41 resultados para Programmes d’aide
Resumo:
Evaluation of antiretroviral treatment (ART) programmes in sub-Saharan Africa is difficult because many patients are lost to follow-up. Outcomes in these patients are generally unknown but studies tracing patients have shown mortality to be high. We adjusted programme-level mortality in the first year of antiretroviral treatment (ART) for excess mortality in patients lost to follow-up.
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Background Prognostic models have been developed for patients infected with HIV-1 who start combination antiretroviral therapy (ART) in high-income countries, but not for patients in sub-Saharan Africa. We developed two prognostic models to estimate the probability of death in patients starting ART in sub-Saharan Africa. Methods We analysed data for adult patients who started ART in four scale-up programmes in Côte d'Ivoire, South Africa, and Malawi from 2004 to 2007. Patients lost to follow-up in the first year were excluded. We used Weibull survival models to construct two prognostic models: one with CD4 cell count, clinical stage, bodyweight, age, and sex (CD4 count model); and one that replaced CD4 cell count with total lymphocyte count and severity of anaemia (total lymphocyte and haemoglobin model), because CD4 cell count is not routinely measured in many African ART programmes. Death from all causes in the first year of ART was the primary outcome. Findings 912 (8·2%) of 11 153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10 331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (≥200 cells per μL vs <25; adjusted hazard ratio 0·21, 95% CI 0·17–0·27), WHO clinical stage (stages III–IV vs I–II; 3·45, 2·43–4·90), bodyweight (≥60 kg vs <45 kg; 0·23, 0·18–0·30), and anaemia status (none vs severe: 0·27, 0·20–0·36). Other independent risk factors for mortality were low total lymphocyte count, advanced age, and male sex. Probability of death at 1 year ranged from 0·9% (95% CI 0·6–1·4) to 52·5% (43·8–61·7) with the CD4 model, and from 0·9% (0·5–1·4) to 59·6% (48·2–71·4) with the total lymphocyte and haemoglobin model. Both models accurately predict early mortality in patients starting ART in sub-Saharan Africa compared with observed data. Interpretation Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa.
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Expanded access to antiretroviral therapy (ART) offers opportunities to strengthen HIV prevention in resource-limited settings. We invited 27 ART programmes from urban settings in Africa, Asia and South America to participate in a survey, with the aim to examine what preventive services had been integrated in ART programmes. Twenty-two programmes participated; eight (36%) from South Africa, two from Brazil, two from Zambia and one each from Argentina, India, Thailand, Botswana, Ivory Coast, Malawi, Morocco, Uganda and Zimbabwe and one occupational programme of a brewery company included five countries (Nigeria, Republic of Congo, Democratic Republic of Congo, Rwanda and Burundi). Twenty-one sites (96%) provided health education and social support, and 18 (82%) provided HIV testing and counselling. All sites encouraged disclosure of HIV infection to spouses and partners, but only 11 (50%) had a protocol for partner notification. Twenty-one sites (96%) supplied male condoms, seven (32%) female condoms and 20 (91%) provided prophylactic ART for the prevention of mother-to child transmission. Seven sites (33%) regularly screened for sexually transmitted infections (STI). Twelve sites (55%) were involved in activities aimed at women or adolescents, and 10 sites (46%) in activities aimed at serodiscordant couples. Stigma and discrimination, gender roles and funding constraints were perceived as the main obstacles to effective prevention in ART programmes. We conclude that preventive services in ART programmes in lower income countries focus on health education and the provision of social support and male condoms. Strategies that might be equally or more important in this setting, including partner notification, prompt diagnosis and treatment of STI and reduction of stigma in the community, have not been implemented widely.
