909 resultados para CD4 cell count


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Objectives: We assessed mortality associated with immunologic and virologic patterns of response at 6 months of highly active antiretroviral therapy (HAART) in HIV-infected individuals from resource-limited countries in Africa and South America. Methods: Patients who initiated HAART between 1996 and 2007, aged 16 years or older, and had at least 1 measurement (HIV-1 RNA plasma viral load or CD4 cell count) at 6 months of therapy (3-9 month window) were included. Therapy response was categorized as complete, discordant (virologic only or immunologic only), and absent. Associations between 6-month response to therapy and all-cause mortality were assessed by Cox proportional hazards regression. Robust standard errors were calculated to account for intrasite correlation. Results: A total of 7160 patients, corresponding to 15,107 person-years, were analyzed. In multivariable analysis adjusted for age at HAART initiation, baseline clinical stage and CD4 cell count, year of HAART initiation, clinic, occurrence of an AIDS-defining condition within the first 6 months of treatment, and discordant and absent responses were associated with increased risk of death. Conclusions: Similar to reports from high-income countries, discordant immunologic and virologic responses were associated with intermediate risk of death compared with complete and no response in this large cohort of HIV-1 patients from resource-limited countries. Our results support a recommendation for wider availability of plasma viral load testing to monitor antiretroviral therapy in these settings.

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Objectiveâ To assess the outcome of patients who experienced treatment failure with antiretrovirals in sub-Saharan Africa. Methodsâ Analysis of 11 antiretroviral therapy (ART) programmes in sub-Saharan Africa. World Health Organization (WHO) criteria were used to define treatment failure. All ART-naive patients aged â¥16 who started with a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen and had at least 6 months of follow-up were eligible. For each patient who switched to a second-line regimen, 10 matched patients who remained on a non-failing first-line regimen were selected. Time was measured from the time of switching, from the corresponding time in matched patients, or from the time of treatment failure in patients who remained on a failing regimen. Mortality was analysed using KaplanâMeier curves and random-effects Cox models. Resultsâ Of 16 591 adult patients starting ART, 382 patients (2.3%) switched to a second-line regimen. Another 323 patients (1.9%) did not switch despite developing immunological or virological failure. Cumulative mortality at 1 year was 4.2% (95% CI 2.2â7.8%) in patients who switched to a second-line regimen and 11.7% (7.3%â18.5%) in patients who remained on a failing first-line regimen, compared to 2.2% (1.6â3.0%) in patients on a non-failing first-line regimen (P < 0.0001). Differences in mortality were not explained by nadir CD4 cell count, age or differential loss to follow up. Conclusionsâ Many patients who meet criteria for treatment failure do not switch to a second-line regimen and die. There is an urgent need to clarify the reasons why in sub-Saharan Africa many patients remain on failing first-line ART.

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Objective: In South Africa, many HIV-infected patients experience delays in accessing antiretroviral therapy (ART). We examined pretreatment mortality and access to treatment in patients waiting for ART. Design: Cohort of HIV-infected patients assessed for ART eligibility at 36 facilities participating in the Comprehensive HIV and AIDS Management (CHAM) program in the Free State Province. Methods: Proportion of patients initiating ART, pre-ART mortality and risk factors associated with these outcomes were estimated using competing risks survival analysis. Results: Forty-four thousand, eight hundred and forty-four patients enrolled in CHAM between May 2004 and December 2007, of whom 22 083 (49.2%) were eligible for ART; pre-ART mortality was 53.2 per 100 person-years [95% confidence interval (CI) 51.8â54.7]. Median CD4 cell count at eligibility increased from 87 cells/ml in 2004 to 101 cells/ml in 2007. Two years after eligibility an estimated 67.7% (67.1â68.4%) of patients had started ART, and 26.2% (25.6â26.9%) died before starting ART. Among patients with CD4 cell counts below 25 cells/ml at eligibility, 48% died before ART and 51% initiated ART. Men were less likely to start treatment and more likely to die than women. Patients in rural clinics or clinics with low staffing levels had lower rates of starting treatment and higher mortality compared with patients in urban/peri-urban clinics, or better staffed clinics. Conclusions: Mortality is high in eligible patients waiting for ART in the Free State Province. The most immunocompromised patients had the lowest probability of starting ART and the highest risk of pre-ART death. Prioritization of these patients should reduce waiting times and pre-ART mortality.

