989 resultados para Sparre, Erik, count.


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The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

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Depuis mon arrivée en Italie j’ai été frappée par les grandes différences qui existent entre les expressions figées et idiomatiques dans les deux langues que sont le français et l’Italien. Etant d’expression francophone, et inscrite à la faculté de langue et de traduction, il m’a été donné de constater que j’avais de grandes difficultés à traduire les expressions figées d’une langue à une autre. Et plus encore il était très difficile de leur trouver des définitions et expressions équivalentes. Fort de ce constat, je me suis intéressée à la possibilité d’analyse des expressions figées du français à l’Italien à travers l’ouvrage de Gaston Gross paru aux éditions OPHRYS, 1996, sous le titre : Les expressions figées en français. Noms composés et autres locutions. Cet ouvrage constitue une avancée importante dans les études et les recherches sur la médiation linguistique et rejoint donc notre domaine de compétence. A travers cette analyse il s’agira de se poser la question fondamentale : Qu’est-ce qu’une expression figée ? Quelles sont ses représentations et ses évolutions dans cet ouvrage et comment s’effectuent son passage et ses transformations d’une langue à une autre ? Pour être plus précis, dans notre cas, comment pouvons-nous établir le passage des expressions figés du français à l’Italien dans cet ouvrage de Gaston Gross ? En répondant à ces questions, nous partons sur la base de l’hypothèse que les expressions figées constituent une richesse dans une langue et sont difficilement traductibles dans une autre langue sans en perdre la richesse et la teneur, lors de ce processus. Notre travail consistera donc à vérifier cette hypothèse.

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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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Background In Switzerland and other developed countries, the number of tuberculosis (TB) cases has been decreasing for decades, but HIV-infected patients and migrants remain risk groups. The aim of this study was to compare characteristics of TB in HIV-negative and HIV-infected patients diagnosed in Switzerland, and between coinfected patients enrolled and not enrolled in the national Swiss HIV Cohort Study (SHCS). Methods and Findings All patients diagnosed with culture-confirmed TB in the SHCS and a random sample of culture-confirmed cases reported to the national TB registry 2000–2008 were included. Outcomes were assessed in HIV-infected patients and considered successful in case of cure or treatment completion. Ninety-three SHCS patients and 288 patients selected randomly from 4221 registered patients were analyzed. The registry sample included 10 (3.5%) coinfected patients not enrolled in the SHCS: the estimated number of HIV-infected patients not enrolled in the SHCS but reported to the registry 2000–2008 was 146 (95% CI 122–173). Coinfected patients were more likely to be from sub-Saharan Africa (51.5% versus 15.8%, P<0.0001) and to present disseminated disease (23.9% vs. 3.4%, P<0.0001) than HIV-negative patients. Coinfected patients not enrolled in the SHCS were asylum seekers or migrant workers, with lower CD4 cell counts at TB diagnosis (median CD4 count 79 cells/µL compared to 149 cells/µL among SHCS patients, P = 0.07). There were 6 patients (60.0%) with successful outcomes compared to 82 (88.2%) patients in the SHCS (P = 0.023). Conclusions The clinical presentation of coinfected patients differed from HIV-negative TB patients. The number of HIV-infected patients diagnosed with TB outside the SHCS is similar to the number diagnosed within the cohort but outcomes are poorer in patients not followed up in the national cohort. Special efforts are required to address the needs of this vulnerable population.

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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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Background Although CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study. Methodology/Principal Findings We built up two prediction rules (“Snap-shot rule” for a single sample and “Track-shot rule” for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior ≥5% or <5% chance of meeting predetermined thresholds for starting treatment. The percentage of measurements that both rules falsely deemed superfluous never exceeded 5%. Superfluous CD4 determinations represented 4%, 11%, and 39% of all actual determinations for treatment thresholds of 500, 350, and 200×106/L, respectively. The Track-shot rule was only marginally superior to the Snap-shot rule. Both rules lose usefulness for CD4 counts coming near to treatment threshold. Conclusions/Significance Frequent CD4 count monitoring of patients with CD4 counts well above the threshold for initiating therapy is unlikely to identify patients who require therapy. It appears sufficient to measure CD4 cell count 1 year after a count >650 for a threshold of 200, >900 for 350, or >1150 for 500×106/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.

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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.