Evidence map›Paper›PMID 35264110›Full record

ArticleBMC gastroenterology2022

Early changes in laboratory tests predict liver function damage in patients with moderate coronavirus disease 2019: a retrospective multicenter study.

Yiting Wang, Dandan Gao, Xuewen Li, Panyang Xu, Qi Zhou, Junguo Yin, Jiancheng Xu

Abstract readMulticenter Study
In one paragraph

Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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.

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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

7 authors.

Yiting Wang *Department of Laboratory Medicine, First Hospital of Jilin University, 1 Xinmin Street, Changchun, 130021, China.ORCID http://orcid.org/0000-0001-5977-5407
Dandan Gao *Department of Laboratory Medicine, First Hospital of Jilin University, 1 Xinmin Street, Changchun, 130021, China.
Xuewen LiDepartment of Laboratory Medicine, First Hospital of Jilin University, 1 Xinmin Street, Changchun, 130021, China.ORCID http://orcid.org/0000-0001-9880-571X
Panyang XuDepartment of Laboratory Medicine, First Hospital of Jilin University, 1 Xinmin Street, Changchun, 130021, China.ORCID http://orcid.org/0000-0002-2895-9112
Qi ZhouDepartment of Pediatrics, First Hospital of Jilin University, Changchun, 130021, China.ORCID http://orcid.org/0000-0002-5084-8697
Junguo YinDepartment of Laboratory Medicine, Changchun Hospital of Traditional Chinese Medicine, Changchun, 130021, China.
Jiancheng XuDepartment of Laboratory Medicine, First Hospital of Jilin University, 1 Xinmin Street, Changchun, 130021, China. xjc@jlu.edu.cn.ORCID http://orcid.org/0000-0001-8796-271X

Funding

Jiancheng Xu no. 20190304110YYQi Zhou no. 20200404171YY
6 · The paper itself

Abstract

backgroundMost patients with coronavirus disease 2019 demonstrate liver function damage. In this study, the laboratory test data of patients with moderate coronavirus disease 2019 were used to establish and evaluate an early prediction model to assess the risk of liver function damage.

methodsClinical data and the first laboratory examination results of 101 patients with moderate coronavirus disease 2019 were collected from four hospitals' electronic medical record systems in Jilin Province, China. Data were randomly divided into training and validation sets. A logistic regression analysis was used to determine the independent factors related to liver function damage in patients in the training set to establish a prediction model. Model discrimination, calibration, and clinical usefulness were evaluated in the training and validation sets.

resultsThe logistic regression analysis showed that plateletcrit, retinol-binding protein, and carbon dioxide combining power could predict liver function damage (P < 0.05 for all). The receiver operating characteristic curve showed high model discrimination (training set area under the curve: 0.899, validation set area under the curve: 0.800; P < 0.05). The calibration curve showed a good fit (training set: P = 0.59, validation set: P = 0.19; P > 0.05). A decision curve analysis confirmed the clinical usefulness of this model.

conclusionsIn this study, the combined model assesses liver function damage in patients with moderate coronavirus disease 2019 performed well. Thus, it may be helpful as a reference for clinical differentiation of liver function damage. Trial registration retrospectively registered.

Indexed as

COVID-19HumansLiverNomogramsRetrospective StudiesRisk FactorsSARS-CoV-2Carbon dioxide combining powerCoronavirus disease 2019Liver functionNomogramPlateletcritPredictRetinol-binding protein

Identifiers

PMID35264110
PMCPMC8905025

What OpenQuestion holds

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Registered trials

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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.