Differences in RDW Values of COVID-19 Patients with Pneumonia and Without Pneumonia at RSUM and RSUDP NTB
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Indri Setiawati , Moulid Hidayat , Rina LestariDOI:
10.29303/jbt.v23i1.5849Published:
2023-11-02Issue:
Vol. 23 No. 1 (2023): Special IssueKeywords:
COVID-19, pneumonia coinfection, red blood cell distribution width.Articles
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Abstract
Pneumonia coinfection in COVID-19 patients can be an important risk factor for patient mortality. Red blood cell distribution width (RDW) is a predictor that can determine clinical outcomes in patients with respiratory tract infections and serious illnesses, so researchers want to conduct research to determine the difference in RDW values in COVID-19 patients with and without pneumonia at RSUM and RSUDP NTB. The design of this research is cross sectional. The sampling technique used was consecutive sampling. There were 110 COVID-19 patient data used in this research. Data collection uses medical record notes. The statistical analysis used was the Mann-Whitney test. The average age of patients was 48 years ± 16 years. Most of the subjects were male (53.6%). The most common comorbidity was diabetes mellitus (21.8%). The average RDW values in COVID-19 patients with and without pneumonia were 13.9% and 13.1%. The difference in the mean RDW value in the two groups is 0.8%. This study found that clinically there were differences in the RDW values of COVID-19 patients with pneumonia and without pneumonia at RSUM and RSUDP NTB.
References
Alkhatib, A., Price, L. L., Esteitie, R., & Lacamera, P. (2020). A Predictive Model for Acute Respiratory Distress Syndrome Mortality Using Red Cell Distribution Width. Critical Care Research and Practice, 2020. DOI: https://doi.org/10.1155/2020/3832683
Alsan, M., Stantcheva, S., Yang, D., & Cutler, D. (2020). Disparities in Coronavirus 2019 Reported Incidence, Knowledge, and Behavior Among US Adults. Jama Network, 3(6). URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303811/
Bai, H. X., Hsieh, B., Xiong, Z., Halsey, K., Choi, J. W., Tran, T. M. L., Pan, I., Shi, L.-B., Wang, D.-C., Mei, J., Jiang, X.-L., Zeng, Q.-H., Egglin, T. K., Hu, P.-F., Agarwal, S., Xie, F., Li, S., Healey, T., Atalay, M. K., …. & Liao, W.-H. (2020). Performance of radiologists in differentiating COVID-19 from viral pneumonia on chest CT. National Library of Medicine. URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233414/
Bernheim, A., Mei, X., Huang, M., Yang, Y., Fayad, Z. A., Zhang, N., Diao, K., Lin, B., Zhu, X., Li, K., Li, S., Shan, H., Jacobi, A., …. & Chung, M. (2020). Chest CT findings of coronavirus disease 2019 (COVID-19). Radiology, 295, 685–695. DOI: https://doi.org/10.29271/jcpsp.2020.Supp1.S53
Büyükkoçak, U., Gencay, I., Ates, G., & Çağlayan, O. (2014). Red Blood Cell Distribution Width and Mortality in ICU Patients; a Cross Sectional Retrospective Analysis Red Blood Cell Distribution Width and Mortality in ICU Patients. Enliven: J Anesthesiol Crit Care Med. 1(4):1-4. DOI: http://dx.doi.org/10.18650/2374-4448.14011
Channappanavar, R., & Perlman, S. (2020). Age-related susceptibility to coronavirus infections: Role of impaired and dysregulated host immunity. Journal of Clinical Investigation, 130(12), 6204–6213. DOI: https://doi.org/10.1172/JCI144115
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., Xia, J., Yu, T., Zhang, X., …. & Zhang, L. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet, 395(10223), 507–513. DOI: https://doi.org/10.1016/S0140-6736(20)30211-7
Conti, P., & Younes, A. (2020). Coronavirus COV-19/SARS-CoV-2 affects women less than men: Clinical response to viral infection. Journal of Biological Regulators and Homeostatic Agents, 34(2), 339–343. DOI: https://doi.org/10.23812/Editorial-Conti-3
Dahlan, M. S. (2014). Statistik untuk Kedokteran dan Kesehatan (A. Kurniawan (ed.); 6th ed.).
