Listas de verificación para la elaboración, tutorización y evaluación de Trabajos Fin de Grado

El Trabajo Fin de Grado (TFG) es una asignatura obligatoria en los títulos de Grado. La diversidad existente en el tipo de trabajo y la falta de mecanismos de coordinación originan disparidad de criterios en la elaboración-tutorización y evaluación-calificación de estos. El objetivo de este trabajo fue diseñar un instrumento que facilitase la realización, tutorización y evaluación de los TFG en la titulación de Grado en Fisioterapia en una universidad pública española. Se diseñaron 6 listas de verificación, una común que incluía las normas de estilo, extensión y estructura y otras 5 para los tipos de TFG contemplados: trabajo de investigación, revisión bibliográfica sistemática, proyectos de investigación, trabajo profesional (caso clínico y protocolo de intervención). Los apartados de las listas y sus epígrafes fueron consensuados entre un equipo de 11 profesores de la titulación. Las listas fueron distribuidas durante el segundo cuatrimestre de 2021 entre profesores y estudiantes de 4º curso. Disponer de listas de verificación organizadas por apartados y epígrafes facilita la elaboración, tutorización y evaluación de los TFG, minimiza la aparición de errores durante las mismas y resultan instrumentos fácilmente exportables a otras universidades y titulaciones en el ámbito de las Ciencias de la Salud

Acceptability and feasibility of a virtual community of practice to primary care professionals regarding patient empowerment: A qualitative pilot study

Background: Virtual communities of practice (vCoPs) facilitate online learning via the exchange of experiences and knowledge between interested participants. Compared to other communities, vCoPs need to overcome technological structures and specific barriers. Our objective was to pilot the acceptability and feasibility of a vCoP aimed at improving the attitudes of primary care professionals to the empowerment of patients with chronic conditions. Methods: We used a qualitative approach based on 2 focus groups: one composed of 6 general practitioners and the other of 6 practice nurses. Discussion guidelines on the topics to be investigated were provided to the moderator. Sessions were audio-recorded and transcribed verbatim. Thematic analysis was performed using the ATLAS-ti software. Results: The available operating systems and browsers and the lack of suitable spaces and time were reported as the main difficulties with the vCoP. The vCoP was perceived to be a flexible learning mode that provided up-to-date resources applicable to routine practice and offered a space for the exchange of experiences and approaches. Conclusions: The results from this pilot study show that the vCoP was considered useful for learning how to empower patients. However, while vCoPs have the potential to facilitate learning and as shown create professional awareness regarding patient empowerment, attention needs to be paid to technological and access issues and the time demands on professionals. We collected relevant inputs to improve the features, content and educational methods to be included in further vCoP implementation. Trial registration: ClinicalTrials.gov, NCT02757781. Registered on 25 April 2016.This study was financed by Instituto de Salud Carlos III and Cofinanced by Fondo Europeo de Desarrollo Regional (FEDER). Ministerio de Economía y Competitividad. Gobierno de España. (PI15/00164, PI15/00586, PI15/00566

COVID-19 Severity and Survival over Time in Patients with Hematologic Malignancies: A Population-Based Registry Study

Mortality rates for COVID-19 have declined over time in the general population, but data in patients with hematologic malignancies are contradictory. We identified independent prognostic factors for COVID-19 severity and survival in unvaccinated patients with hematologic malignancies, compared mortality rates over time and versus non-cancer inpatients, and investigated post COVID-19 condition. Data were analyzed from 1166 consecutive, eligible patients with hematologic malignancies from the population-based HEMATO-MADRID registry, Spain, with COVID-19 prior to vaccination roll-out, stratified into early (February–June 2020; n = 769 (66%)) and later (July 2020–February 2021; n = 397 (34%)) cohorts. Propensity-score matched non-cancer patients were identified from the SEMI-COVID registry. A lower proportion of patients were hospitalized in the later waves (54.2%) compared to the earlier (88.6%), OR 0.15, 95%CI 0.11–0.20. The proportion of hospitalized patients admitted to the ICU was higher in the later cohort (103/215, 47.9%) compared with the early cohort (170/681, 25.0%, 2.77; 2.01–3.82). The reduced 30-day mortality between early and later cohorts of non-cancer inpatients (29.6% vs. 12.6%, OR 0.34; 0.22–0.53) was not paralleled in inpatients with hematologic malignancies (32.3% vs. 34.8%, OR 1.12; 0.81–1.5). Among evaluable patients, 27.3% had post COVID-19 condition. These findings will help inform evidence-based preventive and therapeutic strategies for patients with hematologic malignancies and COVID-19 diagnosis.Depto. de MedicinaFac. de MedicinaTRUEFundación Madrileña de Hematología y HemoterapiaFundación Leucemia y LinfomaAsociación Madrileña de Hematología y Hemoterapiapu

Spatiotemporal Characteristics of the Largest HIV-1 CRF02_AG Outbreak in Spain: Evidence for Onward Transmissions

