960 resultados para LIMITED-RESOURCE COUNTRIES
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Background Changes in CD4 cell counts are poorly documented in individuals with low or moderate-level viremia while on antiretroviral treatment (ART) in resource-limited settings. We assessed the impact of on-going HIV-RNA replication on CD4 cell count slopes in patients treated with a first-line combination ART. Method Naïve patients on a first-line ART regimen with at least two measures of HIV-RNA available after ART initiation were included in the study. The relationships between mean CD4 cell count change and HIV-RNA at 6 and 12 months after ART initiation (M6 and M12) were assessed by linear mixed models adjusted for gender, age, clinical stage and year of starting ART. Results 3,338 patients were included (14 cohorts, 64% female) and the group had the following characteristics: a median follow-up time of 1.6 years, a median age of 34 years, and a median CD4 cell count at ART initiation of 107 cells/μL. All patients with suppressed HIV-RNA at M12 had a continuous increase in CD4 cell count up to 18 months after treatment initiation. By contrast, any degree of HIV-RNA replication both at M6 and M12 was associated with a flat or a decreasing CD4 cell count slope. Multivariable analysis using HIV-RNA thresholds of 10,000 and 5,000 copies confirmed the significant effect of HIV-RNA on CD4 cell counts both at M6 and M12. Conclusion In routinely monitored patients on an NNRTI-based first-line ART, on-going low-level HIV-RNA replication was associated with a poor immune outcome in patients who had detectable levels of the virus after one year of ART.
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OBJECTIVE: To analyse the early loss of patients to antiretroviral therapy (ART) programmes in resource-limited settings. METHODS: Using data on 5491 adult patients starting ART (median age 35 years, 46% female) in 15 treatment programmes in Africa, Asia and South America with (3) 12 months of follow-up, we investigated risk factors for no follow-up after treatment initiation, and loss to follow-up or death in the first 6 months. FINDINGS: Overall, 211 patients (3.8%) had no follow-up, 880 (16.0%) were lost to follow-up and 141 (2.6%) were known to have died in the first 6 months. The probability of no follow-up was higher in 2003-2004 than in 2000 or earlier (odds ratio, OR: 5.06; 95% confidence interval, CI: 1.28-20.0), as was loss to follow-up (hazard ratio, HR: 7.62; 95% CI: 4.55-12.8) but not recorded death (HR: 1.02; 95% CI: 0.44-2.36). Compared with a baseline CD4-cell count (3) 50 cells/microl, a count < 25 cells/microl was associated with a higher probability of no follow-up (OR: 2.49; 95% CI: 1.43-4.33), loss to follow-up (HR: 1.48; 95% CI: 1.23-1.77) and death (HR: 3.34; 95% CI: 2.10-5.30). Compared to free treatment, fee-for-service programmes were associated with a higher probability of no follow-up (OR: 3.71; 95% CI: 0.97-16.05) and higher mortality (HR: 4.64; 95% CI: 1.11-19.41). CONCLUSION: Early patient losses were increasingly common when programmes were scaled up and were associated with a fee for service and advanced immunodeficiency at baseline. Measures to maximize ART programme retention are required in resource-poor countries.
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BACKGROUND: Few data are available on the long-term immunologic response to antiretroviral therapy (ART) in resource-limited settings, where ART is being rapidly scaled up using a public health approach, with a limited repertoire of drugs. OBJECTIVES: To describe immunologic response to ART among ART patients in a network of cohorts from sub-Saharan Africa, Latin America, and Asia. STUDY POPULATION/METHODS: Treatment-naive patients aged 15 and older from 27 treatment programs were eligible. Multilevel, linear mixed models were used to assess associations between predictor variables and CD4 cell count trajectories following ART initiation. RESULTS: Of 29 175 patients initiating ART, 8933 (31%) were excluded due to insufficient follow-up time and early lost to follow-up or death. The remaining 19 967 patients contributed 39 200 person-years on ART and 71 067 CD4 cell count measurements. The median baseline CD4 cell count was 114 cells/microl, with 35% having less than 100 cells/microl. Substantial intersite variation in baseline CD4 cell count was observed (range 61-181 cells/microl). Women had higher median baseline CD4 cell counts than men (121 vs. 104 cells/microl). The median CD4 cell count increased from 114 cells/microl at ART initiation to 230 [interquartile range (IQR) 144-338] at 6 months, 263 (IQR 175-376) at 1 year, 336 (IQR 224-472) at 2 years, 372 (IQR 242-537) at 3 years, 377 (IQR 221-561) at 4 years, and 395 (IQR 240-592) at 5 years. In multivariable models, baseline CD4 cell count was the most important determinant of subsequent CD4 cell count trajectories. CONCLUSION: These data demonstrate robust and sustained CD4 response to ART among patients remaining on therapy. Public health and programmatic interventions leading to earlier HIV diagnosis and initiation of ART could substantially improve patient outcomes in resource-limited settings.
