Evidence map›Paper›PMID 36341271›Full record

ArticleFrontiers in medicine2022

The early stage of COVID-19 pandemic: Gastrointestinal manifestations and liver injury in COVID-19 patients in Wuhan, China.

Dafan Chen, Min Ning, Yun Feng, Jun Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
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  4. 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.

Dafan ChenDepartment of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Min NingDigestive Endoscopic Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yun FengDepartment of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jun LiuDepartment of Nephrology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai Jiao Tong University · CNShanghai Sixth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are few and inconsistent data focusing on gastrointestinal (GI) manifestations and liver injury in China's early stage of COVID-19 pandemic. In this study, we research the prevalence and role of GI symptoms and liver injury in COVID-19 patients in Wuhan during the disease's first outbreak. We conducted a cross-sectional observational study in a non-ICU unit in Wuhan, China. COVID-19 patients were consecutively admitted from 23 February 2020 to 5 April 2020. Demographic and clinical data were retrieved and analyzed throughout the disease course. A total of 93 patients were enrolled, including 45.2% moderate, 54.8% severe, and 2.2% critical type patients. 69.9% of patients had at least one GI symptom; if excluding hyporexia/anorexia, 49.5% of patients showed at least one GI symptom. The incidence rate of hyporexia/anorexia, diarrhea, nausea/vomiting, abdominal discomfort/pain, and elevated liver enzymes were 67.7, 29.0, 28.0, 21.5, and 23.7%, respectively. Patients with GI symptoms or elevated liver enzymes have a higher risk of severe type disease than patients without GI symptoms or elevated liver enzymes (67.7 vs. 25.0%,

Indexed as

COVID-19early stagegastrointestinal symptomsliver injuryWuhan

Identifiers

PMID36341271
PMCPMC9630730
OpenAlexW4306930560

What OpenQuestion holds

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LicenceCC BY
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.