Factores que influyen en la configuración del perfil de conductor de riesgo en la población de jóvenes estudiantes universitarios: evidencias para el diseño de intervenciones preventivas

The aim of this research is to identify and analyse factors that have an influence on the creation of a high risk profile in young drivers, in order to create road safety educational initiatives designed to minimise the risk of suffering a traffic accident, and aimed at preventing young people from developing a high risk profile. With the purpose of identifying what may have been the strongest influences in establishing the risk profile, the factors of family, peers and partner, reactions to stressful situations, videogames and accident experiences were considered among a cohort of university students. The results show that family and peers seem to be the most influential factors, whereas driving schools seems to be the strongest protective factor in preventing the appearance of risky driving profiles. Educational programmes highlighting the modelling role of those who teach young people how to drive need to be developed.El objetivo de esta investigación es identificar y analizar los factores que influyen en la creación de un perfil de conductor de alto riesgo entre los jóvenes conductores. La finalidad de ello es tener evidencias científicas que permitan diseñar iniciativas de intervención educativa para minimizar el riesgo de sufrir accidentes de tráfico y prevenir el desarrollo de perfiles de alto riesgo en jóvenes conductores. Con el propósito de identificar las influencias que podíantener más peso en la creación del perfil de riesgo se analizaron los factores familia, grupo de iguales y pareja, reacción a situaciones estresantes, videojuegos, e involucración en accidentes de tráfico en una muestra de estudiantes universitarios. Los resultados indican que la mayor influencia sería ejercida por la familia y el grupo de iguales, mientras que por otro lado, las autoescuelas se posicionarían como el mayor factor protector en la prevención de la aparición del perfil de conductor de riesgo. A partir de estos hallazgos se recomienda el desarrollo de programas que permitan reforzar el rol modelador de aquellos que enseñan a los jóvenes a conducir

Peripheral T-cell lymphoma: Molecular profiling recognizes subclasses and identifies prognostic markers

Peripheral T-cell lymphoma (PTCL) is a clinically aggressive disease, with a poor response to therapy and a low overall survival rate of approximately 30% after 5 years. We have analyzed a series of 105 cases with a diagnosis of PTCL using a customized NanoString platform (NanoString Technologies, Seattle, WA) that includes 208 genes associated with T-cell differentiation, oncogenes and tumor suppressor genes, deregulated pathways, and stromal cell subpopulations. A comparative analysis of the various histological types of PTCL (angioimmunoblastic T-cell lymphoma [AITL]; PTCL with T follicular helper [TFH] phenotype; PTCL not otherwise specified [NOS]) showed that specific sets of genes were associated with each of the diagnoses. These included TFH markers, cytotoxic markers, and genes whose expression was a surrogate for specific cellular subpopulations, including follicular dendritic cells, mast cells, and genes belonging to precise survival (NF-κB) and other pathways. Furthermore, the mutational profile was analyzed using a custom panel that targeted 62 genes in 76 cases distributed in AITL, PTCL-TFH, and PTCL-NOS. The main differences among the 3 nodal PTCL classes involved the RHOAG17V mutations (P < .0001), which were approximately twice as frequent in AITL (34.09%) as in PTCL-TFH (16.66%) cases but were not detected in PTCL-NOS. A multivariate analysis identified gene sets that allowed the series of cases to be stratified into different risk groups. This study supports and validates the current division of PTCL into these 3 categories, identifies sets of markers that can be used for a more precise diagnosis, and recognizes the expression of B-cell genes as an IPI-independent prognostic factor for AITL

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Factors influencing a risky driving profile among a cohort of young university students: Bases for adopting evidence-based prevention interventions

