116 resultados para Cell counts, microbial

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Background Data on combination antiretroviral therapy (cART) in remote rural African regions is increasing. Methods We assessed prospectively initial cART in HIV-infected adults treated from 2005 to 2008 at St. Francis Designated District Hospital, Ifakara, Tanzania. Adherence was assisted by personal adherence supporters. We estimated risk factors of death or loss to follow-up by Cox regression during the first 12 months of cART. Results Overall, 1,463 individuals initiated cART, which was nevirapine-based in 84.6%. The median age was 40 years (IQR 34-47), 35.4% were males, 7.6% had proven tuberculosis. Median CD4 cell count was 131 cells/μl and 24.8% had WHO stage 4. Median CD4 cell count increased by 61 and 130 cells/μl after 6 and 12 months, respectively. 215 (14.7%) patients modified their treatment, mostly due to toxicity (56%), in particular polyneuropathy and anemia. Overall, 129 patients died (8.8%) and 189 (12.9%) were lost to follow-up. In a multivariate analysis, low CD4 cells at starting cART were associated with poorer survival and loss to follow-up (HR 1.77, 95% CI 1.15-2.75, p = 0.009; for CD4 <50 compared to >100 cells/μl). Higher weight was strongly associated with better survival (HR 0.63, 95% CI 0.51-0.76, p < 0.001 per 10 kg increase). Conclusions cART initiation at higher CD4 cell counts and better general health condition reduces HIV related mortality in a rural African setting. Efforts must be made to promote earlier HIV diagnosis to start cART timely. More research is needed to evaluate effective strategies to follow cART at a peripheral level with limited technical possibilities.

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Low somatic cell count (SCC) is a reliable indicator of high-quality milk free of pathogenic microorganisms. Thus, an important goal in dairy practice is to produce milk with low SCC. Selection for cows with low SCC can sometimes lead to extremely low SCC in single quarters. The cells in milk are, however, predominantly immune cells with important immune functions. To investigate the mammary immune competence of quarters with very low SCC, healthy udder quarters of cows with normal SCC of (40-100) x 10(3) cells/ml and very low SCC of < 20 x 10(3) cells/ml were challenged with lipopolysaccharide (LPS) from Escherichia coli. In the first experiment, SCC and cell viability after a challenge with 50 ng of LPS/quarter was investigated. In the second experiment, tumour necrosis factor alpha (TNF-alpha) concentration and lactate dehydrogenase (LDH) activity in milk, and mRNA expression of various innate immune factors in milk cells were measured after a challenge with 100 mug LPS/quarter. LPS challenge induced an increase of SCC. SCC levels reached were higher in quarters with normal SCC and maximum SCC was reached 1 h earlier than in very low SCC quarters. The increase of TNF-alpha concentrations in milk in response to LPS challenge was lower in quarters with very low SCC than in quarters with normal SCC. The viability of cells and the LDH activity in milk increased in response to LPS challenge, however, without a difference between the groups. The mRNA expression of IL-1beta and IL-8 was increased in milk cells at 12 h after LPS challenge, whereas that of TNF-alpha and lactoferrin was not increased at the measured time points (12, 24 and 36 h after LPS challenge). No differences of mRNA expression of measured immune factors between normal and very low SCC samples were detected. The study showed that udder quarters with very low SCC responded with a less marked increase of SCC compared with quarters with normal SCC. This difference corresponded with simultaneously lower TNF-alpha concentrations in milk. However, the immune competence of the cells themselves based on mRNA expression of TNF-alpha, IL-8, IL-1beta, and lactoferrin, did not differ. The results may indicate that very low SCC can impair the immune competence of udder quarters, because the immune response in udder quarters with lower SCC is less efficient as fewer cells contribute to the production of immunoregulators.

