Browsing by Author "Nglazi, Mweete"

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    Open Access
    Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system
    (BioMed Central Ltd, 2010) Nglazi, Mweete; Kaplan, Richard; Wood, Robin; Bekker, Linda-Gail; Lawn, Stephen
    BACKGROUND:High rates of loss to follow-up (LTFU) are undermining rapidly expanding antiretroviral treatment (ART) services in sub-Saharan Africa. The intelligent dispensing of ART (iDART) is an open-source electronic pharmacy system that provides an efficient means of generating lists of patients who have failed to pick-up medication. We determined the duration of pharmacy delay that optimally identified true LTFU. METHODS: We conducted a retrospective cross-sectional study of a community-based ART cohort in Cape Town, South Africa. We used iDART to identify groups of patients known to be still enrolled in the cohort on the 1st of April 2008 that had failed to pick-up medication for periods of [greater than or equal to] 6, [greater than or equal to] 12, [greater than or equal to] 18 and [greater than or equal to] 24 weeks. We defined true LTFU as confirmed failure to pick up medication for 3 months since last attendance. We then assessed short-term and long-term outcomes using a prospectively maintained database and patient records. RESULTS: On the date of the survey, 2548 patients were registered as receiving ART but of these 85 patients (3.3%) were found to be true LTFU. The numbers of individuals (proportion of the cohort) identified by iDART as having failed to collect medication for periods of [greater than or equal to]6, [greater than or equal to]12, [greater than or equal to]18 and [greater than or equal to]24 weeks were 560 (22%), 194 (8%), 117 (5%) and 80 (3%), respectively. The sensitivities of these pharmacy delays for detecting true LTFU were 100%, 100%, 62.4% and 47.1%, respectively. The corresponding specificities were 80.7%, 95.6%, 97.4% and 98.4%. Thus, the optimal delay was [greater than or equal to]12 weeks since last attendance at this clinic (equivalent to 8 weeks since medication ran out). Pharmacy delays were also found to be significantly associated with LTFU and death one year later. CONCLUSIONS: The iDART electronic pharmacy system can be used to detect patients potentially LTFU and who require recall. Using a short a cut-off period was too non-specific for LTFU and would require the tracing of very large numbers of patients. Conversely prolonged delays were too insensitive. Of the periods assessed, a [greater than or equal to]12 weeks delay appeared optimal. This system requires prospective evaluation to further refine its utility.
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    Mobile phone text messaging for promoting adherence to anti-tuberculosis treatment: a systematic review protocol
    (BioMed Central Ltd, 2013) Nglazi, Mweete; Bekker, Linda-Gail; Wood, Robin; Hussey, Gregory D; Wiysonge, Charles S
    BACKGROUND: In 2010, there were approximately 8.8 million incident cases of tuberculosis (TB) worldwide. The treatment of TB is at least six months long and may be complicated by a high pill burden. In addition, TB patients often do not take their medication on schedule simply because they forget. Mobile phone text messaging has the potential to help promote TB treatment adherence. We, therefore, propose to conduct a review of current best evidence for the use of mobile phone text messaging to promote patient adherence to TB treatment. METHODS: This is a systematic review of the literature. We will preferably include randomized controlled trials (RCTs). However, non-randomized studies (NRS) will be considered if there is an inadequate number of RCTs.We will search PubMed, EMBASE, CINAHL, CENTRAL, Science Citation Index, Africa-Wide Information, and WHOLIS electronic databases for eligible studies available by 30 November 2012 regardless of language or publication status. We will also check reference lists for additional studies, identify abstracts from conference proceedings and communicate with authors for any relevant material.At least two authors will independently screen search outputs, select studies, extract data and assess the risk of bias (using separate criteria for RCTs and NRS); resolving discrepancies by discussion and consensus. We will assess clinical heterogeneity by examining the types of participants, interventions and outcomes in each study and pool studies judged to be clinically homogenous. We will also assess statistical heterogeneity using the chi-square test of homogeneity and quantify it using the I-square statistic. If study results are found to be statistically homogeneous (that is heterogeneity P > 0.1), we will pool them using the fixed-effect meta-analysis. Otherwise, we will use random-effects meta-analysis. We will calculate risk ratios and their corresponding 95% confidence intervals for dichotomous outcomes, and mean differences for continuous outcomes. For other outcomes without quantitative data, a descriptive analysis will be used.DISCUSSION:Our results can be used by researchers and policy-makers to help inform them of the efficacy of mobile phone text messaging interventions to promote patient adherence to TB treatment.
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    Treatment outcomes in HIV-infected adolescents attending a community-based antiretroviral therapy clinic in South Africa
    (BioMed Central Ltd, 2012) Nglazi, Mweete; Kranzer, Katharina; Holele, Pearl; Kaplan, Richard; Mark, Daniella; Jaspan, Heather; Lawn, Stephen; Wood, Robin; Bekker, Linda-Gail
    BACKGROUND: Very few data are available on treatment outcomes of adolescents living with HIV infection (whether perinatally acquired or sexually acquired) in sub-Saharan Africa. The present study therefore compared the treatment outcomes in adolescents with those of young adults at a public sector community-based ART programme in Cape Town, South Africa. METHODS: Treatment outcomes of adolescents (9-19 years) were compared with those of young adults (20-28 years), enrolled in a prospective cohort between September 2002 and June 2009. Kaplan-Meier estimates and Cox proportional hazard models were used to assess outcomes and determine associations with age, while adjusting for potential confounders. The treatment outcomes were mortality, loss to follow-up (LTFU), immunological response, virological suppression and virological failure. RESULTS: 883 patients, including 65 adolescents (47 perinatally infected and 17 sexually infected) and 818 young adults, received ART. There was no difference in median baseline CD4 cell count between adolescents and young adults (133.5 vs 116 cells/muL; p = 0.31). Overall mortality rates in adolescents and young adults were 1.2 (0.3-4.8) and 3.1 (2.4-3.9) deaths per 100 person-years, respectively. Adolescents had lower rates of virological suppression (< 400 copies/mL) at 48 weeks (27.3% vs 63.1%; p < 0.001). Despite this, however, the median change in CD4 count from baseline at 48 weeks of ART was significantly greater for adolescents than young adults (373 vs 187 cells/muL; p = 0.0001). Treatment failure rates were 8.2 (4.6-14.4) and 5.0 (4.1-6.1) per 100 person-years in the two groups. In multivariate analyses, there was no significant difference in LTFU and mortality between age groups but increased risk in virological failure [AHR 2.06 (95% CI 1.11-3.81; p = 0.002)] in adolescents. CONCLUSIONS: Despite lower virological suppression rates and higher rates of virological failure, immunological responses were nevertheless greater in adolescents than young adults whereas rates of mortality and LTFU were similar. Further studies to determine the reasons for poorer virological outcomes are needed.