The Effect of Symptoms on the Survival Time of Coronavirus Patients in the Sudanese Population

Authors

  • Alshaikh A. Shokeralla Department of Mathematics, College of Science and Arts, Al-Baha University, Al-Makhwah, KSA
  • Mohammedelameen E. Qurashi Department of Statistics, College of Science, Sudan University of Science & Technology, Sudan https://orcid.org/0000-0003-1036-1398
  • Reem Yousif Mekki Department of Statistics College of Computer Science and Mathematics, University of Bahri, Sudan
  • Mortada S. Ali Department of Mathematics, College of Science and Arts, Al-Baha University, Al-Makhwah, KSA https://orcid.org/0000-0003-0645-2983

DOI:

https://doi.org/10.6000/1929-6029.2023.12.29

Keywords:

Survival Analysis, Kaplan –Meier, log-rank, COVID-19, symptoms

Abstract

The COVID-19 pandemic has rapidly spread worldwide, resulting in substantial rates of illness and death. Gaining insight into the various factors that impact the duration of survival among individuals diagnosed with COVID-19 is of utmost importance to inform clinical practices and public health strategies This study aims to evaluate the relationship between the acuteness of symptoms and the survival time of coronavirus patients in Sudan. The Kaplan-Meier curves and log-rank test were used to determine the symptom pattern. The results of COVID-19 and Cox regression were utilized to determine the most critical symptoms affecting coronavirus patients. The log-rank test revealed that there are differences in the pattern of age and symptoms among coronavirus patients. Cox regression revealed that symptoms affect on the survival time of coronavirus patients. The Cox proportional Hazard Model shows that the hazard of age at any time increases by 116.5%, diarrhea increases by 9%, headache increases by 62.0%, fatigability increases by 13.3%, and other symptoms increase by 47.3%. This study differs from prior studies in several ways. No current study in Sudan has used survival analysis to discover the most relevant symptoms affecting survival time.

References

Centers for Disease Control and Prevention. Symptoms of coronavirus 2020.

Han C, et al. Digestive Symptoms in COVID-19 Patients With Mild Disease Severity: Clinical Presentation, Stool Viral RNA Testing, and Outcomes. The American Journal of Gastroenterology 2020; 1-8. https://doi.org/10.14309/ajg.0000000000000664 DOI: https://doi.org/10.14309/ajg.0000000000000664

Sisay G, Mantefardo B, Beyene A.Time from symptom onset to severe COVID-19 and risk factors among patients in Southern Ethiopia: a survival analysis. Journal of International Medical Research 2022; 50(8): 1-12. https://doi.org/10.1177/03000605221119366 DOI: https://doi.org/10.1177/03000605221119366

KasoI DAW, et al. Survival analysis of COVID-19 patients in Ethiopia: A hospital-based study. PLOS One 2022; 17(5): e0268280. https://doi.org/10.1371/journal.pone.0268280 DOI: https://doi.org/10.1371/journal.pone.0268280

Subramanian A, et al. Symptoms and risk factors for long COVID in non-hospitalized adults. Nature Medicine 2002; (28): 1706-1717. https://doi.org/10.1038/s41591-022-01909-w DOI: https://doi.org/10.1038/s41591-022-01909-w

Ghodsiyeh A, Freshteh O. Clinical characteristics and risk factors for mortality in COVID-19 inpatients in Birjand, Iran: a single-center retrospective study. Eur J Med Res 2021; 26(1): 79. https://doi.org/10.1186/s40001-021-00553-3 DOI: https://doi.org/10.1186/s40001-021-00553-3

Lawless JF. Statistical Models and Methods for Lifetime Data, Second Edition. Second Edition ed. New York: John Wiley & Sons 2011.

Collett, David. Modelling Survival Data in Medical Research. Fourth Edition. London: Chapman & Hall 2023. https://doi.org/10.1201/9781003282525 DOI: https://doi.org/10.1201/9781003282525

Kleinbaum David G, Mitchel Klein. Survival Analysis A Self-Learning Tex. Third Edition. New York: Springer Science 2012. https://doi.org/10.1007/978-1-4419-6646-9 DOI: https://doi.org/10.1007/978-1-4419-6646-9

Lee ET, Wang JW. Statistical Methods for Survival Data Analysis. Fourth Edition ed. Canada: John Wiley & Sons, Inc., Hoboken, New Jersey 2013.

Kalbfleisch JL, Prentice RL. The Statistical Analysis Of Failure Time Data,. Second Edition ed. Canada.: by John Wiley & Sons, Inc., Hoboken, New Jersey 2002. https://doi.org/10.1002/9781118032985 DOI: https://doi.org/10.1002/9781118032985

Downloads

Published

2023-12-19

How to Cite

Shokeralla, A. A. ., Qurashi, M. E. ., Mekki, R. Y. ., & Ali, M. S. . (2023). The Effect of Symptoms on the Survival Time of Coronavirus Patients in the Sudanese Population. International Journal of Statistics in Medical Research, 12, 249–256. https://doi.org/10.6000/1929-6029.2023.12.29

Issue

Vol. 12 (2023)

Section

General Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Policy for Journals/Articles with Open Access

Authors who publish with this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

  • Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work

Policy for Journals / Manuscript with Paid Access

Authors who publish with this journal agree to the following terms:

  • Publisher retain copyright .

  • Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work .
Crossref
Scopus
Google Scholar
Europe PMC