Evidence map›Paper›PMID 38285376›Full record

ArticleClinical rheumatology2024

The effect of COVID-19 infection on patients with rheumatic diseases in China.

Peng Lai, Haifeng Chen, Yunxia Yan, Mengru Du, Zhiling Zhao, Dandan Wang, Jun Liang, Lingyu Geng, Xue Xu, Lingyun Sun

Abstract read
PubMed Publisher
In one paragraph

Article in Clinical rheumatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Surveillance of SARS-CoV-2 variants in Henan, China from 2023 to 2024.Frontiers in cellular and infection microbiology · 2025
    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

10 authors at 2 institutions in 1 country.

Peng Lai *Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
Haifeng Chen *The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, 299 Qingyang Road, Wuxi, 214000, Jiangsu, China.
Yunxia Yan *Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
Mengru DuDepartment of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
Zhiling ZhaoDepartment of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
Dandan WangDepartment of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
Jun LiangDepartment of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China. 13505193169@163.com.
Lingyu GengDepartment of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China. genglinyu1987@163.com.
Xue XuDepartment of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China. iamxuxue@163.com.ORCID http://orcid.org/0000-0001-7505-0991
Lingyun SunDepartment of Rheumatology and Immunology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
Nanjing Drum Tower Hospital · CNWuxi People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAt the end of 2022, the COVID-19 outbreak erupted in China, and BA.5.2 or BF.7 subtypes of Omicron novel variations were implicated in more than 90% of the cases. We created a real-world questionnaire survey to better understand how this new variant pandemic was affecting rheumatic patients in China.

methodsDuring the COVID-19 outbreak in China, the subjects of this study were rheumatic patients and non-rheumatic individuals (control group), who were matched for sex and age. Professional physicians carefully questioned the participants before administering a questionnaire as part of the study. This study focused on the general baseline characteristics, clinical symptoms and treatment after COVID-19 infection, and the target populations' awareness of COVID-19.

resultsThe study included 1130 participants, of whom 572 were assigned to the rheumatic group and 558 to the control group. The percentage of vaccinated controls was significantly higher than that of rheumatic patients (90.1% vs. 62.8%, p < 0.001), while the rate of COVID-19 infection was not significantly different between the two groups (82.3% vs. 86.6%, p = 0.051). Patients with rheumatic disease experienced substantially more days of fever following infection (2.87 ± 3.42 vs. 2.18 ± 1.65, p = 0.002) compared to individuals in the control group. The rheumatic patients had a greater prevalence of cough (67.1% vs. 54.0%, p < 0.001), somnipathy (13.8% vs. 6.0%, p < 0.001), and conjunctivitis/ophthalmodynia (5.3% vs. 2.1%, p = 0.008), while dry throat/throat pain/weakness (49.9% vs. 59.4%, p = 0.003), myalgia/osteodynia (33.3% vs. 41.8%, p = 0.003), and dyspnea (14.0% vs. 25.3%, p < 0.001) were more likely to occur in non-rheumatic group after infection. Human immunoglobulin (2.1% vs. 0.2%, p = 0.006), glucocorticoids (19.5% vs. 1.6%, p < 0.001), oxygen support (6.8% vs. 2.1%, p < 0.001), and traditional Chinese medicine (21.9% vs. 16.6%, p = 0.037) were all more frequently used by rheumatic patients with COVID-19 infection. People in the control group were more confused about whether to use masks in following social activities after contracting COVID-19 (14.7% vs. 7.6%, p = 0.001). In the control group, more individuals than patients with rheumatic disease (25.1% vs. 13.4%, p < 0.001) expressed an interest to receive the vaccine again. After being exposed to COVID-19, the majority of rheumatic patients (66.9%) reported no discernible change, only 29.1% reported a worsening of their symptoms, and the remaining 4% indicated an improvement.

conclusionsAfter the COVID-19 outbreak in China, the proportion of patients with rheumatic diseases infected with the virus was similar to that of normal individuals. But the clinical symptoms, follow-up treatment requirements, and awareness of the COVID-19 among rheumatic patients were distinct from those among non-rheumatic patients, necessitating the use of individualized diagnosis and treatment plans as well as health advice by medical professionals in clinical work. Key Points • Despite there were different comorbidities and vaccination rates, the rate of COVID-19 infection in patients with rheumatic disease was similar to that of normal individuals. • After COVID-19 infection, rheumatic patients and normal controls had different clinical symptoms and drug usage. • After being exposed to COVID-19, the majority of rheumatic patients felt no significant change in the primary disease, while the normal controls was more likely to accept a new vaccine injection and confused about whether to use masks in following social activities.

Indexed as

COVID-19Rheumatic DiseasesVaccinesChinaHumansMyalgiaVaccinesCOVID-19InfectionRheumatic patients

Identifiers

PMID38285376
OpenAlexW4391316166

What OpenQuestion 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 OpenQuestion graph.