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BACKGROUND: The retention of patients in antiretroviral therapy (ART) programmes is an important issue in resource-limited settings. Loss to follow up can be substantial, but it is unclear what the outcomes are in patients who are lost to programmes. METHODS AND FINDINGS: We searched the PubMed, EMBASE, Latin American and Caribbean Health Sciences Literature (LILACS), Indian Medlars Centre (IndMed) and African Index Medicus (AIM) databases and the abstracts of three conferences for studies that traced patients lost to follow up to ascertain their vital status. Main outcomes were the proportion of patients traced, the proportion found to be alive and the proportion that had died. Where available, we also examined the reasons why some patients could not be traced, why patients found to be alive did not return to the clinic, and the causes of death. We combined mortality data from several studies using random-effects meta-analysis. Seventeen studies were eligible. All were from sub-Saharan Africa, except one study from India, and none were conducted in children. A total of 6420 patients (range 44 to 1343 patients) were included. Patients were traced using telephone calls, home visits and through social networks. Overall the vital status of 4021 patients could be ascertained (63%, range across studies: 45% to 86%); 1602 patients had died. The combined mortality was 40% (95% confidence interval 33%-48%), with substantial heterogeneity between studies (P<0.0001). Mortality in African programmes ranged from 12% to 87% of patients lost to follow-up. Mortality was inversely associated with the rate of loss to follow up in the programme: it declined from around 60% to 20% as the percentage of patients lost to the programme increased from 5% to 50%. Among patients not found, telephone numbers and addresses were frequently incorrect or missing. Common reasons for not returning to the clinic were transfer to another programme, financial problems and improving or deteriorating health. Causes of death were available for 47 deaths: 29 (62%) died of an AIDS defining illness. CONCLUSIONS: In ART programmes in resource-limited settings a substantial minority of adults lost to follow up cannot be traced, and among those traced 20% to 60% had died. Our findings have implications both for patient care and the monitoring and evaluation of programmes.
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BACKGROUND Monitoring of HIV viral load in patients on combination antiretroviral therapy (ART) is not generally available in resource-limited settings. We examined the cost-effectiveness of qualitative point-of-care viral load tests (POC-VL) in sub-Saharan Africa. DESIGN Mathematical model based on longitudinal data from the Gugulethu and Khayelitsha township ART programmes in Cape Town, South Africa. METHODS Cohorts of patients on ART monitored by POC-VL, CD4 cell count or clinically were simulated. Scenario A considered the more accurate detection of treatment failure with POC-VL only, and scenario B also considered the effect on HIV transmission. Scenario C further assumed that the risk of virologic failure is halved with POC-VL due to improved adherence. We estimated the change in costs per quality-adjusted life-year gained (incremental cost-effectiveness ratios, ICERs) of POC-VL compared with CD4 and clinical monitoring. RESULTS POC-VL tests with detection limits less than 1000 copies/ml increased costs due to unnecessary switches to second-line ART, without improving survival. Assuming POC-VL unit costs between US$5 and US$20 and detection limits between 1000 and 10,000 copies/ml, the ICER of POC-VL was US$4010-US$9230 compared with clinical and US$5960-US$25540 compared with CD4 cell count monitoring. In Scenario B, the corresponding ICERs were US$2450-US$5830 and US$2230-US$10380. In Scenario C, the ICER ranged between US$960 and US$2500 compared with clinical monitoring and between cost-saving and US$2460 compared with CD4 monitoring. CONCLUSION The cost-effectiveness of POC-VL for monitoring ART is improved by a higher detection limit, by taking the reduction in new HIV infections into account and assuming that failure of first-line ART is reduced due to targeted adherence counselling.
