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Longitudinal Count Data Analysis of Factors Affecting Epileptic Seizure of Patients in Case of Gondar Referral Hospital, Northwest Ethiopia

Received: 4 June 2020     Accepted: 18 June 2020     Published: 28 July 2020
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Abstract

Even though the world is fighting epileptic seizure disease in unity and patients are getting treatment, it continued to be a serious health issue for parts of the world and a large number of patients are being registered every year. The main objective of this study was to identify associated risk factors affecting the progression of patients in Gondar Referral Hospital. In this longitudinal count data analysis, data was collected from 337 epileptic seizure patients registered for treatment from January 1, 2016 to April 30, 2018 in the Hospital and Poisson, Poisson-gamma, Poisson-Normal and Poisson-Gamma-Normal models were applied to the data. Poisson-Gamma-Normal model with random intercept was selected as a best model to fit the data based on different model selection criteria. The findings of the study revealed that time, brain injury, treatment, interaction of time with residence and interaction of time with brain injury were significant factors for epileptic seizure of the patients. Minimization of epileptic seizure of patients in response to treatment was observed, which means the patients were at decreased epileptic seizure when enrolled for treatment. Therefore, patients should be encouraged to stay on treatment.

Published in American Journal of Bioscience and Bioengineering (Volume 8, Issue 4)
DOI 10.11648/j.bio.20200804.11
Page(s) 59-69
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Epilepsy, Longitudinal Data Analysis, Seizure, Poisson-Normal Model, Poisson-Gamma-Normal Model

References
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[2] Bazil C, Pedley T. (2005). Epilepsy. In: Rowland LP, editor. Merritt’s Neurology. 11th ed. Philadelphia: Lippincott Williams & Wilkins; pp. 990–1008.
[3] Lowenstein DH (2008). Seizures and epilepsy. In: Fauci A, Kasper DL, Longo DL, editors. Harrison’s Principles of Internal Medicine. 17th ed. New York: McGraw-Hill; pp. 2498–2512. Section 2: Diseases of the Central Nervous System.
[4] Ayalew, M., and Muche, E. (2018). Patient reported adverse events among epileptic patients taking antiepileptic drugs. SAGE open medicine, 6, 2050312118772471.
[5] Berhanu, S., Alemu, S., Prevett, M., and Parry, E. (2009). Primary care treatment of epilepsy in rural Ethiopia: causes of default from follow-up. Seizure, 18 (2), 100-103.
[6] Megiddo, I., Colson, A., Chisholm, D., Dua, T., Nandi, A., and Laxminarayan, R. (2016). Health and economic benefits of public financing of epilepsy treatment in India: An agent‐based simulation model. Epilepsia, 57 (3), 464-474.
[7] Verbeke, G. (1997). Linear mixed models for longitudinal data. In Linear mixed models in practice (pp. 63-153). Springer, New York, NY.
[8] Booth, J. G., Casella, G., Friedl, H., and Hobert, J. P. (2003). Negative binomial log linear mixed models. Statistical Modelling, 3 (3), 179-191.
[9] Molenberghs, G., Verbeke, G., and Demétrio, C. (2007). An extended random-effects approach to modeling repeated, overdispersed count data. Lifetime data analysis, 13 (4), 513-531.
[10] Molenberghs, G., Verbeke, G., Demétrio, C., and Vieira, A. M. (2010). A family of generalized linear models for repeated measures with normal and conjugate random effects. Statistical science, 25 (3), 325-347.
[11] Hilbe M. (2011). Negative Binomial Regression. Second edition. Cambridge University Press, New York.
[12] Devinsky, O., Marsh, E., Friedman, D., Thiele, E., Laux, L., Sullivan, J.,... and Wong, M. (2016). Cannabidiol in patients with treatment-resistant epilepsy: an open-label interventional trial. The Lancet Neurology, 15 (3), 270-278.
[13] Devinsky, O., Cross, J., Laux, L., Marsh, E., Miller, I., Nabbout, R.,... and Wright, S. (2017). Trial of cannabidiol for drug-resistant seizures in the Dravet syndrome. New England Journal of Medicine, 376 (21), 2011-2020.
[14] Jeffery (2008). Research paper on epilepsy." vol. 5, no. 9, article a022848.
[15] Gebre, A., and Haylay, A. (2018). Sociodemographic, Clinical Variables, and Quality of Life in Patients with Epilepsy in Mekelle City, Northern Ethiopia. Behavioural neurology, 2018.
[16] Shuo-BinJou, (2012). Epilepsy in the Elderly. International Journal of Gerontology Volume 6: Pages 63-67.
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    Belema Hailu Regesa, Gizachew Gobebo Mekebo. (2020). Longitudinal Count Data Analysis of Factors Affecting Epileptic Seizure of Patients in Case of Gondar Referral Hospital, Northwest Ethiopia. American Journal of Bioscience and Bioengineering, 8(4), 59-69. https://doi.org/10.11648/j.bio.20200804.11

