22 resultados para Wit and humor


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Context: In virologically suppressed, antiretroviral-treated patients, the effect of switching to tenofovir (TDF) on bone biomarkers compared to patients remaining on stable antiretroviral therapy is unknown. Methods: We examined bone biomarkers (osteocalcin [OC], procollagen type 1 amino-terminal propeptide, and C-terminal cross-linking telopeptide of type 1 collagen) and bone mineral density (BMD) over 48 weeks in virologically suppressed patients (HIV RNA < 50 copies/ml) randomized to switch to TDF/emtricitabine (FTC) or remain on first-line zidovudine (AZT)/lamivudine (3TC). PTH was also measured. Between-group differences in bone biomarkers and associations between change in bone biomarkers and BMD measures were assessed by Student's t tests, Pearson correlation, and multivariable linear regression, respectively. All data are expressed as mean (SD), unless otherwise specified. Results: Of 53 subjects (aged 46.0 y; 84.9% male; 75.5% Caucasian), 29 switched to TDF/FTC. There were reductions in total hip and lumbar spine BMD in those switching to TDF/FTC (total hip, TDF/FTC, −1.73 (2.76)% vs AZT/3TC, −0.39 (2.41)%; between-group P = .07; lumbar spine, TDF/FTC, −1.50 (3.49)% vs AZT/3TC, +0.25 (2.82)%; between-group P = .06), but they did not reach statistical significance. Greater declines in lumbar spine BMD correlated with greater increases in OC (r = −0.28; P = .05). The effect of TDF/FTC on bone biomarkers remained significant when adjusted for baseline biomarker levels, gender, and ethnicity. There was no difference in change in PTH levels over 48 weeks between treatment groups (between-group P = .23). All biomarkers increased significantly from weeks 0 to 48 in the switch group, with no significant change in those remaining on AZT/3TC (between-group, all biomarkers, P < .0001). Conclusion: A switch to TDF/FTC compared to remaining on a stable regimen is associated with increases in bone turnover that correlate with reductions in BMD, suggesting that TDF exposure directly affects bone metabolism in vivo.

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Background Persons infected with human immunodeficiency virus (HIV) have increased rates of coronary artery disease (CAD). The relative contribution of genetic background, HIV-related factors, antiretroviral medications, and traditional risk factors to CAD has not been fully evaluated in the setting of HIV infection. Methods In the general population, 23 common single-nucleotide polymorphisms (SNPs) were shown to be associated with CAD through genome-wide association analysis. Using the Metabochip, we genotyped 1875 HIV-positive, white individuals enrolled in 24 HIV observational studies, including 571 participants with a first CAD event during the 9-year study period and 1304 controls matched on sex and cohort. Results A genetic risk score built from 23 CAD-associated SNPs contributed significantly to CAD (P = 2.9×10−4). In the final multivariable model, participants with an unfavorable genetic background (top genetic score quartile) had a CAD odds ratio (OR) of 1.47 (95% confidence interval [CI], 1.05–2.04). This effect was similar to hypertension (OR = 1.36; 95% CI, 1.06–1.73), hypercholesterolemia (OR = 1.51; 95% CI, 1.16–1.96), diabetes (OR = 1.66; 95% CI, 1.10–2.49), ≥1 year lopinavir exposure (OR = 1.36; 95% CI, 1.06–1.73), and current abacavir treatment (OR = 1.56; 95% CI, 1.17–2.07). The effect of the genetic risk score was additive to the effect of nongenetic CAD risk factors, and did not change after adjustment for family history of CAD. Conclusions In the setting of HIV infection, the effect of an unfavorable genetic background was similar to traditional CAD risk factors and certain adverse antiretroviral exposures. Genetic testing may provide prognostic information complementary to family history of CAD.

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OBJECTIVES: The aim of this study was to determine whether the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)- or Cockcroft-Gault (CG)-based estimated glomerular filtration rates (eGFRs) performs better in the cohort setting for predicting moderate/advanced chronic kidney disease (CKD) or end-stage renal disease (ESRD). METHODS: A total of 9521 persons in the EuroSIDA study contributed 133 873 eGFRs. Poisson regression was used to model the incidence of moderate and advanced CKD (confirmed eGFR < 60 and < 30 mL/min/1.73 m(2) , respectively) or ESRD (fatal/nonfatal) using CG and CKD-EPI eGFRs. RESULTS: Of 133 873 eGFR values, the ratio of CG to CKD-EPI was ≥ 1.1 in 22 092 (16.5%) and the difference between them (CG minus CKD-EPI) was ≥ 10 mL/min/1.73 m(2) in 20 867 (15.6%). Differences between CKD-EPI and CG were much greater when CG was not standardized for body surface area (BSA). A total of 403 persons developed moderate CKD using CG [incidence 8.9/1000 person-years of follow-up (PYFU); 95% confidence interval (CI) 8.0-9.8] and 364 using CKD-EPI (incidence 7.3/1000 PYFU; 95% CI 6.5-8.0). CG-derived eGFRs were equal to CKD-EPI-derived eGFRs at predicting ESRD (n = 36) and death (n = 565), as measured by the Akaike information criterion. CG-based moderate and advanced CKDs were associated with ESRD [adjusted incidence rate ratio (aIRR) 7.17; 95% CI 2.65-19.36 and aIRR 23.46; 95% CI 8.54-64.48, respectively], as were CKD-EPI-based moderate and advanced CKDs (aIRR 12.41; 95% CI 4.74-32.51 and aIRR 12.44; 95% CI 4.83-32.03, respectively). CONCLUSIONS: Differences between eGFRs using CG adjusted for BSA or CKD-EPI were modest. In the absence of a gold standard, the two formulae predicted clinical outcomes with equal precision and can be used to estimate GFR in HIV-positive persons.