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BACKGROUND: The aim of this study was to evaluate the effect of CD4+ T-cell counts and other characteristics of HIV-infected individuals on hepatitis C virus (HCV) RNA levels. METHODS: All HIV-HCV-coinfected Swiss HIV Cohort Study participants with available HCV RNA levels and concurrent CD4+ T-cell counts before starting HCV therapy were included. Potential predictors of HCV RNA levels were assessed by multivariate censored linear regression models that adjust for censored values. RESULTS: The study included 1,031 individuals. Low current and nadir CD4+ T-cell counts were significantly associated with higher HCV RNA levels (P = 0.004 and 0.001, respectively). In individuals with current CD4+ T-cell counts < 200/microl, median HCV RNA levels (6.22 log10 IU/ml) were +0.14 and +0.24 log10 IU/ml higher than those with CD4+ T-cell counts of 200-500/microl and > 500/microl. Based on nadir CD4+ T-cell counts, median HCV RNA levels (6.12 log10 IU/ml) in individuals with < 200/microl CD4+ T-cells were +0.06 and +0.44 log10 IU/ml higher than those with nadir T-cell counts of 200-500/microl and > 500/microl. Median HCV RNA levels were also significantly associated with HCV genotype: lower values were associated with genotype 4 and higher values with genotype 2, as compared with genotype 1. Additional significant predictors of lower HCV RNA levels were female gender and HIV transmission through male homosexual contacts. In multivariate analyses, only CD4+ T-cell counts and HCV genotype remained significant predictors of HCV RNA levels. Conclusions: Higher HCV RNA levels were associated with CD4+ T-cell depletion. This finding is in line with the crucial role of CD4+ T-cells in the control of HCV infection.

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OBJECTIVE: To determine the effects of cognitive-behavioral stress management (CBSM) training on clinical and psychosocial markers in HIV-infected persons. METHODS: A randomized controlled trial in four HIV outpatient clinics of 104 HIV-infected persons taking combination antiretroviral therapy (cART), measuring HIV-1 surrogate markers, adherence to therapy and well-being 12 months after 12 group sessions of 2 h CBSM training. RESULTS: Intent-to-treat analyses showed no effects on HIV-1 surrogate markers in the CBSM group compared with the control group: HIV-1 RNA < 50 copies/ml in 81.1% [95% confidence interval (CI), 68.0-90.6] and 74.5% (95% CI, 60.4-85.7), respectively (P = 0.34), and mean CD4 cell change from baseline of 53.0 cells/microl (95% CI, 4.1-101.8) and 15.5 cells/microl (95% CI, -34.3 to 65.4), respectively (P = 0.29). Self-reported adherence to therapy did not differ between groups at baseline (P = 0.53) or at 12 month's post-intervention (P = 0.47). Significant benefits of CBSM over no intervention were observed in mean change of quality of life scores: physical health 2.9 (95% CI, 0.7-5.1) and -0.2 (95% CI, -2.1 to 1.8), respectively (P = 0.05); mental health 4.8 (95% CI, 1.8-7.3) and -0.5 (95% CI, -3.3 to 2.2) (P = 0.02); anxiety -2.1 (95% CI, -3.6 to -1.0) and 0.3 (95% CI, -0.7 to 1.4), respectively (P = 0.002); and depression -2.1 (95% CI, -3.2 to -0.9) and 0.02 (95% CI, -1.0 to 1.1), respectively (P = 0.001). Alleviation of depression and anxiety symptoms were most pronounced among participants with high psychological distress at baseline. CONCLUSION: CBSM training of HIV-infected persons taking on cART does not improve clinical outcome but has lasting effects on quality of life and psychological well-being.

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Determination of somatic cell count (SCC) is used worldwide in dairy practice to describe the hygienic status of the milk and the udder health of cows. When SCC is tested on a quarter level to detect single quarters with high SCC levels of cows for practical reasons, mostly foremilk samples after prestimulation (i.e. cleaning of the udder) are used. However, SCC is usually different in different milk fractions. Therefore, the goal of this study was the investigation of the use of foremilk samples for the estimation of total quarter SCC. A total of 378 milkings in 19 dairy cows were performed with a special milking device to drain quarter milk separately. Foremilk samples were taken after udder stimulation and before cluster attachment. SCC was measured in foremilk samples and in total quarter milk. Total quarter milk SCC could not be predicted precisely from foremilk SCC measurements. At relatively high foremilk SCC levels (>300 x 10(3) cells/ml) foremilk SCC were higher than total quarter milk. At around (50-300) x 10(3) cells/ml foremilk and total quarter SCC did not differ considerably. Most interestingly, if foremilk SCC was lower than 50 x 10(3) cells/ml the total quarter SCC was higher than foremilk SCC. In addition, individual cows showed dramatic variations in foremilk SCC that were not very well related to total quarter milk SCC. In conclusion, foremilk samples are useful to detect high quarter milk SCC to recognize possibly infected quarters, only if precise cell counts are not required. However, foremilk samples can be deceptive if very low cell numbers are to be detected.

