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