Dr Molefi M BSc MBChB MSc 2008 Stuart Isett aidstemple Background To date data detailing the burden of HIVAIDS in our health facilities have not been analysed This is important ID: 754850
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Slide1
A retrospective analysis of the burden of HIV-related admissions and mortality at Princess Marina Hospital, Gaborone in 2000
Dr. Molefi, MBSc , MBChB , MSc Slide2
2008 Stuart
Isett
(
aids.temple
)
Slide3
Background
To date, data detailing the burden of HIV/AIDS in our health facilities have not been analysedThis 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 years
Chabrol
, F.BIOMEDICINE
, PUBLIC HEALTH, AND CITIZENSHIP IN THE ADVENT
OF ANTIRETROVIRALS
IN
BOTSWANA .
Developing World BioethicsSlide4
Objective
To analyse the proportion of HIV-related admissions and HIV-related deaths in 2000 the associated socio-demographic
and biologic factorsSlide5
Methods
Design- A retrospective cross-sectional surveySetting-PMH records departmentSample- ALL records of patients admitted in 2000Data collection-carried out by trained data collectors(6) over 6 weeks in 2014
Data collection tool
-Pre-tested
-questionnaire:
demographic, clinical dataData analysis: STATA 12Slide6
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 EuropeSlide7
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 admissionsSlide8
Associated biologic, socio-
demograhic factorsLog binomial regression; PR(more interpretable) instead of OR as more recently used in the literature*Dependent variables:
(i) HIV-related admission
(ii) HIV-related death
Independent 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, 2003Slide9
Results
9748 files were analysed653(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%Slide10
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: Yes1 852(19)0.590.35-0.990.34*0.18-0.64 No7 896(81)1 1-Sex: Male2 798(28.7)1-1- Female 6 950(71.3)0.270.16-0.440.31*0.16-0.60Age: 0-141 618(16.6)1-1- 15-396 902(70.8)1.361.14-1.641.39*1.17-3.94 >401 228(12.6)1.671.36-2.041.68*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=0.57Slide11
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
P
R
95%CI
P
R
95%CI
cART: Yes
252(36)
0.21
0.48-0.93
0.13*
0.03-0.64
No450(64)1-1-Age: 0-14 15-39 >40
207(31) 295(42)200(27)15.061.75
3.33-7.68
1.14-2.70
1
5.62
*
1.98*
3.61-8.75
1.26-3.11Slide12
Discussion
Vital study showing significant presence(HIV-related admission)† and severity (CFR)of HIV/AIDS at PMH.Implications for resource allocation and planning thenMajority 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 ,2001Slide13
Age-specific Mortality Rates, HIV, 1995, ZimbabweSlide14
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,2014Slide15
Merits & Limitations
Merits of the studyFirst kind in-country to attempt to quantify facility-based (hospital)-burden of HIV/AIDS using primary source of dataThe 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
LimitationsMedical records; missing data , varying practices, often poor quality and eligibilityMost people did not test for HIVSlide16
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 neededSlide17
Acknowledgements
The Office of Research & Development(UB)Ministry of Health HRDC Princess Marina Hospital ManagementPrincess 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 PretoriaSlide18
Ever-so dedicated research assistant & Data entry clerksSlide19
Status
Accepted at the 7th Middle-East Global Summit on Vaccine & VaccinationsScheduled 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 networkSell the good name of the Faculty & UB, Botswana at large