Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up
Abstract Background The relaxation of the “zero-COVID” policy on Dec. 7, 2022, in China posed a major public health threat recently. Complete blood count test was discovered to have complicated relationships with COVID-19 after the infection, while very few studies could track long-term monitoring o...
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| Format: | Article |
| Language: | English |
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BMC
2024-03-01
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| Series: | BMC Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12916-024-03326-x |
| _version_ | 1827321437433626624 |
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| author | Yifei Lin Yong Yang Nanyan Xiang Le Wang Tao Zheng Xuejun Zhuo Rui Shi Xiaoyi Su Yan Liu Ga Liao Liang Du Jin Huang |
| author_facet | Yifei Lin Yong Yang Nanyan Xiang Le Wang Tao Zheng Xuejun Zhuo Rui Shi Xiaoyi Su Yan Liu Ga Liao Liang Du Jin Huang |
| author_sort | Yifei Lin |
| collection | DOAJ |
| description | Abstract Background The relaxation of the “zero-COVID” policy on Dec. 7, 2022, in China posed a major public health threat recently. Complete blood count test was discovered to have complicated relationships with COVID-19 after the infection, while very few studies could track long-term monitoring of the health status and identify the characterization of hematological parameters prior to COVID-19. Methods Based on a 13-year longitudinal prospective health checkup cohort of ~ 480,000 participants in West China Hospital, the largest medical center in western China, we documented 998 participants with a laboratory-confirmed diagnosis of COVID-19 during the 1 month after the policy. We performed a time-to-event analysis to explore the associations of severe COVID-19 patients diagnosed, with 34 different hematological parameters at the baseline level prior to COVID-19, including the whole and the subtypes of white and red blood cells. Results A total of 998 participants with a positive SARS-CoV-2 test were documented in the cohort, 42 of which were severe cases. For white blood cell-related parameters, a higher level of basophil percentage (HR = 6.164, 95% CI = 2.066–18.393, P = 0.001) and monocyte percentage (HR = 1.283, 95% CI = 1.046–1.573, P = 0.017) were found associated with the severe COVID-19. For lymphocyte-related parameters, a lower level of lymphocyte count (HR = 0.571, 95% CI = 0.341–0.955, P = 0.033), and a higher CD4/CD8 ratio (HR = 2.473, 95% CI = 1.009–6.059, P = 0.048) were found related to the risk of severe COVID-19. We also observed that abnormality of red cell distribution width (RDW), mean corpuscular hemoglobin concentration (MCHC), and hemoglobin might also be involved in the development of severe COVID-19. The different trajectory patterns of RDW-SD and white blood cell count, including lymphocyte and neutrophil, prior to the infection were also discovered to have significant associations with the risk of severe COVID-19 (all P < 0.05). Conclusions Our findings might help decision-makers and clinicians to classify different risk groups of population due to outbreaks including COVID-19. They could not only optimize the allocation of medical resources, but also help them be more proactive instead of reactive to long COVID-19 or even other outbreaks in the future. |
| first_indexed | 2024-04-25T01:06:05Z |
| format | Article |
| id | doaj.art-859dd22db6374892bfc6f01989204ea0 |
| institution | Directory Open Access Journal |
| issn | 1741-7015 |
| language | English |
| last_indexed | 2024-04-25T01:06:05Z |
| publishDate | 2024-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medicine |
| spelling | doaj.art-859dd22db6374892bfc6f01989204ea02024-03-10T12:14:34ZengBMCBMC Medicine1741-70152024-03-0122111610.1186/s12916-024-03326-xCharacterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-upYifei Lin0Yong Yang1Nanyan Xiang2Le Wang3Tao Zheng4Xuejun Zhuo5Rui Shi6Xiaoyi Su7Yan Liu8Ga Liao9Liang Du10Jin Huang11Department of Urology, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan UniversityHealth Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan UniversityDepartment of Urology, Innovation Institute for Integration of Medicine and Engineering, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan UniversityDepartment of Urology, Innovation Institute for Integration of Medicine and Engineering, Frontiers Science Center for Disease-Related Molecular