Resumo:
To assess the impact of screening programmes in reducing the prevalence of Chlamydia trachomatis, mathematical and computational models are used as a guideline for decision support. Unfortunately, large uncertainties exist about the parameters that determine the transmission dynamics of C. trachomatis. Here, we use a SEIRS (susceptible-exposed-infected-recovered-susceptible) model to critically analyze the turnover of C. trachomatis in a population and the impact of a screening programme. We perform a sensitivity analysis on the most important steps during an infection with C. trachomatis. Varying the fraction of the infections becoming symptomatic as well as the duration of the symptomatic period within the range of previously used parameter estimates has little effect on the transmission dynamics. However, uncertainties in the duration of temporary immunity and the asymptomatic period can result in large differences in the predicted impact of a screening programme. We therefore analyze previously published data on the persistence of asymptomatic C. trachomatis infection in women and estimate the mean duration of the asymptomatic period to be longer than anticipated so far, namely 433 days (95% CI: 420-447 days). Our study shows that a longer duration of the asymptomatic period results in a more pronounced impact of a screening programme. However, due to the slower turnover of the infection, a substantial reduction in prevalence can only be achieved after screening for several years or decades.
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BACKGROUND: Tuberculosis (TB) is a common diagnosis in human immunodeficiency virus (HIV) infected patients on antiretroviral treatment (ART). OBJECTIVE: To describe TB-related practices in ART programmes in lower-income countries and identify risk factors for TB in the first year of ART. METHODS: Programme characteristics were assessed using standardised electronic questionnaire. Patient data from 2003 to 2008 were analysed and incidence rate ratios (IRRs) calculated using Poisson regression models. RESULTS: Fifteen ART programmes in 12 countries in Africa, South America and Asia were included. Chest X-ray, sputum microscopy and culture were available free of charge in respectively 13 (86.7%), 14 (93.3%) and eight (53.3%) programmes. Eight sites (53.3%) used directly observed treatment and five (33.3%) routinely administered isoniazid preventive treatment (IPT). A total of 19 413 patients aged ≥16 years contributed 13 227 person-years of follow-up; 1081 new TB events were diagnosed. Risk factors included CD4 cell count (>350 cells/μl vs. <25 cells/μl, adjusted IRR 0.46, 95%CI 0.33–0.64, P < 0.0001), sex (women vs. men, adjusted IRR 0.77, 95%CI 0.68–0.88, P = 0.0001) and use of IPT (IRR 0.24, 95%CI 0.19–0.31, P < 0.0001). CONCLUSIONS: Diagnostic capacity and practices vary widely across ART programmes. IPT prevented TB, but was used in few programmes. More efforts are needed to reduce the burden of TB in HIV co-infected patients in lower income countries.
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Background The World Health Organization estimates that in sub-Saharan Africa about 4 million HIV-infected patients had started antiretroviral therapy (ART) by the end of 2008. Loss of patients to follow-up and care is an important problem for treatment programmes in this region. As mortality is high in these patients compared to patients remaining in care, ART programmes with high rates of loss to follow-up may substantially underestimate mortality of all patients starting ART. Methods and Findings We developed a nomogram to correct mortality estimates for loss to follow-up, based on the fact that mortality of all patients starting ART in a treatment programme is a weighted average of mortality among patients lost to follow-up and patients remaining in care. The nomogram gives a correction factor based on the percentage of patients lost to follow-up at a given point in time, and the estimated ratio of mortality between patients lost and not lost to follow-up. The mortality observed among patients retained in care is then multiplied by the correction factor to obtain an estimate of programme-level mortality that takes all deaths into account. A web calculator directly calculates the corrected, programme-level mortality with 95% confidence intervals (CIs). We applied the method to 11 ART programmes in sub-Saharan Africa. Patients retained in care had a mortality at 1 year of 1.4% to 12.0%; loss to follow-up ranged from 2.8% to 28.7%; and the correction factor from 1.2 to 8.0. The absolute difference between uncorrected and corrected mortality at 1 year ranged from 1.6% to 9.8%, and was above 5% in four programmes. The largest difference in mortality was in a programme with 28.7% of patients lost to follow-up at 1 year. Conclusions The amount of bias in mortality estimates can be large in ART programmes with substantial loss to follow-up. Programmes should routinely report mortality among patients retained in care and the proportion of patients lost. A simple nomogram can then be used to estimate mortality among all patients who started ART, for a range of plausible mortality rates among patients lost to follow-up.
