Evidence map›Paper›PMID 40160330›Full record

ArticleFrontiers in medicine2025

Dynamic changes in platelet counts and psychological state in ITP patients after COVID-19 infection.

Xiaoli Chen, Dan Wang, Jie Tang, Li Wang, Yao Quan, Jia Liu, Zhongmin Zou, Hengrui Sun, Yimei Feng, Xi Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 2025. 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
–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

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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

1 citing paper in PubMed.

  1. Review
4 · The record

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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.

Xiaoli Chen *Medical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Dan Wang *Medical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Jie Tang *Medical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Li WangMedical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Yao QuanMedical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Jia LiuMedical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Zhongmin ZouDepartment of Chemical Defense Medicine, School of Military Preventive Medicine, Army Medical University, Chongqing, China.
Hengrui SunMedical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Yimei FengMedical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.
Xi ZhangMedical Center of Hematology, The Xinqiao Hospital of Army Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: At the end of 2022, the COVID-19 wreaked havoc in China as well as around the world. Here, we focused on the dynamic changes in platelet kinetics and psychological state in ITP patients before and after infection with COVID-19. Methods: A questionnaire survey was designed to retrospectively investigate the COVID-19-related symptoms, changes in platelet count, and psychological changes in ITP patients infected with Omicron variant during November 2022 to January 2023, with a healthy population survey conducted as a control. Results: A total of 90 ITP patients and 69 healthy individuals were included in the study. The results showed that only in terms of low-grade fever, the proportion of ITP patients was significantly higher than that of healthy individuals, 31% vs. 17% ( Conclusion: Some ITP patients showed transiently elevated platelet counts after COVID-19 infection, and the specific mechanism requires further exploration. Additionally, ITP patients experienced heightened anxiety and tension after COVID-19 infection, needing for more mental health support.

Indexed as

COVID-19ITPplatelet countsPLRpsychological state

Identifiers

PMID40160330
PMCPMC11949926

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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.