Evidence map›Paper›PMID 40688484›Full record

ArticleInfectious medicine2025

A comparative analysis of clinical characteristics between primary and recurrent COVID-19 infections in China.

Yuan Chen, Qianjin Su, Dawei Zhang, Wenting Wei, Fangfang Zhang, Qi Li, Jinxue Zhang

Abstract read
In one paragraph

Article in Infectious medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yuan ChenDepartment of Orthopedics, No. 963 Hospital of Chinese People's Liberation Army, Jiamusi 154000, Heilongjiang Province, China.
Qianjin SuDepartment of Orthopedics, No. 963 Hospital of Chinese People's Liberation Army, Jiamusi 154000, Heilongjiang Province, China.
Dawei ZhangThe Fifth Medical Center, Chinese People's Liberation Army General Hospital, Beijing 100039, China.
Wenting WeiPhysical Education Institute, Kunming University, Kunming 650000, Yunnan Province, China.
Fangfang ZhangThe Fifth Medical Center, Chinese People's Liberation Army General Hospital, Beijing 100039, China.
Qi LiDepartment of Orthopedics, No. 963 Hospital of Chinese People's Liberation Army, Jiamusi 154000, Heilongjiang Province, China.
Jinxue ZhangDepartment of Orthopedics, No. 963 Hospital of Chinese People's Liberation Army, Jiamusi 154000, Heilongjiang Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with COVID-19 exhibited a variety of clinical characteristics. However, there is currently insufficient evidence to delineate the differences in clinical symptomatology between primary infection and reinfection. This study aims to compare the clinical symptom characteristics between primary infection and reinfection during COVID-19. Methods: This research utilized a convenience sampling method to gather survey data from Chinese individuals aged 18 to 60 years across China. Questionnaire assessments were conducted to collect data on general demographic and clinical information during the COVID-19 pandemic in China. The collected data were analyzed using IBM SPSS 26.0 software. Results: This study analyzed 1156 patients. During second infection, the frequency of fever, painful muscles, ageusia or anosmia, headache, back pain, feeling hot and cold alternately, general tiredness, tingling extremities, heavy arms or legs, and chest pain symptoms were significantly lower. However, the rate of sneezing, runny nose, and stuffy nose were significantly higher ( Conclusions: The analysis of COVID-19 cases showed significant differences in demographic and clinical symptom characteristics between the first-time and second-time positive populations. This understanding can help guide changes in management strategies.

Indexed as

Clinical featuresCOVID-19ReinfectionSARS-CoV-2Symptoms

Identifiers

PMID40688484
PMCPMC12268010

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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.