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We examined the effect of switching to second-line antiretroviral therapy (ART) on mortality in patients who experienced immunological failure in ART programmes without access to routine viral load monitoring in sub-Saharan Africa.
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Objectives: To compare outcomes of antiretroviral therapy (ART) in South Africa, where viral load monitoring is routine, with those in Malawi and Zambia, where monitoring is based on CD4 cell counts. Methods: We included 18 706 adult patients starting ART in South Africa and 80 937 patients in Zambia or Malawi. We examined CD4 responses in models for repeated measures and the probability of switching to second-line regimens, mortality and loss to follow-up in multistate models, measuring time from 6 months. Results: In South Africa, 9.8% [95% confidence interval (CI) 9.1–10.5] had switched at 3 years, 1.3% (95% CI 0.9–1.6) remained on failing first-line regimens, 9.2% (95% CI 8.5–9.8) were lost to follow-up and 4.3% (95% CI 3.9–4.8) had died. In Malawi and Zambia, more patients were on a failing first-line regimen [3.7% (95% CI 3.6–3.9], fewer patients had switched [2.1% (95% CI 2.0–2.3)] and more patients were lost to follow-up [15.3% (95% CI 15.0–15.6)] or had died [6.3% (95% CI 6.0–6.5)]. Median CD4 cell counts were lower in South Africa at the start of ART (93 vs. 132 cells/μl; P < 0.001) but higher after 3 years (425 vs. 383 cells/μl; P < 0.001). The hazard ratio comparing South Africa with Malawi and Zambia after adjusting for age, sex, first-line regimen and CD4 cell count was 0.58 (0.50–0.66) for death and 0.53 (0.48–0.58) for loss to follow-up. Conclusion: Over 3 years of ART mortality was lower in South Africa than in Malawi or Zambia. The more favourable outcome in South Africa might be explained by viral load monitoring leading to earlier detection of treatment failure, adherence counselling and timelier switching to second-line ART.
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OBJECTIVE: To describe the electronic medical databases used in antiretroviral therapy (ART) programmes in lower-income countries and assess the measures such programmes employ to maintain and improve data quality and reduce the loss of patients to follow-up. METHODS: In 15 countries of Africa, South America and Asia, a survey was conducted from December 2006 to February 2007 on the use of electronic medical record systems in ART programmes. Patients enrolled in the sites at the time of the survey but not seen during the previous 12 months were considered lost to follow-up. The quality of the data was assessed by computing the percentage of missing key variables (age, sex, clinical stage of HIV infection, CD4+ lymphocyte count and year of ART initiation). Associations between site characteristics (such as number of staff members dedicated to data management), measures to reduce loss to follow-up (such as the presence of staff dedicated to tracing patients) and data quality and loss to follow-up were analysed using multivariate logit models. FINDINGS: Twenty-one sites that together provided ART to 50 060 patients were included (median number of patients per site: 1000; interquartile range, IQR: 72-19 320). Eighteen sites (86%) used an electronic database for medical record-keeping; 15 (83%) such sites relied on software intended for personal or small business use. The median percentage of missing data for key variables per site was 10.9% (IQR: 2.0-18.9%) and declined with training in data management (odds ratio, OR: 0.58; 95% confidence interval, CI: 0.37-0.90) and weekly hours spent by a clerk on the database per 100 patients on ART (OR: 0.95; 95% CI: 0.90-0.99). About 10 weekly hours per 100 patients on ART were required to reduce missing data for key variables to below 10%. The median percentage of patients lost to follow-up 1 year after starting ART was 8.5% (IQR: 4.2-19.7%). Strategies to reduce loss to follow-up included outreach teams, community-based organizations and checking death registry data. Implementation of all three strategies substantially reduced losses to follow-up (OR: 0.17; 95% CI: 0.15-0.20). CONCLUSION: The quality of the data collected and the retention of patients in ART treatment programmes are unsatisfactory for many sites involved in the scale-up of ART in resource-limited settings, mainly because of insufficient staff trained to manage data and trace patients lost to follow-up.