Fan, H., Zhou, L., Lv, J., Yang, S., Chen, G., Liu, X., Han, C., Tan, X., Qian, S., Wu, Z., Yu, S., Guo, M., Zhu, C., Chen, Y., …. & Lan, K. (2023). Bacterial coinfections contribute to severe COVID-19 in winter. Cell Research, Maret, 562–564. DOI: https://doi.org/10.1038/s41422-023-00821-3
Gaghaube, A. M., Kaseke, M. M., & Kalangi, S. J. R. (2021). Karakteristik Gambaran Histologis Paru-Paru Pasien COVID-19. Jurnal E-Biomedik, 9(1), 52–67. DOI: https://doi.org/10.35790/ebm.v9i1.31896
Garcia-Vidal, C., Sanjuan, G., Moreno-García, E., Puerta-Alcalde, P., Garcia-Pouton, N., Chumbita, M., Fernandez-Pittol, M., Pitart, C., Inciarte, A., Bodro, M., Morata, L., Ambrosioni, J., Grafia, I., Meira, F., Macaya, I., Cardozo, C., Casals, C., Tellez, A., Castro, P., … & Torres, A. (2021). Incidence of co-infections and superinfections in hospitalized patients with COVID-19: a retrospective cohort study. Clinical Microbiology and Infection, 27(1), 83–88. DOI: https://doi.org/10.1016/j.cmi.2020.07.041
Guo, Y.-R., Cao, Q.-D., Hong, Z.-S., Tan, Y.-Y., Chen, S.-D., Jin, H., Tan, S.-T., Wang, D.-Y., & Yan, Y. (2020). The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak – an update on the status. Military Medical Research, 7(11), 2–10. DOI: https://doi.org/10.1093/eurheartj/ehaa396
Hoque, M. N., Akter, S., Mishu, I. D., Islam, M. R., Rahman, M. S., Akhter, M., Islam, I., Hasan, M. M., Rahaman, M. M., Sultana, M., Islam, T., …. & Hossain, M. A. (2021). Microbial co-infections in COVID-19: Associated microbiota and underlying mechanisms of pathogenesis. Microbial Pathogenesis, 156(April), 104941. DOI: https://doi.org/10.1016/j.micpath.2021.104941
Hughes, S., Troise, O., Donaldson, H., Mughal, N., & Moore, L. S. P. (2020). Bacterial and fungal coinfection among hospitalized patients with COVID-19: a retrospective cohort study in a UK secondary-care setting. Clinical Microbiology and Infection, 26(10), 1395–1399. DOI: https://doi.org/10.1016/j.cmi.2020.06.025
Kim, D., Quinn, J., Pinsky, B., SHah, N. H., & Brown, I. (2020). Rates of Co-infection Between SARS-CoV-2 and Other Respiratory Pathogens. Jama Network, 232(20), 2058–2085. URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160748/
Klein, S. L., & Flanagan, K. L. (2016). Sex differences in immune responses. Nature Reviews Immunology, 16, 626–638. DOI: https://doi.org/10.1038/nri.2016.90
Kurtoǧlu, E., Aktürk, E., Korkmaz, H., Sincer, I., Yilmaz, M., Erdem, K., Çelik, A., & Özdemir, R. (2013). Elevated red blood cell distribution width in healthy smokers. Turk Kardiyoloji Dernegi Arsivi, 41(3), 199–206. DOI: https://doi.org/10.5543/tkda.2013.42375
Lakbar, I., Luque-Paz, D., Mege, J. L., Einav, S., & Leone, M. (2020). COVID-19 gender susceptibility and outcomes: A systematic review. PLoS ONE, 15(11), 1–15. DOI: https://doi.org/10.1371/journal.pone.0241827
Lippi, G., Henry, B. M., & Sanchis-Gomar, F. (2020). Red Blood Cell Distribution Is a Significant Predictor of Severe Illness in Coronavirus Disease 2019. Acta Haematologica. DOI: https://doi.org/10.1159/000510914
Lippi, G., & Plebani, M. (2014). Red blood cell distribution width (RDW) and human pathology. One size fits all. Clinical Chemistry and Laboratory Medicine, 52(9), 1247–1249. DOI: https://doi.org/10.1515/cclm-2014-0585
Satuan Tugas Penanganan COVID-19. (2022). Peta Sebaran. URL: https://covid19.go.id/id/peta-sebaran
Scully, E. P., Haverfield, J., Ursin, R. L., Tannenbaum, C., & Klein, S. L. (2020). Considering how biological sex impacts immune responses and COVID-19 outcomes. Nature Reviews Immunology, 20(7), 442–447. DOI: https://doi.org/10.1038/s41577-020-0348-8
Wang, B., Gong, Y., Ying, B., & Cheng, B. (2019). Relation between Red Cell Distribution Width and Mortality in Critically Ill Patients with Acute Respiratory Distress Syndrome. BioMed Research International, 2019. DOI: https://doi.org/10.1155/2019/1942078
Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., Xiang, H., Cheng, Z., Xiong, Y., Zhao, Y., Li, Y., …. & Wang, X. (2020). Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China. Jama Network, 323(11), 1061–1069. URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042881/
Zhang, H., Wu, Y., He, Y., Liu, X., Liu, M., Tang, Y., Li, X., Yang, G., Liang, G., Xu, S., Wang, M., …. & Wang, W. (2022). Age-Related Risk Factors and Complications of Patients With COVID-19: A Population-Based Retrospective Study. Frontiers in Medicine, 8(January), 1–12. DOI: https://doi.org/10.3389/fmed.2021.757459
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