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    ACS Style

    Belema Hailu Regesa; Gizachew Gobebo Mekebo. Longitudinal Count Data Analysis of Factors Affecting Epileptic Seizure of Patients in Case of Gondar Referral Hospital, Northwest Ethiopia. Am. J. BioSci. Bioeng. 2020, 8(4), 59-69. doi: 10.11648/j.bio.20200804.11

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    AMA Style

    Belema Hailu Regesa, Gizachew Gobebo Mekebo. Longitudinal Count Data Analysis of Factors Affecting Epileptic Seizure of Patients in Case of Gondar Referral Hospital, Northwest Ethiopia. Am J BioSci Bioeng. 2020;8(4):59-69. doi: 10.11648/j.bio.20200804.11

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  • @article{10.11648/j.bio.20200804.11,
      author = {Belema Hailu Regesa and Gizachew Gobebo Mekebo},
      title = {Longitudinal Count Data Analysis of Factors Affecting Epileptic Seizure of Patients in Case of Gondar Referral Hospital, Northwest Ethiopia},
      journal = {American Journal of Bioscience and Bioengineering},
      volume = {8},
      number = {4},
      pages = {59-69},
      doi = {10.11648/j.bio.20200804.11},
      url = {https://doi.org/10.11648/j.bio.20200804.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bio.20200804.11},
      abstract = {Even though the world is fighting epileptic seizure disease in unity and patients are getting treatment, it continued to be a serious health issue for parts of the world and a large number of patients are being registered every year. The main objective of this study was to identify associated risk factors affecting the progression of patients in Gondar Referral Hospital. In this longitudinal count data analysis, data was collected from 337 epileptic seizure patients registered for treatment from January 1, 2016 to April 30, 2018 in the Hospital and Poisson, Poisson-gamma, Poisson-Normal and Poisson-Gamma-Normal models were applied to the data. Poisson-Gamma-Normal model with random intercept was selected as a best model to fit the data based on different model selection criteria. The findings of the study revealed that time, brain injury, treatment, interaction of time with residence and interaction of time with brain injury were significant factors for epileptic seizure of the patients. Minimization of epileptic seizure of patients in response to treatment was observed, which means the patients were at decreased epileptic seizure when enrolled for treatment. Therefore, patients should be encouraged to stay on treatment.},
     year = {2020}
    }
    

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    AU  - Belema Hailu Regesa
    AU  - Gizachew Gobebo Mekebo
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    JO  - American Journal of Bioscience and Bioengineering
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    AB  - Even though the world is fighting epileptic seizure disease in unity and patients are getting treatment, it continued to be a serious health issue for parts of the world and a large number of patients are being registered every year. The main objective of this study was to identify associated risk factors affecting the progression of patients in Gondar Referral Hospital. In this longitudinal count data analysis, data was collected from 337 epileptic seizure patients registered for treatment from January 1, 2016 to April 30, 2018 in the Hospital and Poisson, Poisson-gamma, Poisson-Normal and Poisson-Gamma-Normal models were applied to the data. Poisson-Gamma-Normal model with random intercept was selected as a best model to fit the data based on different model selection criteria. The findings of the study revealed that time, brain injury, treatment, interaction of time with residence and interaction of time with brain injury were significant factors for epileptic seizure of the patients. Minimization of epileptic seizure of patients in response to treatment was observed, which means the patients were at decreased epileptic seizure when enrolled for treatment. Therefore, patients should be encouraged to stay on treatment.
    VL  - 8
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Author Information
  • Department of Statistics, Ambo University, Ambo, Ethiopia

  • Department of Statistics, Ambo University, Ambo, Ethiopia

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