a retrospective analysis of the burden of hiv-related admissions and mortality at princess marina...
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A retrospective analysis of the burden of HIV-related admissions and mortality at Princess Marina
Hospital, Gaborone in 2000Dr. Molefi, M
BSc , MBChB , MSc
2008 Stuart Isett(aids.temple)
Background• To date, data detailing the burden of HIV/AIDS in our
health facilities have not been analysed• This is important:-historical benefit-interesting period; pre-HAART; era preceding President F. Mogae ’s call for international help • ‘It is however with regret that I have to say that the
HIV/AIDS pandemic is working against all these painstaking efforts to develop our country. (. . .) We stand at the crossroads of a threat of annihilation of our nation’. F. Mogae’s state of the Nation address, 1999
“A Developmental State in Danger of Collapse”*-basis for comparison with the subsequent yearsChabrol, F.BIOMEDICINE, PUBLIC HEALTH, AND CITIZENSHIP IN THE ADVENT OF ANTIRETROVIRALS IN BOTSWANA .Developing World Bioethics
ObjectiveTo analyse the proportion of HIV-related admissions and HIV-related deaths in 2000 the associated socio-demographic and biologic factors
Methods• Design- A retrospective cross-sectional survey• Setting-PMH records department• Sample- ALL records of patients admitted in 2000• Data collection-carried out by trained data
collectors(6) over 6 weeks in 2014• Data collection tool-Pre-tested-questionnaire: demographic, clinical dataData analysis: STATA 12
Operational case definition
• Cases were identified by documented HIV status and/or using section B20-B24 of the International Classification of Diseases (ICD 10 B20-B24) list of opportunistic infection
European joint DRD/DRID expert meeting, 2013: Estimating HIV/AIDS mortality in Europe
Outcomes• % HIV-related admissions = #HIV-related
admission/Total # of admissions• % HIV-related deaths = #HIV-related deaths/
Total# of deaths• Case Fatality Rate(%) = HIV-related deaths/HIV-
related admissions
• Associated biologic, socio-demograhic factors• Log binomial regression; PR(more interpretable)
instead of OR as more recently used in the literature*
• Dependent variables: (i) HIV-related admission
(ii) HIV-related deathIndependent variables: Age ,sex , SES,CD4 count, ART status, ART beneficiary and regimen
*Barros, A.J., Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio .BMC Med Res Methodol, 2003
Results• 9748 files were analysed• 653(6.7%) files excluded for missing data, mainly
diagnosis• % HIV-related admission: 988/9748≈10%• % HIV-related deaths:291/702≈41.5%• CFR=291/988≈29%
Proportion (%)
Unadjusted Adjusted
Exposure Variables PR 95%CI PR 95%CI
HIV Status: Unknown
9 202(94.4) 2.12 0.87-5.18 1.62 0.37-7.09
Positive
Negative
401(4.12)
1 44(1.48)
27.56
1
11.01-68.97 25.4*
1
8.39-76.90
cART: Yes 1 852(19) 0.59 0.35-0.99 0.34* 0.18-0.64
No 7 896(81) 1 1 -
Sex: Male 2 798(28.7) 1 - 1 -
Female 6 950(71.3)
0.27 0.16-0.44 0.31* 0.16-0.60
Age: 0-14 1 618(16.6) 1 - 1 -
15-39 6 902(70.8) 1.36 1.14-1.64 1.39* 1.17-3.94
>40 1 228(12.6) 1.67 1.36-2.04 1.68* 1.41-6.94
Sub-model A:Socio demographic/economic and biomedical factors independently associated with HIV admissionDependent variable: HIV-related admission (N = 9748)
Sub-Model A Hosmer-Lemeshow test of goodness of fit **P=0.57
Sub-model B:Socio demographic/economic and biomedical factors independently associated with HIV-death Dependent variable: HIV-related death (N = 702)
Sub Model B Hosmer-Lemeshow test of goodness of fit **P=0.41
Proportion (%)
Unadjusted Adjusted
Exposure Variables PR 95%CI PR 95%CI
cART: Yes 252(36) 0.21 0.48-0.93 0.13* 0.03-0.64
No 450(64) 1 - 1 -
Age: 0-14
15-39
>40
207(31)
295(42)
200(27)
1
5.06
1.75
3.33-7.68
1.14-2.70
1
5.62*
1.98*
3.61-8.75
1.26-3.11
Discussion• Vital study showing significant presence(HIV-
related admission)† and severity (CFR)of HIV/AIDS at PMH.
• Implications for resource allocation and planning then
• Majority of those affected were the youth consistent with national figures regionally*
• Marked a time of HIV awareness scale up, therefore most people were not aware of their HIV-status
Urassa, M. Boerma, J et al. The impact of HIV/AIDS on mortality and household mobility in rural Tanzania AIDS ,2001
Age-specific Mortality Rates, HIV, 1995, Zimbabwe
-
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Age group
1995
• HIV sero-positivity and age more than 14 years were highly associated with the risk of HIV-related admission while being female and being on cART were protective against the risk of HIV-related admission.
• The risk of HIV-related death was lower in those on cART and the risk of HIV-related death greatest in the 15-39 year age group consistent with a South African study*
Being on cART at the time was protective against the risk of HIV-related admission and HIV-related death indicating the early benefits of cART before the National Roll-out.
*De Wet et al. Youth mortality due to HIV/AIDS in South Africa, 2001-2009: an analysis of the levels of mortality using life table techniques. Afr J AIDS Res,2014
Merits & Limitations Merits of the study• First kind in-country to attempt to quantify facility-
based (hospital)-burden of HIV/AIDS using primary source of data
• The use of a well accepted Case definition • Justifies the actions leading to large-scale
interventions such as the MASA program and serves as pre-cART comparison
Limitations• Medical records; missing data , varying practices,
often poor quality and eligibility• Most people did not test for HIV
Conclusion• An important cross-sectional study focused on
quantifying HIV- burden in a health facility( main tertiary facility)in 2000. Significant hospital admission and mortality , a good proportion of which were related to HIV. There were significant factors that have been identified to mediate the risk of HIV-related admission and death.
• More recent studies evaluating the burden and associated socio-demograhic and biologic factors in health facilities in the cART era, are needed
Acknowledgements• The Office of Research & Development(UB)• Ministry of Health HRDC • Princess Marina Hospital Management• Princess Marina Hospital Records Department• Ministry of Labor and Home affairs( Births &
Deaths Registry)• Central Statistics Office, Botswana• School of Health Systems & Public Health,
University of Pretoria
• Ever-so dedicated research assistant & Data entry clerks
Status• Accepted at the 7th Middle-East Global Summit on
Vaccine & Vaccinations• Scheduled to be presented on 28th 1040 hrs• International platform to showcase a variety of
research projects such as this• An ideal environment for young researchers & to
network• Sell the good name of the Faculty & UB, Botswana
at large