CD4+ T-cell count increase in HIV-1-infected patients with suppressed viral load within 1 year after start of antiretroviral therapy

BACKGROUND: CD4+ T-cell recovery in patients with continuous suppression of plasma HIV-1 viral load (VL) is highly variable. This study aimed to identify predictive factors for long-term CD4+ T-cell increase in treatment-naive patients starting combination antiretroviral therapy (cART). METHODS: Treatment-naive patients in the Swiss HIV Cohort Study reaching two VL measurements <50 copies/ml >3 months apart during the 1st year of cART were included (n=1816 patients). We studied CD4+ T-cell dynamics until the end of suppression or up to 5 years, subdivided into three periods: 1st year, years 2-3 and years 4-5 of suppression. Multiple median regression adjusted for repeated CD4+ T-cell measurements was used to study the dependence of CD4+ T-cell slopes on clinical covariates and drug classes. RESULTS: Median CD4+ T-cell increases following VL suppression were 87, 52 and 19 cells/microl per year in the three periods. In the multiple regression model, median CD4+ T-cell increases over all three periods were significantly higher for female gender, lower age, higher VL at cART start, CD4+ T-cell <650 cells/microl at start of the period and low CD4+ T-cell increase in the previous period. Patients on tenofovir showed significantly lower CD4+ T-cell increases compared with stavudine. CONCLUSIONS: In our observational study, long-term CD4+ T-cell increase in drug-naive patients with suppressed VL was higher in regimens without tenofovir. The clinical relevance of these findings must be confirmed in, ideally, clinical trials or large, collaborative cohort projects but could influence treatment of older patients and those starting cART at low CD4+ T-cell levels.

A pedigree with autosomal dominant thrombocytopenia, red cell macrocytosis, and an occurrence of t(12:21) positive pre-B acute lymphoblastic leukemia

Sampling and analyzing new families with inherited blood disorders are major steps contributing to the identification of gene(s) responsible for normal and pathologic hematopoiesis. Familial occurrences of hematological disorders alone, or as part of a syndromic disease, have been reported, and for some the underlying genetic mutation has been identified. Here we describe a new autosomal dominant inherited phenotype of thrombocytopenia and red cell macrocytosis in a four-generation pedigree. Interestingly, in the youngest generation, a 2-year-old boy presenting with these familial features has developed acute lymphoblastic leukemia characterized by a t(12;21) translocation. Tri-lineage involvement of platelets, red cells and white cells may suggest a genetic defect in an early multiliear progenitor or a stem cell. Functional assays in EBV-transformed cell lines revealed a defect in cell proliferation and tubulin dynamics. Two candidate genes, RUNX1 and FOG1, were sequenced but no pathogenic mutation was found. Identification of the underlying genetic defect(s) in this family may help in understanding the complex process of hematopoiesis.

Red cell survival in relation to changes in the hematocrit: more important than you think

The management of anemia in patients with chronic renal failure has greatly improved with the availability of recombinant human erythropoietin in the late 1980s, leading to a considerable reduction in mortality and morbidity and to an improvement in quality of life. The findings from recent controlled clinical outcome trials have resulted in a rather narrow, generally accepted therapeutic hematocrit target range. However, currently available dosing algorithms do not permit achievement and maintenance of target values within the therapeutic range in many patients. One possible explanation for this failure may be the ignorance of a finite erythrocyte lifespan not integrated into most algorithms. The purpose of this article is to underline the essential role played by the erythrocyte lifespan in the erythropoietic response to recombinant human erythropoietin and to encourage the integration of this concept in the future development of computer-assisted decision support systems.

CD4+ T cell count recovery in HIV type 1-infected patients is independent of class of antiretroviral therapy

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.

CD4(+) T cell count decreases by ethnicity among untreated patients with HIV infection in South Africa and Switzerland

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.

Accuracy of WHO CD4 cell count criteria for virological failure of antiretroviral therapy

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.

Prognosis of patients treated with cART from 36 months after initiation, according to current and previous CD4 cell count and plasma HIV-1 RNA measurements