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BACKGROUND The cost-effectiveness of routine viral load (VL) monitoring of HIV-infected patients on antiretroviral therapy (ART) depends on various factors that differ between settings and across time. Low-cost point-of-care (POC) tests for VL are in development and may make routine VL monitoring affordable in resource-limited settings. We developed a software tool to study the cost-effectiveness of switching to second-line ART with different monitoring strategies, and focused on POC-VL monitoring. METHODS We used a mathematical model to simulate cohorts of patients from start of ART until death. We modeled 13 strategies (no 2nd-line, clinical, CD4 (with or without targeted VL), POC-VL, and laboratory-based VL monitoring, with different frequencies). We included a scenario with identical failure rates across strategies, and one in which routine VL monitoring reduces the risk of failure. We compared lifetime costs and averted disability-adjusted life-years (DALYs). We calculated incremental cost-effectiveness ratios (ICER). We developed an Excel tool to update the results of the model for varying unit costs and cohort characteristics, and conducted several sensitivity analyses varying the input costs. RESULTS Introducing 2nd-line ART had an ICER of US$1651-1766/DALY averted. Compared with clinical monitoring, the ICER of CD4 monitoring was US$1896-US$5488/DALY averted and VL monitoring US$951-US$5813/DALY averted. We found no difference between POC- and laboratory-based VL monitoring, except for the highest measurement frequency (every 6 months), where laboratory-based testing was more effective. Targeted VL monitoring was on the cost-effectiveness frontier only if the difference between 1st- and 2nd-line costs remained large, and if we assumed that routine VL monitoring does not prevent failure. CONCLUSION Compared with the less expensive strategies, the cost-effectiveness of routine VL monitoring essentially depends on the cost of 2nd-line ART. Our Excel tool is useful for determining optimal monitoring strategies for specific settings, with specific sex-and age-distributions and unit costs.
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BACKGROUND HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing. METHODS We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20% or 40% of patients in seven cohorts of patients starting ART in South Africa, and plotted cut-offs for VL testing on colour-coded risk charts. We assessed the accuracy of risk chart-guided VL testing to detect virologic failure in validation cohorts from South Africa, Zambia and the Asia-Pacific. FINDINGS 31,450 adult patients were included in the derivation and 25,294 patients in the validation cohorts. Positive predictive values increased with the percentage of patients tested: from 79% (10% tested) to 98% (40% tested) in the South African, from 64% to 93% in the Zambian and from 73% to 96% in the Asia-Pacific cohorts. Corresponding increases in sensitivity were from 35% to 68% in South Africa, from 55% to 82% in Zambia and from 37% to 71% in Asia-Pacific. The area under the receiver-operating curve increased from 0.75 to 0.91 in South Africa, from 0.76 to 0.91 in Zambia and from 0.77 to 0.92 in Asia Pacific. INTERPRETATION CD4-based risk charts with optimal cut-offs for targeted VL testing may be useful to monitor ART in settings where VL capacity is limited.
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BACKGROUND HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing. METHODS We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20%, or 40% of patients in 7 cohorts of patients starting ART in South Africa, and plotted cutoffs for VL testing on colour-coded risk charts. We assessed the accuracy of risk chart-guided VL testing to detect virologic failure in validation cohorts from South Africa, Zambia, and the Asia-Pacific. RESULTS In total, 31,450 adult patients were included in the derivation and 25,294 patients in the validation cohorts. Positive predictive values increased with the percentage of patients tested: from 79% (10% tested) to 98% (40% tested) in the South African cohort, from 64% to 93% in the Zambian cohort, and from 73% to 96% in the Asia-Pacific cohort. Corresponding increases in sensitivity were from 35% to 68% in South Africa, from 55% to 82% in Zambia, and from 37% to 71% in Asia-Pacific. The area under the receiver operating curve increased from 0.75 to 0.91 in South Africa, from 0.76 to 0.91 in Zambia, and from 0.77 to 0.92 in Asia-Pacific. CONCLUSIONS CD4-based risk charts with optimal cutoffs for targeted VL testing maybe useful to monitor ART in settings where VL capacity is limited.
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BACKGROUND Viral load and CD4% are often not available in resource-limited settings for monitoring children's responses to antiretroviral therapy (ART). We aimed to construct normative curves for weight gain at 6, 12, 18, and 24 months following initiation of ART in children, and to assess the association between poor weight gain and subsequent responses to ART. DESIGN Analysis of data from HIV-infected children younger than 10 years old from African and Asian clinics participating in the International epidemiologic Databases to Evaluate AIDS. METHODS The generalized additive model for location, scale, and shape was used to construct normative percentile curves for weight gain at 6, 12, 18, and 24 months following ART initiation. Cox proportional models were used to assess the association between lower percentiles (< 50th) of weight gain distribution at the different time points and subsequent death, virological suppression, and virological failure. RESULTS Among 7173 children from five regions of the world, 45% were underweight at baseline. Weight gain below the 50th percentile at 6, 12, 18, and 24 months of ART was associated with increased risk of death, independent of baseline characteristics. Poor weight gain was not associated with increased hazards of virological suppression or virological failure. CONCLUSION Monitoring weight gain on ART using age-specific and sex-specific normative curves specifically developed for HIV-infected children on ART is a simple, rapid, sustainable tool that can aid in the identification of children who are at increased risk of death in the first year of ART.