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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 11âˆ153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10âˆ331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (â¥200 cells per μL vs <25; adjusted hazard ratio 0·21, 95% CI 0·17â0·27), WHO clinical stage (stages IIIâIV vs IâII; 3·45, 2·43â4·90), bodyweight (â¥60 kg vs <45 kg; 0·23, 0·18â0·30), and anaemia status (none vs severe: 0·27, 0·20â0·36). 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 0·6â1·4) to 52·5% (43·8â61·7) with the CD4 model, and from 0·9% (0·5â1·4) to 59·6% (48·2â71·4) 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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When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

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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 19â413 patients aged â¥16 years contributed 13â227 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 0.33â0.64, P < 0.0001), sex (women vs. men, adjusted IRR 0.77, 95%CI 0.68â0.88, P = 0.0001) and use of IPT (IRR 0.24, 95%CI 0.19â0.31, 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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In low-income settings, treatment failure is often identified using CD4 cell count monitoring. Consequently, patients remain on a failing regimen, resulting in a higher risk of transmission. We investigated the benefit of routine viral load monitoring for reducing HIV transmission.

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Background Loss to follow-up (LTFU) is common in antiretroviral therapy (ART) programmes. Mortality is a competing risk (CR) for LTFU; however, it is often overlooked in cohort analyses. We examined how the CR of death affected LTFU estimates in Zambia and Switzerland. Methods and Findings HIV-infected patients aged â¥18 years who started ART 2004â2008 in observational cohorts in Zambia and Switzerland were included. We compared standard Kaplan-Meier curves with CR cumulative incidence. We calculated hazard ratios for LTFU across CD4 cell count strata using cause-specific Cox models, or Fine and Gray subdistribution models, adjusting for age, gender, body mass index and clinical stage. 89,339 patients from Zambia and 1,860 patients from Switzerland were included. 12,237 patients (13.7%) in Zambia and 129 patients (6.9%) in Switzerland were LTFU and 8,498 (9.5%) and 29 patients (1.6%), respectively, died. In Zambia, the probability of LTFU was overestimated in Kaplan-Meier curves: estimates at 3.5 years were 29.3% for patients starting ART with CD4 cells <100 cells/µl and 15.4% among patients starting with â¥350 cells/µL. The estimates from CR cumulative incidence were 22.9% and 13.6%, respectively. Little difference was found between naïve and CR analyses in Switzerland since only few patients died. The results from Cox and Fine and Gray models were similar: in Zambia the risk of loss to follow-up and death increased with decreasing CD4 counts at the start of ART, whereas in Switzerland there was a trend in the opposite direction, with patients with higher CD4 cell counts more likely to be lost to follow-up. Conclusions In ART programmes in low-income settings the competing risk of death can substantially bias standard analyses of LTFU. The CD4 cell count and other prognostic factors may be differentially associated with LTFU in low-income and high-income settings.

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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 18âŠ706 adult patients starting ART in South Africa and 80âŠ937 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) 9.1â10.5] had switched at 3 years, 1.3% (95% CI 0.9â1.6) remained on failing first-line regimens, 9.2% (95% CI 8.5â9.8) were lost to follow-up and 4.3% (95% CI 3.9â4.8) had died. In Malawi and Zambia, more patients were on a failing first-line regimen [3.7% (95% CI 3.6â3.9], fewer patients had switched [2.1% (95% CI 2.0â2.3)] and more patients were lost to follow-up [15.3% (95% CI 15.0â15.6)] or had died [6.3% (95% CI 6.0â6.5)]. Median CD4 cell counts were lower in South Africa at the start of ART (93 vs. 132âŠcells/μl; PâŠ<âŠ0.001) but higher after 3 years (425 vs. 383âŠcells/μl; PâŠ<âŠ0.001). 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 (0.50â0.66) for death and 0.53 (0.48â0.58) 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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Background:â Alcohol is heavily consumed in sub-Saharan Africa and affects HIV transmission and treatment and is difficult to measure. Our goal was to examine the test characteristics of a direct metabolite of alcohol consumption, phosphatidylethanol (PEth). Methods:â Persons infected with HIV were recruited from a large HIV clinic in southwestern Uganda. We conducted surveys and breath alcohol concentration (BRAC) testing at 21 daily home or drinking establishment visits, and blood was collected on day 21 (nâƒ=âƒ77). PEth in whole blood was compared with prior 7-, 14-, and 21-day alcohol consumption. Results:â (i) The receiver operator characteristic area under the curve (ROC-AUC) was highest for PEth versus any consumption over the prior 21âƒdays (0.92; 95% confidence interval [CI]: 0.86 to 0.97). The sensitivity for any detectable PEth was 88.0% (95% CI: 76.0 to 95.6) and the specificity was 88.5% (95% CI: 69.8 to 97.6). (ii) The ROC-AUC of PEth versus any 21-day alcohol consumption did not vary with age, body mass index, CD4 cell count, hepatitis B virus infection, and antiretroviral therapy status, but was higher for men compared with women (pâƒ=âƒ0.03). (iii) PEth measurements were correlated with several measures of alcohol consumption, including number of drinking days in the prior 21âƒdays (Spearman râƒ=âƒ0.74, pâƒ<âƒ0.001) and BRAC (râƒ=âƒ0.75, pâƒ<âƒ0.001). Conclusions:â The data add support to the body of evidence for PEth as a useful marker of alcohol consumption with high ROC-AUC, sensitivity, and specificity. Future studies should further address the period and level of alcohol consumption for which PEth is detectable.