OBJECTIVES: CD4 cell count and plasma viral load are well known predictors of AIDS and mortality in HIV-1-infected patients treated with combination antiretroviral therapy (cART). This study investigated, in patients treated for at least 3 years, the respective prognostic importance of values measured at cART initiation, and 6 and 36 months later, for AIDS and death. METHODS: Patients from 15 HIV cohorts included in the ART Cohort Collaboration, aged at least 16 years, antiretroviral-naive when they started cART and followed for at least 36 months after start of cART were eligible. RESULTS: Among 14 208 patients, the median CD4 cell counts at 0, 6 and 36 months were 210, 320 and 450 cells/microl, respectively, and 78% of patients achieved viral load less than 500 copies/ml at 6 months. In models adjusted for characteristics at cART initiation and for values at all time points, values at 36 months were the strongest predictors of subsequent rates of AIDS and death. Although CD4 cell count and viral load at cART initiation were no longer prognostic of AIDS or of death after 36 months, viral load at 6 months and change in CD4 cell count from 6 to 36 months were prognostic for rates of AIDS from 36 months. CONCLUSIONS: Although current values of CD4 cell count and HIV-1 RNA are the most important prognostic factors for subsequent AIDS and death rates in HIV-1-infected patients treated with cART, changes in CD4 cell count from 6 to 36 months and the value of 6-month HIV-1 RNA are also prognostic for AIDS.

White blood cell count and mortality in patients with acute pulmonary embolism

Although associated with adverse outcomes in other cardiovascular diseases, the prognostic value of an elevated white blood cell (WBC) count, a marker of inflammation and hypercoagulability, is uncertain in patients with pulmonary embolism (PE). We therefore sought to assess the prognostic impact of the WBC in a large, state-wide retrospective cohort of patients with PE. We evaluated 14,228 patient discharges with a primary diagnosis of PE from 186 hospitals in Pennsylvania. We used random-intercept logistic regression to assess the independent association between WBC count levels at the time of presentation and mortality and hospital readmission within 30 days, adjusting for patient and hospital characteristics. Patients with an admission WBC count <5.0, 5.0-7.8, 7.9-9.8, 9.9-12.6, and >12.6 × 10(9) /L had a cumulative 30-day mortality of 10.9%, 6.2%, 5.4%, 8.3%, and 16.3% (P < 0.001), and a readmission rate of 17.6%, 11.9%, 10.9%, 11.5%, and 15.0%, respectively (P < 0.001). Compared with patients with a WBC count 7.9-9.8 × 10(9) /L, adjusted odds of 30-day mortality were significantly greater for patients with a WBC count <5.0 × 10(9) /L (odds ratio [OR] 1.52, 95% confidence interval [CI] 1.14-2.03), 9.9-12.6 × 10(9) /L (OR 1.55, 95% CI 1.26-1.91), or >12.6 × 10(9) /L (OR 2.22, 95% CI 1.83-2.69), respectively. The adjusted odds of readmission were also significantly increased for patients with a WBC count <5.0 × 10(9) /L (OR 1.34, 95% CI 1.07-1.68) or >12.6 × 10(9) /L (OR 1.29, 95% CI 1.10-1.51). In patients presenting with PE, WBC count is an independent predictor of short-term mortality and hospital readmission.

Genotype-specific risk factors for Staphylococcus aureus in Swiss dairy herds with an elevated yield-corrected herd somatic cell count

Bovine mastitis is a frequent problem in Swiss dairy herds. One of the main pathogens causing significant economic loss is Staphylococcus aureus. Various Staph. aureus genotypes with different biological properties have been described. Genotype B (GTB) of Staph. aureus was identified as the most contagious and one of the most prevalent strains in Switzerland. The aim of this study was to identify risk factors associated with the herd-level presence of Staph. aureus GTB and Staph. aureus non-GTB in Swiss dairy herds with an elevated yield-corrected herd somatic cell count (YCHSCC). One hundred dairy herds with a mean YCHSCC between 200,000 and 300,000cells/mL in 2010 were recruited and each farm was visited once during milking. A standardized protocol investigating demography, mastitis management, cow husbandry, milking system, and milking routine was completed during the visit. A bulk tank milk (BTM) sample was analyzed by real-time PCR for the presence of Staph. aureus GTB to classify the herds into 2 groups: Staph. aureus GTB-positive and Staph. aureus GTB-negative. Moreover, quarter milk samples were aseptically collected for bacteriological culture from cows with a somatic cell count ≥150,000cells/mL on the last test-day before the visit. The culture results allowed us to allocate the Staph. aureus GTB-negative farms to Staph. aureus non-GTB and Staph. aureus-free groups. Multivariable multinomial logistic regression models were built to identify risk factors associated with the herd-level presence of Staph. aureus GTB and Staph. aureus non-GTB. The prevalence of Staph. aureus GTB herds was 16% (n=16), whereas that of Staph. aureus non-GTB herds was 38% (n=38). Herds that sent lactating cows to seasonal communal pastures had significantly higher odds of being infected with Staph. aureus GTB (odds ratio: 10.2, 95% CI: 1.9-56.6), compared with herds without communal pasturing. Herds that purchased heifers had significantly higher odds of being infected with Staph. aureus GTB (rather than Staph. aureus non-GTB) compared with herds without purchase of heifers. Furthermore, herds that did not use udder ointment as supportive therapy for acute mastitis had significantly higher odds of being infected with Staph. aureus GTB (odds ratio: 8.5, 95% CI: 1.6-58.4) or Staph. aureus non-GTB (odds ratio: 6.1, 95% CI: 1.3-27.8) than herds that used udder ointment occasionally or regularly. Herds in which the milker performed unrelated activities during milking had significantly higher odds of being infected with Staph. aureus GTB (rather than Staph. aureus non-GTB) compared with herds in which the milker did not perform unrelated activities at milking. Awareness of 4 potential risk factors identified in this study guides implementation of intervention strategies to improve udder health in both Staph. aureus GTB and Staph. aureus non-GTB herds.

