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  1. Kanapathipillai R, McManus H, Kamarulzaman A, Lim PL, Templeton DJ, Law M, et al.
    PLoS One, 2014;9(2):e86122.
    PMID: 24516527 DOI: 10.1371/journal.pone.0086122
    INTRODUCTION: Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).

    METHODS: Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.

    RESULTS: 5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.

    CONCLUSION: Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.

  2. Jung IY, Rupasinghe D, Woolley I, O'Connor CC, Giles M, Azwa RI, et al.
    J Int AIDS Soc, 2019 Jan;22(1):e25219.
    PMID: 30615271 DOI: 10.1002/jia2.25219
    INTRODUCTION: AIDS-related deaths in people living with HIV/AIDS have been decreasing in number since the introduction of combination antiretroviral treatment (cART). However, data on recent causes of death in the Asia-Pacific region are limited. Hence, we analysed and compared AIDS-related and non-AIDS-related mortality in high- and low-income settings in the region.

    METHODS: Patients from the TREAT Asia HIV Observational Database (TAHOD) and Australian HIV Observational Database (AHOD) receiving cART between 1999 and 2017 were included. Causes of death verification were based on review of the standardized Cause of Death (CoDe) form designed by the D:A:D group. Cohorts were grouped as AHOD (all high-income sites), TAHOD-high (high/upper-middle income countries) and TAHOD-low (lower-middle income countries). TAHOD sites were split into high/upper-middle income and lower-middle income country settings based on World Bank classifications. Competing risk regression was used to analyse factors associated with AIDS and non-AIDS-related mortality.

    RESULTS: Of 10,386 patients, 522 died; 187 from AIDS-related and 335 from non-AIDS-related causes. The overall incidence rate of deaths during follow-up was 0.28 per 100 person-years (/100 PYS) for AIDS and 0.51/100 PYS for non-AIDS. Analysis indicated that the incidence rate of non-AIDS mortality decreased from 0.78/100 PYS to 0.37/100 PYS from year groups 2003 to 2007 to 2013 to 2017 (p 

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