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Current guidelines suggest that primary prophylaxis for Pneumocystis jiroveci pneumonia (PcP) can be safely stopped in human immunodeficiency virus (HIV)-infected patients who are receiving combined antiretroviral therapy (cART) and who have a CD4 cell count >200 cells/microL. There are few data regarding the incidence of PcP or safety of stopping prophylaxis in virologically suppressed patients with CD4 cell counts of 101-200 cells/microL.

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The risk of Hodgkin lymphoma (HL) is increased in patients infected with HIV-1. We studied the incidence and outcomes of HL, and compared CD4⁺ T-cell trajectories in HL patients and controls matched for duration of combination antiretroviral therapy (cART). A total of 40 168 adult HIV-1-infected patients (median age, 36 years; 70% male; median CD4 cell count, 234 cells/μL) from 16 European cohorts were observed during 159 133 person-years; 78 patients developed HL. The incidence was 49.0 (95% confidence interval [CI], 39.3-61.2) per 100,000 person-years, and similar on cART and not on cART (P = .96). The risk of HL declined as the most recent (time-updated) CD4 count increased: the adjusted hazard ratio comparing more than 350 with less than 50 cells/μL was 0.27 (95% CI, 0.08-0.86). Sixty-one HL cases diagnosed on cART were matched to 1652 controls: during the year before diagnosis, cases lost 98 CD4 cells (95% CI, -159 to -36 cells), whereas controls gained 35 cells (95% CI, 24-46 cells; P < .0001). The incidence of HL is not reduced by cART, and patients whose CD4 cell counts decline despite suppression of HIV-1 replication on cART may harbor HL.

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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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Background Most adults infected with HIV achieve viral suppression within a year of starting combination antiretroviral therapy (cART). It is important to understand the risk of AIDS events or death for patients with a suppressed viral load. Methods and Findings Using data from the Collaboration of Observational HIV Epidemiological Research Europe (2010 merger), we assessed the risk of a new AIDS-defining event or death in successfully treated patients. We accumulated episodes of viral suppression for each patient while on cART, each episode beginning with the second of two consecutive plasma viral load measurements <50 copies/µl and ending with either a measurement >500 copies/µl, the first of two consecutive measurements between 50–500 copies/µl, cART interruption or administrative censoring. We used stratified multivariate Cox models to estimate the association between time updated CD4 cell count and a new AIDS event or death or death alone. 75,336 patients contributed 104,265 suppression episodes and were suppressed while on cART for a median 2.7 years. The mortality rate was 4.8 per 1,000 years of viral suppression. A higher CD4 cell count was always associated with a reduced risk of a new AIDS event or death; with a hazard ratio per 100 cells/µl (95% CI) of: 0.35 (0.30–0.40) for counts <200 cells/µl, 0.81 (0.71–0.92) for counts 200 to <350 cells/µl, 0.74 (0.66–0.83) for counts 350 to <500 cells/µl, and 0.96 (0.92–0.99) for counts ≥500 cells/µl. A higher CD4 cell count became even more beneficial over time for patients with CD4 cell counts <200 cells/µl. Conclusions Despite the low mortality rate, the risk of a new AIDS event or death follows a CD4 cell count gradient in patients with viral suppression. A higher CD4 cell count was associated with the greatest benefit for patients with a CD4 cell count <200 cells/µl but still some slight benefit for those with a CD4 cell count ≥500 cells/µl.