When to Monitor CD4 Cell Count and HIV RNA to Reduce Mortality and AIDS-Defining Illness in Virologically Suppressed HIV-Positive Persons on Antiretroviral Therapy in High-Income Countries: A Prospective Observational Study.

OBJECTIVE To illustrate an approach to compare CD4 cell count and HIV-RNA monitoring strategies in HIV-positive individuals on antiretroviral therapy (ART). DESIGN Prospective studies of HIV-positive individuals in Europe and the USA in the HIV-CAUSAL Collaboration and The Center for AIDS Research Network of Integrated Clinical Systems. METHODS Antiretroviral-naive individuals who initiated ART and became virologically suppressed within 12 months were followed from the date of suppression. We compared 3 CD4 cell count and HIV-RNA monitoring strategies: once every (1) 3 ± 1 months, (2) 6 ± 1 months, and (3) 9-12 ± 1 months. We used inverse-probability weighted models to compare these strategies with respect to clinical, immunologic, and virologic outcomes. RESULTS In 39,029 eligible individuals, there were 265 deaths and 690 AIDS-defining illnesses or deaths. Compared with the 3-month strategy, the mortality hazard ratios (95% CIs) were 0.86 (0.42 to 1.78) for the 6 months and 0.82 (0.46 to 1.47) for the 9-12 month strategy. The respective 18-month risk ratios (95% CIs) of virologic failure (RNA >200) were 0.74 (0.46 to 1.19) and 2.35 (1.56 to 3.54) and 18-month mean CD4 differences (95% CIs) were -5.3 (-18.6 to 7.9) and -31.7 (-52.0 to -11.3). The estimates for the 2-year risk of AIDS-defining illness or death were similar across strategies. CONCLUSIONS Our findings suggest that monitoring frequency of virologically suppressed individuals can be decreased from every 3 months to every 6, 9, or 12 months with respect to clinical outcomes. Because effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.

Determinants of CD4 cell count decline after treatment interruption

Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

Red Cell Volume Expansion at Altitude: A Meta-analysis and Monte Carlo Simulation

Meta-análisis del volumen de eritrocitos en altitud

Deciphering the Nuclear Import Pathway for the Cytoskeletal Red Cell Protein 4.1R

The erythroid membrane cytoskeletal protein 4.1 is the prototypical member of a genetically and topologically complex family that is generated by combinatorial alternative splicing pathways and is localized at diverse intracellular sites including the nucleus. To explore the molecular determinants for nuclear localization, we transfected COS-7 cells with epitope-tagged versions of natural red cell protein 4.1 (4.1R) isoforms as well as mutagenized and truncated derivatives. Two distant topological sorting signals were required for efficient nuclear import of the 4.1R80 isoform: a basic peptide, KKKRER, encoded by alternative exon 16 and acting as a weak core nuclear localization signal (4.1R NLS), and an acidic peptide, EED, encoded by alternative exon 5. 4.1R80 isoforms lacking either of these two exons showed decreased nuclear import. Fusion of various 4.1R80 constructs to the cytoplasmic reporter protein pyruvate kinase confirmed a requirement for both motifs for full NLS function. 4.1R80 was efficiently imported in the nuclei of digitonin-permeabilized COS-7 cells in the presence of recombinant Rch1 (human importin α2), importin β, and GTPase Ran. Quantitative analysis of protein–protein interactions using a resonant mirror detection technique showed that 4.1R80 bound to Rch1 in vitro with high affinity (KD = 30 nM). The affinity decreased at least 7- and 20-fold, respectively, if the EED motif in exon 5 or if 4.1R NLS in exon 16 was lacking or mutated, confirming that both motifs were required for efficient importin-mediated nuclear import of 4.1R80.