Evidence map›Paper›PMID 35865540›Full record

ArticleFrontiers in immunology2022

High Number and Specific Comorbidities Could Impact the Immune Response in COVID-19 Patients.

Dafeng Liu, Xiaoyan Yuan, Fengjiao Gao, Bennan Zhao, Ling Ding, Mingchang Huan, Chao Liu, Liangshuang Jiang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.5field-weighted citation impact, top 9% 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

18 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
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  8. Article
  9. Review
  10. Article
  11. Article
  12. COVID-19 and Fatty Liver Disorders.Journal of clinical medicine · 2023
    Review
  13. Article
  14. SARS-CoV2 Infection and Comorbidity in Inmates: A Study of Central Italy.International journal of environmental research and public health · 2023
    Article
  15. Article
  16. Review
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  18. 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

8 authors at 1 institution in 1 country.

Dafeng LiuDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Xiaoyan YuanDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Fengjiao GaoDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Bennan ZhaoDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Ling DingDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Mingchang HuanDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Chao LiuDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Liangshuang JiangDepartment of Internal Medicine, Public Health and Clinical Centre of Chengdu, Chengdu, China.
Public Health Clinical Center of Chengdu · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cellular immunodeficiency and comorbidities are common in COVID-19 patients. Aim: The purpose of this study was to investigate comorbidities impacting on the cellular immunity in COVID-19 patients. Methods: The research objects included 55 healthy controls and 718 COVID-19 patients who divided into the control group and the COVID-19 group, respectively. Those in the COVID-19 group were divided into subgroups on the basis of the number and types of comorbidities present. Lymphocyte itself and its subsets were compared between the control group and the COVID-19 group, the groups with comorbidities based on the different number and types of comorbidities, and the relationship between the lymphocyte counts and subsets with the number and types of comorbidities was investigated. Results: Compared with the control group, the lymphocyte counts and T cell subsets were significantly increased in the groups with comorbidities, but both B and NK cell subsets were significantly decreased in the no comorbidity group and in most of the groups with comorbidities (all P<0.05). In the three comorbidities group, the lymphocyte counts and T cell subsets were all significantly decreased, but the CD56+ percentage was obviously increased (all P<0.05). The number of comorbidities was negatively correlated with the lymphocyte counts and the T and NK cell subsets. A negative correlation also existed between cancer and both the lymphocyte counts and the T cell subsets, between chronic hepatitis B and the lymphocyte counts, and between chronic kidney disease and the CD3+ counts. A positive correlation existed between nonalcoholic fatty liver disease (NAFLD) disease and both lymphocyte and CD3+ counts. The risk factors were number of comorbidities for the lymphocyte count, CD3+CD4+ and CD3+CD8+ percentages, NAFLD for the lymphocyte and CD3+ counts, cardiovascular diseases for CD3+CD4+ and CD3+CD8+ percentages, diabetes mellitus for the CD3+CD8+ percentage, and cancer for the CD3+ percentage, respectively. Conclusions: High numbers of comorbidities and specific comorbidities could impact the immune response of COVID-19 patients. This study provides a reference for clinicians in the identification of suitable and timely immunotherapy for COVID-19 patients. Clinical Trial Registry: https://www.chictr.org.cn/enindex.aspx, identifier ChiCTR2000034563.

Indexed as

COVID-19Non-alcoholic Fatty Liver DiseaseHumansImmunityLymphocyte CountLymphocyte Subsetscomorbiditiescoronavirus disease 2019 (COVID-19)immune responseimpactlymphocyte subsets

Identifiers

PMID35865540
PMCPMC9295452
OpenAlexW4283814979

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.