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This study investigated the changes in somatic cell counts (SCC) in different fractions of milk, with special emphasis on the foremilk and cisternal milk fractions. Therefore, in Experiment 1, quarter milk samples were defined as strict foremilk (F), cisternal milk (C), first 400 g of alveolar milk (A1), and the remaining alveolar milk (A2). Experiment 2 included 6 foremilk fractions (F1 to F6), consisting of one hand-stripped milk jet each, and the remaining cisternal milk plus the entire alveolar milk (RM). In Experiment 1, changes during milking indicated the importance of the sampled milk fraction for measuring SCC because the decrease in the first 3 fractions (F, C, and A1) was enormous in milk with high total quarter SCC. The decline in SCC from F to C was 50% and was 80% from C to A1. Total quarter SCC presented a value of approximately 20% of SCC in F or 35% of SCC in C. Changes in milk with low or very low SCC were marginal during milking. Fractions F and C showed significant differences in SCC among different total SCC concentrations. These differences disappeared with the alveolar fractions A1 and A2. In Experiment 2, a more detailed investigation of foremilk fractions supported the findings of Experiment 1. A significant decline in the foremilk fractions even of F1 to F6 was observed in high-SCC milk at concentrations >350 x 10(3) cells/mL. Although one of these foremilk fractions presented only 0.1 to 0.2% of the total milk, the SCC was 2- to 3-fold greater than the total quarter milk SCC. Because the trait of interest (SCC) was measured directly by using the DeLaval cell counter (DCC), the quality of measurement was tested. Statistically interesting factors (repeatability, recovery rate, and potential matrix effects of milk) proved that the DCC is a useful tool for identifying the SCC of milk samples, and thus of grading udder health status. Generally, the DCC provides reliable results, but one must consider that SCC even in strict foremilk can differ dramatically from SCC in the total cisternal fraction, and thus also from SCC in the alveolar fraction.

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BACKGROUND: Patients coinfected with hepatitis C virus (HCV) and HIV experience higher mortality rates than patients infected with HIV alone. We designed a study to determine whether risks for later mortality are similar for HCV-positive and HCV-negative individuals when subjects are stratified on the basis of baseline CD4+ T-cell counts. METHODS: Antiretroviral-naive individuals, who initiated highly active antiretroviral therapy (HAART) between 1996 and 2002 were included in the study. HCV-positive and HCV-negative individuals were stratified separately by baseline CD4+ T-cell counts of 50 cell/microl increments. Cox-proportional hazards regression was used to model the effect of these strata with other variables on survival. RESULTS: CD4+ T-cell strata below 200 cells/microl, but not above, imparted an increased relative hazard (RH) of mortality for both HCV-positive and HCV-negative individuals. Among HCV-positive individuals, after adjustment for baseline age, HIV RNA levels, history of injection drug use and adherence to therapy, only CD4+ T-cell strata of <50 cells/microl (RH=4.60; 95% confidence interval [CI] 2.72-7.76) and 50-199 cells/microl (RH=2.49; 95% CI 1.63-3.81) were significantly associated with increased mortality when compared with those initiating therapy at cell counts >500 cells/microl. The same baseline CD4+ T-cell strata were found for HCV-negative individuals. CONCLUSION: In a within-groups analysis, the baseline CD4+ T-cell strata that are associated with increased RHs for mortality are the same for HCV-positive and HCV-negative individuals initiating HAART. However, a between-groups analysis reveals a higher absolute mortality risk for HCV-positive individuals.

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BACKGROUND: In recent years, treatment options for human immunodeficiency virus type 1 (HIV-1) infection have changed from nonboosted protease inhibitors (PIs) to nonnucleoside reverse-transcriptase inhibitors (NNRTIs) and boosted PI-based antiretroviral drug regimens, but the impact on immunological recovery remains uncertain. METHODS: During January 1996 through December 2004 [corrected] all patients in the Swiss HIV Cohort were included if they received the first combination antiretroviral therapy (cART) and had known baseline CD4(+) T cell counts and HIV-1 RNA values (n = 3293). For follow-up, we used the Swiss HIV Cohort Study database update of May 2007 [corrected] The mean (+/-SD) duration of follow-up was 26.8 +/- 20.5 months. The follow-up time was limited to the duration of the first cART. CD4(+) T cell recovery was analyzed in 3 different treatment groups: nonboosted PI, NNRTI, or boosted PI. The end point was the absolute increase of CD4(+) T cell count in the 3 treatment groups after the initiation of cART. RESULTS: Two thousand five hundred ninety individuals (78.7%) initiated a nonboosted-PI regimen, 452 (13.7%) initiated an NNRTI regimen, and 251 (7.6%) initiated a boosted-PI regimen. Absolute CD4(+) T cell count increases at 48 months were as follows: in the nonboosted-PI group, from 210 to 520 cells/muL; in the NNRTI group, from 220 to 475 cells/muL; and in the boosted-PI group, from 168 to 511 cells/muL. In a multivariate analysis, the treatment group did not affect the response of CD4(+) T cells; however, increased age, pretreatment with nucleoside reverse-transcriptase inhibitors, serological tests positive for hepatitis C virus, Centers for Disease Control and Prevention stage C infection, lower baseline CD4(+) T cell count, and lower baseline HIV-1 RNA level were risk factors for smaller increases in CD4(+) T cell count. CONCLUSION: CD4(+) T cell recovery was similar in patients receiving nonboosted PI-, NNRTI-, and boosted PI-based cART.