El objetivo de esta investigación es identificar y analizar los factores que influyen en la creación de un perfil de conductor de alto riesgo entre los jóvenes conductores. La finalidad de ello es tener evidencias científicas que permitan diseñar iniciativas de intervención educativa para minimizar el riesgo de sufrir accidentes de tráfico y prevenir el desarrollo de perfiles de alto riesgo en jóvenes conductores. Con el propósito de identificar las influencias que podíantener más peso en la creación del perfil de riesgo se analizaron los factores familia, grupo de iguales y pareja, reacción a situaciones estresantes, videojuegos, e involucración en accidentes de tráfico en una muestra de estudiantes universitarios. Los resultados indican que la mayor influencia sería ejercida por la familia y el grupo de iguales, mientras que por otro lado, las autoescuelas se posicionarían como el mayor factor protector en la prevención de la aparición del perfil de conductor de riesgo. A partir de estos hallazgos se recomienda el desarrollo de programas que permitan reforzar el rol modelador de aquellos que enseñan a los jóvenes a conducir.The aim of this research is to identify and analyse factors that have an influence on the creation of a high risk profile in young drivers, in order to create road safety educational initiatives designed to minimise the risk of suffering a traffic accident, and aimed at preventing young people from developing a high risk profile. With the purpose of identifying what may have been the strongest influences in establishing the risk profile, the factors of family, peers and partner, reactions to stressful situations, videogames and accident experiences were considered among a cohort of university students. The results show that family and peers seem to be the most influential factors, whereas driving schools seems to be the strongest protective factor in preventing the appearance of risky driving profiles. Educational programmes highlighting the modelling role of those who teach young people how to drive need to be developed

An integrated prognostic model for diffuse large B-cell lymphoma treated with immunochemotherapy

Diffuse large B-cell lymphoma (DLBCL), the most frequent non-Hodgkin's lymphoma subtype, is characterized by strong biological, morphological, and clinical heterogeneity, but patients are treated with immunochemotherapy in a relatively homogeneous way. Here, we have used a customized NanoString platform to analyze a series of 197 homogeneously treated DLBCL cases. The platform includes the most relevant genes or signatures known to be useful for predicting response to R-CHOP (Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone) in DLBCL cases. We generated a risk score that combines the International Prognostic Index with cell of origin and double expression of MYC/BCL2, and stratified the series into three groups, yielding hazard ratios from 0.15 to 5.49 for overall survival, and from 0.17 to 5.04 for progression-free survival. Group differences were highly significant (p < 0.0001), and the scoring system was applicable to younger patients (<60 years of age) and patients with advanced or localized stages of the disease. Results were validated in an independent dataset from 166 DLBCL patients treated in two distinct clinical trials. This risk score combines clinical and biological data in a model that can be used to integrate biological variables into the prognostic models for DLBCL cases.Funding information: GILEAD, Grant/Award Numbers: PIE15/0081, PI16/01294, PI17/2172, PI17/00272, PI19/00715, GL18/00019; Asociación Española Contra el Cáncer, Grant/Award Number: PROYE18054PIRI; Instituto de Salud Carlos III, Grant/Award Number: PT17/0015/0024; Xarxa de Bancs de Tumors de Catalunya; Biobank do Complexo Hospitalario Universitario de Santiago de Compostela, Grant/Award Number: PT17/0015/0002; Hospital Universitario Virgen del Rocío-Instituto de Biomedicina de Sevilla Biobank, Grant/Award Number: PT17/0015/0041; Valdecilla Biobank, Grant/Award Number: PT17/0015/0019;MD Anderson Biobank, Grant/Award Number: PT17/0015/0008; AIRC (Italian Association for Cancer Research, Milan, Italy), Grant/Award Number: 5×1000 n. 21198; Marie Skłodowska-Curie Individual Fellowship, Grant/Award Number: 882597; CIBERONC, Grant/Award Number: CB16/12/00291; Comunidad Autonoma de MadridDLBCLGene expressionImmunochemotherapyDiffuse large B-cell lymphomaPrognosi

An integrated prognostic model for diffuse large B‐cell lymphoma treated with immunochemotherapy

Abstract Diffuse large B‐cell lymphoma (DLBCL), the most frequent non‐Hodgkin's lymphoma subtype, is characterized by strong biological, morphological, and clinical heterogeneity, but patients are treated with immunochemotherapy in a relatively homogeneous way. Here, we have used a customized NanoString platform to analyze a series of 197 homogeneously treated DLBCL cases. The platform includes the most relevant genes or signatures known to be useful for predicting response to R‐CHOP (Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone) in DLBCL cases. We generated a risk score that combines the International Prognostic Index with cell of origin and double expression of MYC/BCL2, and stratified the series into three groups, yielding hazard ratios from 0.15 to 5.49 for overall survival, and from 0.17 to 5.04 for progression‐free survival. Group differences were highly significant (p < 0.0001), and the scoring system was applicable to younger patients (<60 years of age) and patients with advanced or localized stages of the disease. Results were validated in an independent dataset from 166 DLBCL patients treated in two distinct clinical trials. This risk score combines clinical and biological data in a model that can be used to integrate biological variables into the prognostic models for DLBCL cases

