiddle East Respiratory Syndrome Coronavirus (MERS)safetysevere acute respiratory syndrome (SARS)therapeutic options

Identifiers

PMID33313272
PMCPMC7729372
OpenAlexW3103604964

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.