Background and Aim: The circulating recombinant form 02_AG (CRF02_AG) is the predominant clade among the human immunodeficiency virus type-1 (HIV-1) non-Bs with a prevalence of 5.97% (95% Confidence Interval-CI: 5.41–6.57%) across Spain. Our aim was to estimate the levels of regional clustering for CRF02_AG and the spatiotemporal characteristics of the largest CRF02_AG subepidemic in Spain.Methods: We studied 396 CRF02_AG sequences obtained from HIV-1 diagnosed patients during 2000–2014 from 10 autonomous communities of Spain. Phylogenetic analysis was performed on the 391 CRF02_AG sequences along with all globally sampled CRF02_AG sequences (N = 3,302) as references. Phylodynamic and phylogeographic analysis was performed to the largest CRF02_AG monophyletic cluster by a Bayesian method in BEAST v1.8.0 and by reconstructing ancestral states using the criterion of parsimony in Mesquite v3.4, respectively.Results: The HIV-1 CRF02_AG prevalence differed across Spanish autonomous communities we sampled from (p < 0.001). Phylogenetic analysis revealed that 52.7% of the CRF02_AG sequences formed 56 monophyletic clusters, with a range of 2–79 sequences. The CRF02_AG regional dispersal differed across Spain (p = 0.003), as suggested by monophyletic clustering. For the largest monophyletic cluster (subepidemic) (N = 79), 49.4% of the clustered sequences originated from Madrid, while most sequences (51.9%) had been obtained from men having sex with men (MSM). Molecular clock analysis suggested that the origin (tMRCA) of the CRF02_AG subepidemic was in 2002 (median estimate; 95% Highest Posterior Density-HPD interval: 1999–2004). Additionally, we found significant clustering within the CRF02_AG subepidemic according to the ethnic origin.Conclusion: CRF02_AG has been introduced as a result of multiple introductions in Spain, following regional dispersal in several cases. We showed that CRF02_AG transmissions were mostly due to regional dispersal in Spain. The hot-spot for the largest CRF02_AG regional subepidemic in Spain was in Madrid associated with MSM transmission risk group. The existence of subepidemics suggest that several spillovers occurred from Madrid to other areas. CRF02_AG sequences from Hispanics were clustered in a separate subclade suggesting no linkage between the local and Hispanic subepidemics

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

Informe sobre los planes y programas asociados a las Estrategias de Desarrollo Urbano Sostenible (EDUSI) y su vinculación con la vulnerabilidad urbana en España en el marco de los nuevos retos urbanos

Este informe analiza los planes y programas en materia de regeneración de barrios, asociados a las EDUSI en el contexto temporal que transcurre entre la aprobación de la Declaración de Toledo de 2010 y el año 2020, como fecha en la que, como consecuencia de la implementación de los Planes de Acción Local de la Agenda Urbana Española, se prevé un cambio de metodología alineada con los objetivos Europeos y la Agenda 2030. En el citado análisis se presta especial atención a la vinculación, en su caso, de dichos planes y programas con los barrios vulnerables, su continuidad con políticas de regeneración anteriores y futuras, haciendo hincapié en la Agenda Urbana Española y, de forma complementaria, a si el contenido de estas estrategias ha permitido dar cabida a las demandas evidenciadas por la pandemia COVID19

Informe sobre otros Observatorios de la Vulnerabilidad Urbana y su vinculación con las políticas urbanas de regeneración de barrios en Europa y España

Este trabajo se ha desarrollado gracias al Convenio firmado en diciembre de 2019 entre el Ministerio de Transportes, Movilidad y Agenda Urbana a través de la Dirección General de Arquitectura, Vivienda y Suelo y el Instituto Juan de Herrera para el desarrollo del Observatorio de la Vulnerabilidad Urbana en España a través de un “Informe sobre otros Observatorios de la Vulnerabilidad Urbana y su vinculación con las políticas urbanas de regeneración de barrios en Europa y España” El trabajo identifica y analiza las herramientas (observatorios y/o estrategias) para la detección y/o intervención de la vulnerabilidad y/o pobreza urbana en Europa y en España teniendo en cuenta el marco de las agendas urbanas y las políticas en materia de regeneración de barrios. Se ha realizado un inventario de las herramientas (treinta y tres casos) y luego se ha llevado a cabo un análisis más detallado de diez casos de estudio, considerando los más relevantes por la metodología de detección de la vulnerabilidad urbana que utilizan

Prevalence of Anal High-Risk Human Papilloma Virus Infection and Abnormal Anal Cytology among Women Living with HIV

Background: Women living with human immunodeficiency virus (HIV), WLWHs, are at high risk of developing anal cancer associated with high-risk human papilloma virus infection (HR-HPV). We analyzed the prevalence of anal HR-HPV infection and abnormal anal cytology in a cohort of WLWHs and assessed the risk factors for anal HR-HPV infection. Methods: We present a single-center, observational cross-sectional study. WLWHs who underwent anal cytology and anal human papilloma virus (HPV) testing were selected. High-resolution anoscopy was performed in cases of abnormal anal cytology. All suspicious lesions were biopsied. A univariate and multivariate logistic regression model was used to analyze risk factors for abnormal anal screening. The results are presented as odds ratios (ORs) and 95% confidence intervals (CIs). Results: In total, 400 WLWHs were studied. Of them, 334 met the eligibility criteria and were enrolled in the study. Abnormal anal cytology was detected in 39.5% of patients, and anal HR-HPV in 40.1%, with HPV 16 in 33 (26.6%) of them. Concomitant HR-HPV cervical infection was the only independent risk factor for HR-HPV anal infection (OR 1.67 95% CI, p < 0.001). Conclusions: WLWHs have a high prevalence of HR-HPV anal infection and anal cytologic abnormalities. HR-HPV cervical infection is the main predictor of HR-HPV anal infection

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

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