Evidence map›Paper›PMID 34743661›Full record

SynthesisExpert review of anti-infective therapy2022

Janus kinase inhibitors for hospitalized patients with COVID-19: a meta-analysis of randomized controlled trials.

Shao-Huan Lan, Chiung-Kai Wang, Shen-Peng Chang, Li-Chin Lu, Shun-Hsing Hung, Wei-Ting Lin

Open access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Expert review of anti-infective therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 31% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Observational
  6. 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 at 3 institutions in 2 countries.

Shao-Huan LanSchool of Pharmaceutical Sciences and Medical Technology, Putian University, Putian, China.
Chiung-Kai WangDepartment of Internal Medicine, Kaohsiung Veterans General Hospital, Tainan, Taiwan.
Shen-Peng ChangYijia Pharmacy, Tainan, Taiwan.
Li-Chin LuSchool of Management, Putian University, Putian, China.
Shun-Hsing HungDivisionof Urology, Department of Surgery, Chi-Mei Hospital, Chia Li, Tainan, Taiwan.
Wei-Ting LinDepartment of Orthopedic, Chi Mei Medical Center, Tainan, Taiwan.
Chi Mei Medical Center · TWPutian University · CNKaohsiung Veterans General Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis meta-analysis of randomized controlled trials (RCTs) investigated the usefulness of Janus kinase (JAK) inhibitors among hospitalized patients with COVID-19.

methodsPubMed, Web of Science, the Cochrane Library, and Ovid MEDLINE were searched for RCTs published before 7 September 2021. Only RCTs that compared the clinical efficacy and safety of JAK inhibitors with other alternative treatments or placebos in the treatment of hospitalized patients with COVID-19 were included.

resultsOverall, patients receiving JAK inhibitors exhibited a lower 28-day mortality rate than the control group (risk ratio [RR], 0.60; 95% CI, 0.47-0.77;

conclusionsJAK inhibitors can help reduce mortality and improve clinical outcomes among hospitalized patients with COVID-19. Additionally, JAK inhibitors can be used safely in this clinical entity.

Indexed as

COVID-19 Drug TreatmentJanus Kinase InhibitorsHumansRandomized Controlled Trials as TopicRespiration, ArtificialSARS-CoV-2Janus Kinase InhibitorsCOVID-19Janus kinase inhibitormortalitySARS-CoV-2

Identifiers

PMID34743661
PMCPMC8607541
OpenAlexW3212071702

What Socratic 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 Socratic graph.