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Background Interferon-gamma release assays (IGRA) are more specific than the tuberculin skin test (TST) for the diagnosis of Mycobacterium tuberculosis infection. Data on sensitivity are controversial in HIV infection. Methods IGRA (T-SPOT.TB) was performed using lymphocytes stored within 6 months before culture-confirmed tuberculosis was diagnosed in HIV-infected individuals in the Swiss HIV Cohort Study. Results 64 individuals (69% males, 45% of non-white ethnicity, median age 35 years (interquartile range [IQR] 31-42), 28% with prior AIDS) were analysed. Median CD4 cell count was 223 cells/μl (IQR 103-339), HIV-RNA was 4.7 log10 copies/mL (IQR 4.3-5.2). T-SPOT.TB resulted positive in 25 patients (39%), negative in 18 (28%) and indeterminate in 21 (33%), corresponding to a sensitivity of 39% (95% CI 27-51%) if all test results were considered, and 58% (95% CI 43-74%) if indeterminate results were excluded. Sensitivity of IGRA was independent of CD4 cell count (p = 0.698). Among 44 individuals with available TST, 22 (50%) had a positive TST. Agreement between TST and IGRA was 57% (kappa = 0.14, p = 0.177), and in 34% (10/29) both tests were positive. Combining TST and IGRA (at least one test positive) resulted in an improved sensitivity of 67% (95% CI 52-81%). In multivariate analysis, older age was associated with negative results of TST and T-SPOT.TB (OR 3.07, 95% CI 1,22-7.74, p = 0.017, per 10 years older). Conclusions T-SPOT.TB and TST have similar sensitivity to detect latent TB in HIV-infected individuals. Combining TST and IGRA may help clinicians to better select HIV-infected individuals with latent tuberculosis who qualify for preventive treatment.

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Objectivesâ To assess the proportion of patients lost to programme (died, lost to follow-up, transferred out) between HIV diagnosis and start of antiretroviral therapy (ART) in sub-Saharan Africa, and determine factors associated with loss to programme. Methodsâ Systematic review and meta-analysis. We searched PubMed and EMBASE databases for studies in adults. Outcomes were the percentage of patients dying before starting ART, the percentage lost to follow-up, the percentage with a CD4 cell count, the distribution of first CD4 counts and the percentage of eligible patients starting ART. Data were combined using random-effects meta-analysis. Resultsâ Twenty-nine studies from sub-Saharan Africa including 148âƒ912 patients were analysed. Six studies covered the whole period from HIV diagnosis to ART start. Meta-analysis of these studies showed that of the 100 patients with a positive HIV test, 72 (95% CI 60-84) had a CD4 cell count measured, 40 (95% CI 26-55) were eligible for ART and 25 (95% CI 13-37) started ART. There was substantial heterogeneity between studies (Pâƒ<âƒ0.0001). Median CD4 cell count at presentation ranged from 154 to 274âƒcells/μl. Patients eligible for ART were less likely to become lost to programme (25%vs. 54%, Pâƒ<âƒ0.0001), but eligible patients were more likely to die (11%vs. 5%, Pâƒ<âƒ0.0001) than ineligible patients. Loss to programme was higher in men, in patients with low CD4 cell counts and low socio-economic status and in recent time periods. Conclusionsâ Monitoring and care in the pre-ART time period need improvement, with greater emphasis on patients not yet eligible for ART.

