Evidence map›Paper›PMID 39183824›Full record

ArticleHeliyon2024

Dynamic changes of complete blood cell count parameters among airport workers during the COVID-19 pandemic in Chongqing, China: A retrospective longitudinal study.

Baige Cao, Yingchao Li, Jinfang Xu, Yinan Zhang, Congrong Wang

Abstract read
In one paragraph

Article in Heliyon, 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
–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

1 citing paper in PubMed.

  1. 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

5 authors.

Baige CaoDepartment of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Yingchao LiDepartment of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Jinfang XuDepartment of Health Statistics, Second Military Medical University, Shanghai, China.
Yinan ZhangThe Metabolic Disease Biobank, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Congrong WangDepartment of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: This study aimed to examine the dynamic changes in the complete blood counts of airport staff from 2019 to 2021 and assess the impact of the coronavirus disease 2019 (COVID-19) on their overall health status during the first pandemic wave. Materials and methods: A total of 2144 airport staff members from Chongqing Jiangbei International Airport who underwent health examinations for three consecutive years from 2019 to 2021 were recruited for this study. Venous blood samples were collected for a complete blood cell count. Results: Changes were observed in blood routine parameters from airport staff over three consecutive years. After adjusting for age, body mass index, and systolic blood pressure, the red blood cell count decreased consecutively during the COVID-19 pandemic. Hemoglobin and basophil counts decreased significantly during COVID-19 year 1. Lymphocyte and platelet counts decreased, whereas the monocyte-to-lymphocyte ratio increased in COVID-19 year 2. However, the white blood cell count, neutrophil count, neutrophil-to-lymphocyte ratio, and eosinophil count did not change from 2019 to 2021. Conclusion: This study showed changes in complete blood counts in frontline airport workers, especially men, during the COVID-19 pandemic. Therefore, paying more attention to the overall health conditions and immune function of airport staff engaged in intensive work is necessary.

Indexed as

Airport staffChinaComplete blood countCOVID-19

Identifiers

PMID39183824
PMCPMC11341334

What OpenQuestion holds

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LicenceCC BY
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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.