Network, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, West China Hospital, Sichuan UniversityEngineering Research Center of Medical Information Technology, Ministry of Education, West China Hospital of Sichuan UniversityEngineering Research Center of Medical Information Technology, Ministry of Education, West China Hospital of Sichuan UniversityEngineering Research Center of Medical Information Technology, Ministry of Education, West China Hospital of Sichuan UniversityDepartment of Urology, Innovation Institute for Integration of Medicine and Engineering, Chinese Evidence-Based Medicine Center, West China Hospital, West China Hospital, Sichuan UniversityDepartment of Neurosurgery, Innovation Institute for Integration of Medicine and Engineering, Ministry of Education, West China Hospital of Sichuan UniversityState Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan UniversityDepartment of Urology, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan UniversityDepartment of Urology, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan UniversityAbstract Background The relaxation of the “zero-COVID” policy on Dec. 7, 2022, in China posed a major public health threat recently. Complete blood count test was discovered to have complicated relationships with COVID-19 after the infection, while very few studies could track long-term monitoring of the health status and identify the characterization of hematological parameters prior to COVID-19. Methods Based on a 13-year longitudinal prospective health checkup cohort of ~ 480,000 participants in West China Hospital, the largest medical center in western China, we documented 998 participants with a laboratory-confirmed diagnosis of COVID-19 during the 1 month after the policy. We performed a time-to-event analysis to explore the associations of severe COVID-19 patients diagnosed, with 34 different hematological parameters at the baseline level prior to COVID-19, including the whole and the subtypes of white and red blood cells. Results A total of 998 participants with a positive SARS-CoV-2 test were documented in the cohort, 42 of which were severe cases. For white blood cell-related parameters, a higher level of basophil percentage (HR = 6.164, 95% CI = 2.066–18.393, P = 0.001) and monocyte percentage (HR = 1.283, 95% CI = 1.046–1.573, P = 0.017) were found associated with the severe COVID-19. For lymphocyte-related parameters, a lower level of lymphocyte count (HR = 0.571, 95% CI = 0.341–0.955, P = 0.033), and a higher CD4/CD8 ratio (HR = 2.473, 95% CI = 1.009–6.059, P = 0.048) were found related to the risk of severe COVID-19. We also observed that abnormality of red cell distribution width (RDW), mean corpuscular hemoglobin concentration (MCHC), and hemoglobin might also be involved in the development of severe COVID-19. The different trajectory patterns of RDW-SD and white blood cell count, including lymphocyte and neutrophil, prior to the infection were also discovered to have significant associations with the risk of severe COVID-19 (all P < 0.05). Conclusions Our findings might help decision-makers and clinicians to classify different risk groups of population due to outbreaks including COVID-19. They could not only optimize the allocation of medical resources, but also help them be more proactive instead of reactive to long COVID-19 or even other outbreaks in the future.https://doi.org/10.1186/s12916-024-03326-xHealth checkupProspective cohortCOVID-19Proactive healthLong term |
| spellingShingle | Yifei Lin Yong Yang Nanyan Xiang Le Wang Tao Zheng Xuejun Zhuo Rui Shi Xiaoyi Su Yan Liu Ga Liao Liang Du Jin Huang Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up BMC Medicine Health checkup Prospective cohort COVID-19 Proactive health Long term |
| title | Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up |
| title_full | Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up |
| title_fullStr | Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up |
| title_full_unstemmed | Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up |
| title_short | Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up |
| title_sort | characterization and trajectories of hematological parameters prior to severe covid 19 based on a large scale prospective health checkup cohort in western china a longitudinal study of 13 year follow up |
| topic | Health checkup Prospective cohort COVID-19 Proactive health Long term |
| url | https://doi.org/10.1186/s12916-024-03326-x |
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