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Background. According to the WHO 2007 country report, Haiti lags behind the Millennium Development Goal of reducing child mortality and maintains the highest under-5 mortality rate in the Western hemisphere. 3 Overall, few studies exist that seek to better grasp barriers in caring for a seriously ill child in a resource-limited setting and only a handful propose sustainable, effective interventions. ^ Objectives. The objectives of this study are to describe the prevalence of serious illnesses among children hospitalized at 2 children's hospitals in Port au Prince, to determine the barriers faced when caring for seriously ill children, and to report hospital outcomes of children admitted with serious illnesses. ^ Methods. Data were gathered from 2 major children's hospitals in Port au Prince, Haiti (Grace Children's Hospital [GCH] and Hopital d l'Universite d'Etat d'Haiti [HUEH]) using a triangulated approach of focus group discussions, physician questionnaires, and retrospective chart review. 23 pediatric physicians participated in focus group discussions and completed a self-administered questionnaire evaluating healthcare provider knowledge, self-efficacy, and perceived barriers relating to the care of seriously ill children in a resource-limited setting. A sample of 240 patient charts meeting eligibility criteria was abstracted for pertinent elements including sociodemographics, documentation, treatment strategies, and outcomes. Factors associated with mortality were analyzed using χ2 test and Fisher exact test [Minitab v.15]. ^ Results. The most common primary diagnoses at admission were gastroenteritis with moderate dehydration (35.5%), severe malnutrition (25.8%), and pneumonia (19.3%) for GCH, and severe malnutrition (32.6%), sepsis (24.7%), and severe respiratory distress (18%) for HUEH. Overall, 12.9% and 27% of seriously ill patients presented with shock to GCH and HUEH, respectively. ^ Shortage of necessary materials and equipment represented the most commonly reported limitation (18/23 respondents). According to chart data, 9.4% of children presenting with shock did not receive a fluid bolus, and only 8% of patients presenting with altered mental status or seizures received a glucose check. 65% of patients with meningitis did not receive a lumbar puncture due to lack of materials. ^ Hospital mortality rates did not differ by gender or by institution. Children who died were more likely to have a history of prematurity (OR 4.97 [95% CI 1.32-18.80]), an incomplete vaccination record (OR 4.05 [95% CI 1.68-9.74]), or a weight for age ≤3rd percentile (OR 6.1 [95% CI 2.49-14.93]. Case-fatality rates were significantly higher among those who presented with signs of shock compared with those who did not (23.1% vs. 10.7%, RR=2.16, p=0.03). Caregivers did not achieve shock reversal in 21% of patients and did not document shock reversal in 50% of patients. ^ Conclusions. Many challenges face those who seek to optimize care for seriously ill children in resource-limited settings. Specifically, in Haiti, qualitative and quantitative data suggest major issues with lack of supplies, pre-hospital factors, including malnutrition as a comorbidity, and early recognition and management of shock. A tailored intervention designed to address these issues is needed in order to prospectively evaluate improvements in child mortality in a high-risk population.^
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The structure of the atmospheric boundary layer (ABL) is modelled with the limited- length-scale k-ε model of Apsley and Castro. Contrary to the standard k-ε model, the limited-length-scale k-ε model imposes a maximum mixing length which is derived from the boundary layer height, for neutral and unstable atmospheric situations, or by Monin-Obukhov length when the atmosphere is stably stratified. The model is first verified reproducing the famous Leipzig wind profile. Then the performance of the model is tested with measurements from FINO-1 platform using sonic anemometers to derive the appropriate maximum mixing length.
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This Working Document provides an estimate of China’s impact on the growth rate of resource-rich countries since its WTO accession in December 2001. The authors’ empirical approach follows the logic of the differences-in-differences estimator. In addition to temporal variation arising from the WTO accession, which they argue was exogenous to other countries’ growth trajectories, the authors exploit spatial variation arising from differences in natural resource wealth. In this way they can compare changes in economic growth in the pre- and post-accession periods between countries that benefited from the surge in demand for industrial commodities brought about by China’s WTO accession and countries that were less able to do so. They find that that roughly one-tenth of the average annual post-accession growth in resource-rich countries was due to China’s increased appetite for commodities. The authors use this finding to inform the debate about what will happen to economic growth in resource-rich countries as China rebalances and its demand for commodities weakens.
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Despite the public perception in many member states that labour mobility has spiralled out of control, intra-EU migration remains low, particularly within the euro area. The limits to the potential of labour mobility became evident during the economic crisis as high unemployment rates in the periphery have only caused limited mobility from crisis countries. Hence, the bulk of labour mobility still flows from east to west but ten years after the eastern enlargement the number of East Europeans living in EU15 should be of no overall concern. In view of the lessons learned from the crisis, the Commission and member states should improve existing tools for cross-border job matching and adopt a longer-term view on labour mobility.