GBV Determinants of Survival of HIV-HAART Naive Patients to HAART Initiation at Bondo Sub-County Hospital: A Two Year Retrospective Cohort Study
International Journal of HIV/AIDS Prevention, Education and Behavioural Science
Volume 3, Issue 2, April 2017, Pages: 7-14
Received: Feb. 10, 2017;
Accepted: Feb. 23, 2017;
Published: May 10, 2017
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Oghera Wesley Ooga, Institute of Tropical and Infectious Diseases, College of Health Sciences, University of Nairobi, Nairobi, Kenya
Otundo Denis Orare, Institute of Tropical and Infectious Diseases, College of Health Sciences, University of Nairobi, Nairobi, Kenya
Wambura Francis Muchiri, Institute of Topical Medicine and Infectious Diseases (ITROMID), College of Health Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Chimbevo Mwagandi Lenny, School of Health Sciences, Kirinyaga University, Kerugoya, Kenya
Kariuki James Ngumo, Center for Public Health Research (CPHR), Department of KEMRI, Nairobi, Kenya
Wang’ombe Anne, Institute of Tropical and Infectious Diseases, College of Health Sciences, University of Nairobi, Nairobi, Kenya
HIV-AIDS remains a major public health issue in Kenya with a prevalence of 5.3% and contributing to 29% of annual mortality. Despite marked improvement in the provision for care and treatment, a search for improvement of the current care and treatment programs may lead to better health outcomes. Various factors influence the prognosis of HIV disease. However, minimal research has been conducted to determine information gathered on enrollment influence HIV-AIDS prognosis. Early identification of how information can inform disease prognosis may aid in improving management strategies and increase quality of life of the HIV infected patients. This research aimed at determining how collected information influence times to HAART eligibility and factors influencing this duration. A retrospective cohort study was carried out in Bondo Sub County Hospital Comprehensive Care Centre. Primary data was collected from patient treatment files, in the period beginning 1st January 2013 to 31st December 2014 in data collection forms entered in Microsoft Excel, cleaned and transferred to Stata ver 13 for survival analysis. In the study period 2015 patients were enrolled and 164 (female=93, male =71) satisfied the inclusion criteria. The medium survival time was 65 days. The WHO stage of enrollment (p = 0.0000) and age of enrollment (p = 0.006) were found to be the major determinants of the time to HAART eligibility. The WHO stages of enrollment and age of enrollment were strongly associated with HIV prognosis and this could be attributed to level of immune status which is affected by both this factors. Age of enrollment and WHO stage of enrollment were the main variables captured in MOH 257 that inform on HIV-HAART naïve disease progression to HAART eligibility. This study needs to be done in a prospective study incorporating time dependent covariates so as to give a clear picture of the other covariates not picked in this study.
Oghera Wesley Ooga,
Otundo Denis Orare,
Wambura Francis Muchiri,
Chimbevo Mwagandi Lenny,
Kariuki James Ngumo,
GBV Determinants of Survival of HIV-HAART Naive Patients to HAART Initiation at Bondo Sub-County Hospital: A Two Year Retrospective Cohort Study, International Journal of HIV/AIDS Prevention, Education and Behavioural Science.
Vol. 3, No. 2,
2017, pp. 7-14.
National Aids Control Council Kenya(NACC). (2014). KENYA HIV COUNTY PROFILES. NAIROBI: National Aids Control Council Kenya.
WHO. (2014). GLOBAL UPDATE ON HEALTH SECTOR RESPONSE TO HIV. GENEVA: WHO.
Kenya National Bearau of Statistic(KNBS). (2013). statistical abstract 2013. Nairobi: KNBS.
National AIDS/STI Control Program(NASCOP). (2011). Guidelines for aantiretroviral therapy in Kenya. Nairobi: NASCOP.
National Aids Control Council kenya(NACC). (2014). Kenya aids progressive report. nairobi: natinal aids contol council.
NASCOP. (2014). guidelines on use of ntiretroviral drugs for treating and preventing HIV infection:a rapid advise. NAIROBI: MINISTRY OF HEALTH.
Kleinbaum, D. G., & Klein, M. (2005). Survival analysis:a self learning text. New York: springer.
Lee, E., & wang, J. W. (2003). Statistical Methods for Survival Data Analysis. New Jersey: John Wiley & Sons.
Kaplan, E. L., & Meier, P. (1958). Non-parametric Estimation from Incomplete Observation. journal of American Statistical Association, 457-48.
Mantel, N., & Haenszel, W. (1959). Statistical Aspect of the Analysis of Data from Retrospetive Studies od Diseases. Journal of National Cancer Institute, 719-748.
Branson BM, Handsfield HH, Lampe MA, et al. Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep. Sep 22 2006;55(RR-14):1-17. Available at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16988643.
Granich RM, Gilks CF, Dye C, De Cock KM, Williams BG. Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model. Lancet. Jan 3 2009;373(9657):48-57. Available at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19038438.
Althoff KN, Gange SJ, Klein MB, et al. Late presentation for human immunodeficiency virus care in the United States and Canada. Clin Infect Dis. Jun 1 2010;50(11):1512-1520. Available at http://www.ncbi.nlm.nih.gov/pubmed/20415573.
Wolbers M, Bucher HC, Furrer H, et al. Delayed diagnosis of HIV infection and late initiation of antiretroviral therapy in the Swiss HIV Cohort Study. HIV Med. Jul 2008;9(6):397-405. Available at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18410354.
Centers for Disease Control and Prevention. Late HIV testing—34 states, 1996–2005. MMWR Morb Mortal Wkly Rep. Jun 26 2009;58(24):661-665. Available at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19553901.
Grigoryan A, Hall HI, Durant T, Wei X. Late HIV diagnosis and determinants of progression to AIDS or death after HIV diagnosis among injection drug users, 33 US States, 1996–2004. PLoS One. 2009;4(2):e4445. Available at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19214229.
Anastos, k., Gange, S. J., Lau, B., Weiser, B., & Detels, R. (2000). Association of race and gender with HIV-1 RNA levels and immunologic progression. journal of acquired immunodeficiency syndrome, 218-226.
Faauci, A. S., & Lane, H. C. (2005). Harrison's Principles of Internal Medicine 16 Edition (Edited by: Fauci AS, Lane HC). McGraw-Hill 2005, 1:p1076–1139. McGraw-Hill 2005, 1:p1076–1139.
Winchester, M. S., McGrath, J. W., Kaawa-mafigiri, D., Namutiiba, F., Ssendegye, G., Nalwoga, A., et al. (2013). Early HIV disclosure and nondisclosure among men and women on antiretroviral treatment in Uganda. AIDS Care: Psychological and Socio-medical Aspects of AIDS/HIV, 1253-1258.