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Background Increased mortality among men on antiretroviral therapy (ART) has been documented but remains poorly understood. We examined the magnitude of and risk factors for gender differences in mortality on ART. Methods and Findings Analyses included 46,201 ART-naïve adults starting ART between January 2002 and December 2009 in eight ART programmes across South Africa (SA). Patients were followed from initiation of ART to outcome or analysis closure. The primary outcome was mortality; secondary outcomes were loss to follow-up (LTF), virologic suppression, and CD4+ cell count responses. Survival analyses were used to examine the hazard of death on ART by gender. Sensitivity analyses were limited to patients who were virologically suppressed and patients whose CD4+ cell count reached >200 cells/µl. We compared gender differences in mortality among HIV+ patients on ART with mortality in an age-standardised HIV-negative population. Among 46,201 adults (65% female, median age 35 years), during 77,578 person-years of follow-up, men had lower median CD4+ cell counts than women (85 versus 110 cells/µl, p<0.001), were more likely to be classified WHO stage III/IV (86 versus 77%, p<0.001), and had higher mortality in crude (8.5 versus 5.7 deaths/100 person-years, p<0.001) and adjusted analyses (adjusted hazard ratio [AHR] 1.31, 95% CI 1.22â1.41). After 36 months on ART, men were more likely than women to be truly LTF (AHR 1.20, 95% CI 1.12â1.28) but not to die after LTF (AHR 1.04, 95% CI 0.86â1.25). Findings were consistent across all eight programmes. Virologic suppression was similar by gender; women had slightly better immunologic responses than men. Notably, the observed gender differences in mortality on ART were smaller than gender differences in age-standardised death rates in the HIV-negative South African population. Over time, non-HIV mortality appeared to account for an increasing proportion of observed mortality. The analysis was limited by missing data on baseline HIV disease characteristics, and we did not observe directly mortality in HIV-negative populations where the participating cohorts were located. Conclusions HIV-infected men have higher mortality on ART than women in South African programmes, but these differences are only partly explained by more advanced HIV disease at the time of ART initiation, differential LTF and subsequent mortality, and differences in responses to treatment. The observed differences in mortality on ART may be best explained by background differences in mortality between men and women in the South African population unrelated to the HIV/AIDS epidemic.

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Background Minor protease inhibitor (PI) mutations often exist as polymorphisms in HIV-1 sequences from treatment-naïve patients. Previous studies showed that their presence impairs the antiretroviral treatment (ART) response. Evaluating these findings in a larger cohort is essential. Methods To study the impact of minor PI mutations on time to viral suppression and time to virological failure, we included patients from the Swiss HIV Cohort Study infected with HIV-1 subtype B who started first-line ART with a PI and two nucleoside reverse transcriptase inhibitors. Cox regression models were performed to compare the outcomes among patients with 0 and â¥1 minor PI mutation. Models were adjusted for baseline HIV-1 RNA, CD4 cell count, sex, transmission category, age, ethnicity, year of ART start, the presence of nucleoside reverse transcriptase inhibitor mutations, and stratified for the administered PIs. Results We included 1199 patients of whom 944 (78.7%) received a boosted PI. Minor PI mutations associated with the administered PI were common: 41.7%, 16.1%, 4.7% and 1.9% had 1, 2, 3 or â¥4 mutations, respectively. The time to viral suppression was similar between patients with 0 (reference) and â¥1 minor PI mutation (multivariable hazard ratio (HR): 1.1 [95% confidence interval (CI): 1.0â1.3], P = .196). The time to virological failure was also similar (multivariable HR:.9 [95% CI:.5â1.6], P = .765). In addition, the impact of each single minor PI mutation was analyzed separately: none was significantly associated with the treatment outcome. Conclusions The presence of minor PI mutations at baseline has no effect on the therapy outcome in HIV infected individuals.

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Aim To analyze alcohol use, clinical data and laboratory parameters that may affect FIB-4, an index for measuring liver fibrosis, in HCV-monoinfected and HCV/HIV-coinfected drug users. Patients and Methods Patients admitted for substance abuse treatment between 1994 and 2006 were studied. Socio-demographic data, alcohol and drug use characteristics and clinical variables were obtained through hospital records. Blood samples for biochemistry, liver function tests, CD4 cell count, and serology of HIV and HCV infection were collected at admission. Multivariate linear regression was used to analyze the predictors of FIB-4 increase. Results A total of 472 (83% M, 17% F) patients were eligible. The median age at admission was 31 years (Interquartile range (IQR) 27â35 years), and the median duration of drug use was 10 years (IQR 5.5â15 years). Unhealthy drinking (>50 grams/day) was reported in 32% of the patients. The FIB-4 scores were significantly greater in the HCV/HIV-coinfected patients (1.14, IQR 0.76â1.87) than in the HCV-monoinfected patients (0.75, IQR 0.56â1.11) (p<0.001). In the multivariate analysis, unhealthy drinking (p = 0.034), lower total cholesterol (p = 0.042), serum albumin (p<0.001), higher GGT (p<0.001) and a longer duration of addiction (p = 0.005) were independently associated with higher FIB-4 scores in the HCV-monoinfected drug users. The effect of unhealthy drinking on FIB-4 scores disappeared in the HCV/HIV-coinfected patients, whereas lower serum albumin (p<0.001), a lower CD4 cell count (p = 0.006), higher total bilirubin (p<0.001) and a longer drug addiction duration (p<0.001) were significantly associated with higher FIB-4 values. Conclusions Unhealthy alcohol use in the HCV-monoinfected patients and HIV-related immunodeficiency in the HCV/HIV-coinfected patients are important risk factors associated with liver fibrosis in the respective populations.