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In natural hazard research, risk is defined as a function of (1) the probability of occurrence of a hazardous process, and (2) the assessment of the related extent of damage, defined by the value of elements at risk exposed and their physical vulnerability. Until now, various works have been undertaken to determine vulnerability values for objects exposed to geomorphic hazards such as mountain torrents. Yet, many studies only provide rough estimates for vulnerability values based on proxies for process intensities. However, the deduced vulnerability functions proposed in the literature show a wide range, in particular with respect to medium and high process magnitudes. In our study, we compare vulnerability functions for torrent processes derived from studies in test sites located in the Austrian Alps and in Taiwan. Based on this comparison we expose needs for future research in order to enhance mountain hazard risk management with a particular focus on the question of vulnerability on a catchment scale.

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Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise e.g., Fundus photography, Optical Coherence Tomography (OCT), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The presented article’s goal is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI which was not visible before like vessels and the macula. This article’s contributions include automatic detection of the optic disc, the fovea, the optic axis and an automatic segmentation of the vitreous humor of the eye.

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BACKGROUND The association between combination antiretroviral therapy (cART) and cancer risk, especially regimens containing protease inhibitors (PIs) or nonnucleoside reverse transcriptase inhibitors (NNRTIs), is unclear. METHODS Participants were followed from the latest of D:A:D study entry or January 1, 2004, until the earliest of a first cancer diagnosis, February 1, 2012, death, or 6 months after the last visit. Multivariable Poisson regression models assessed associations between cumulative (per year) use of either any cART or PI/NNRTI, and the incidence of any cancer, non-AIDS-defining cancers (NADC), AIDS-defining cancers (ADC), and the most frequently occurring ADC (Kaposi sarcoma, non-Hodgkin lymphoma) and NADC (lung, invasive anal, head/neck cancers, and Hodgkin lymphoma). RESULTS A total of 41,762 persons contributed 241,556 person-years (PY). A total of 1832 cancers were diagnosed [incidence rate: 0.76/100 PY (95% confidence interval: 0.72 to 0.79)], 718 ADC [0.30/100 PY (0.28-0.32)], and 1114 NADC [0.46/100 PY (0.43-0.49)]. Longer exposure to cART was associated with a lower ADC risk [adjusted rate ratio: 0.88/year (0.85-0.92)] but a higher NADC risk [1.02/year (1.00-1.03)]. Both PI and NNRTI use were associated with a lower ADC risk [PI: 0.96/year (0.92-1.00); NNRTI: 0.86/year (0.81-0.91)]. PI use was associated with a higher NADC risk [1.03/year (1.01-1.05)]. Although this was largely driven by an association with anal cancer [1.08/year (1.04-1.13)], the association remained after excluding anal cancers from the end point [1.02/year (1.01-1.04)]. No association was seen between NNRTI use and NADC [1.00/year (0.98-1.02)]. CONCLUSIONS Cumulative use of PIs may be associated with a higher risk of anal cancer and possibly other NADC. Further investigation of biological mechanisms is warranted.

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OBJECTIVES Pre-antiretroviral therapy (ART) inflammation and coagulation activation predict clinical outcomes in HIV-positive individuals. We assessed whether pre-ART inflammatory marker levels predicted the CD4 count response to ART. METHODS Analyses were based on data from the Strategic Management of Antiretroviral Therapy (SMART) trial, an international trial evaluating continuous vs. interrupted ART, and the Flexible Initial Retrovirus Suppressive Therapies (FIRST) trial, evaluating three first-line ART regimens with at least two drug classes. For this analysis, participants had to be ART-naïve or off ART at randomization and (re)starting ART and have C-reactive protein (CRP), interleukin-6 (IL-6) and D-dimer measured pre-ART. Using random effects linear models, we assessed the association between each of the biomarker levels, categorized as quartiles, and change in CD4 count from ART initiation to 24 months post-ART. Analyses adjusted for CD4 count at ART initiation (baseline), study arm, follow-up time and other known confounders. RESULTS Overall, 1084 individuals [659 from SMART (26% ART naïve) and 425 from FIRST] met the eligibility criteria, providing 8264 CD4 count measurements. Seventy-five per cent of individuals were male with the mean age of 42 years. The median (interquartile range) baseline CD4 counts were 416 (350-530) and 100 (22-300) cells/μL in SMART and FIRST, respectively. All of the biomarkers were inversely associated with baseline CD4 count in FIRST but not in SMART. In adjusted models, there was no clear relationship between changing biomarker levels and mean change in CD4 count post-ART (P for trend: CRP, P = 0.97; IL-6, P = 0.25; and D-dimer, P = 0.29). CONCLUSIONS Pre-ART inflammation and coagulation activation do not predict CD4 count response to ART and appear to influence the risk of clinical outcomes through other mechanisms than blunting long-term CD4 count gain.