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BACKGROUND: Estimates of the decrease in CD4(+) cell counts in untreated patients with human immunodeficiency virus (HIV) infection are important for patient care and public health. We analyzed CD4(+) cell count decreases in the Cape Town AIDS Cohort and the Swiss HIV Cohort Study. METHODS: We used mixed-effects models and joint models that allowed for the correlation between CD4(+) cell count decreases and survival and stratified analyses by the initial cell count (50-199, 200-349, 350-499, and 500-750 cells/microL). Results are presented as the mean decrease in CD4(+) cell count with 95% confidence intervals (CIs) during the first year after the initial CD4(+) cell count. RESULTS: A total of 784 South African (629 nonwhite) and 2030 Swiss (218 nonwhite) patients with HIV infection contributed 13,388 CD4(+) cell counts. Decreases in CD4(+) cell count were steeper in white patients, patients with higher initial CD4(+) cell counts, and older patients. Decreases ranged from a mean of 38 cells/microL (95% CI, 24-54 cells/microL) in nonwhite patients from the Swiss HIV Cohort Study 15-39 years of age with an initial CD4(+) cell count of 200-349 cells/microL to a mean of 210 cells/microL (95% CI, 143-268 cells/microL) in white patients in the Cape Town AIDS Cohort > or =40 years of age with an initial CD4(+) cell count of 500-750 cells/microL. CONCLUSIONS: Among both patients from Switzerland and patients from South Africa, CD4(+) cell count decreases were greater in white patients with HIV infection than they were in nonwhite patients with HIV infection.

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OBJECTIVES: To examine the accuracy of the World Health Organization immunological criteria for virological failure of antiretroviral treatment. METHODS: Analysis of 10 treatment programmes in Africa and South America that monitor both CD4 cell counts and HIV-1 viral load. Adult patients with at least two CD4 counts and viral load measurements between month 6 and 18 after starting a non-nucleoside reverse transcriptase inhibitor-based regimen were included. WHO immunological criteria include CD4 counts persistently <100 cells/microl, a fall below the baseline CD4 count, or a fall of >50% from the peak value. Virological failure was defined as two measurements > or =10 0000 copies/ml (higher threshold) or > or =500 copies/ml (lower threshold). Measures of accuracy with exact binomial 95% confidence intervals (CI) were calculated. RESULTS: A total of 2009 patients were included. During 1856 person-years of follow up 63 patients met the immunological criteria and 35 patients (higher threshold) and 95 patients (lower threshold) met the virological criteria. Sensitivity [95% confidence interval (CI)] was 17.1% (6.6-33.6%) for the higher and 12.6% (6.7-21.0%) for the lower threshold. Corresponding results for specificity were 97.1% (96.3-97.8%) and 97.3% (96.5-98.0%), for positive predictive value 9.5% (3.6-19.6%) and 19.0% (10.2-30.9%) and for negative predictive value 98.5% (97.9-99.0%) and 95.7% (94.7-96.6%). CONCLUSIONS: The positive predictive value of the WHO immunological criteria for virological failure of antiretroviral treatment in resource-limited settings is poor, but the negative predictive value is high. Immunological criteria are more appropriate for ruling out than for ruling in virological failure in resource-limited settings.