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts

COVID-19 in hospitalized HIV-positive and HIV-negative patients : A matched study

CatedresObjectives: We compared the characteristics and clinical outcomes of hospitalized individuals with COVID-19 with [people with HIV (PWH)] and without (non-PWH) HIV co-infection in Spain during the first wave of the pandemic. Methods: This was a retrospective matched cohort study. People with HIV were identified by reviewing clinical records and laboratory registries of 10 922 patients in active-follow-up within the Spanish HIV Research Network (CoRIS) up to 30 June 2020. Each hospitalized PWH was matched with five non-PWH of the same age and sex randomly selected from COVID-19@Spain, a multicentre cohort of 4035 patients hospitalized with confirmed COVID-19. The main outcome was all-cause in-hospital mortality. Results: Forty-five PWH with PCR-confirmed COVID-19 were identified in CoRIS, 21 of whom were hospitalized. A total of 105 age/sex-matched controls were selected from the COVID-19@Spain cohort. The median age in both groups was 53 (Q1-Q3, 46-56) years, and 90.5% were men. In PWH, 19.1% were injecting drug users, 95.2% were on antiretroviral therapy, 94.4% had HIV-RNA < 50 copies/mL, and the median (Q1-Q3) CD4 count was 595 (349-798) cells/μL. No statistically significant differences were found between PWH and non-PWH in number of comorbidities, presenting signs and symptoms, laboratory parameters, radiology findings and severity scores on admission. Corticosteroids were administered to 33.3% and 27.4% of PWH and non-PWH, respectively (P = 0.580). Deaths during admission were documented in two (9.5%) PWH and 12 (11.4%) non-PWH (P = 0.800). Conclusions: Our findings suggest that well-controlled HIV infection does not modify the clinical presentation or worsen clinical outcomes of COVID-19 hospitalization

How do women living with HIV experience menopause? Menopausal symptoms, anxiety and depression according to reproductive age in a multicenter cohort

CatedresBackground: To estimate the prevalence and severity of menopausal symptoms and anxiety/depression and to assess the differences according to menopausal status among women living with HIV aged 45-60 years from the cohort of Spanish HIV/AIDS Research Network (CoRIS). Methods: Women were interviewed by phone between September 2017 and December 2018 to determine whether they had experienced menopausal symptoms and anxiety/depression. The Menopause Rating Scale was used to evaluate the prevalence and severity of symptoms related to menopause in three subscales: somatic, psychologic and urogenital; and the 4-item Patient Health Questionnaire was used for anxiety/depression. Logistic regression models were used to estimate odds ratios (ORs) of association between menopausal status, and other potential risk factors, the presence and severity of somatic, psychological and urogenital symptoms and of anxiety/depression. Results: Of 251 women included, 137 (54.6%) were post-, 70 (27.9%) peri- and 44 (17.5%) pre-menopausal, respectively. Median age of onset menopause was 48 years (IQR 45-50). The proportions of pre-, peri- and post-menopausal women who had experienced any menopausal symptoms were 45.5%, 60.0% and 66.4%, respectively. Both peri- and post-menopause were associated with a higher likelihood of having somatic symptoms (aOR 3.01; 95% CI 1.38-6.55 and 2.63; 1.44-4.81, respectively), while post-menopause increased the likelihood of having psychological (2.16; 1.13-4.14) and urogenital symptoms (2.54; 1.42-4.85). By other hand, post-menopausal women had a statistically significant five-fold increase in the likelihood of presenting severe urogenital symptoms than pre-menopausal women (4.90; 1.74-13.84). No significant differences by menopausal status were found for anxiety/depression. Joint/muscle problems, exhaustion and sleeping disorders were the most commonly reported symptoms among all women. Differences in the prevalences of vaginal dryness (p = 0.002), joint/muscle complaints (p = 0.032), and sweating/flush (p = 0.032) were found among the three groups. Conclusions: Women living with HIV experienced a wide variety of menopausal symptoms, some of them initiated before women had any menstrual irregularity. We found a higher likelihood of somatic symptoms in peri- and post-menopausal women, while a higher likelihood of psychological and urogenital symptoms was found in post-menopausal women. Most somatic symptoms were of low or moderate severity, probably due to the good clinical and immunological situation of these women