Propuesta y aplicación de un modelo de análisis de posicionamiento académico web (A-SEO): el caso de las universidades públicas valencianas

[ES] El objetivo de este trabajo es generar un método de análisis multidimensional adaptado a la estructura universitaria para analizar el posicionamiento web y visibilidad de las universidades. Para ello, se propone el diseño de un vocabulario multidimensional y multinivel de 170 palabras clave facetadas (asignadas a 9-10 categorías) y personalizadas a cada dimensión universitaria (Investigación, Docencia y Transferencia), conformando un total de 290 consultas. La validez del vocabulario se aplica a una muestra formada por las cinco universidades públicas valencianas (UPV, UV, UJI, UA, UMH). Entre los resultados más destacados, se observa como la UPV y la UV posicionan mejor, destacando en docencia e investigación. Por el contrario, la UMH es la que peor posicionamiento web obtiene. Las universidades con menos resultados (UJI y UA) destacan por otro lado, en transferencia. El modelo de análisis se demuestra eficaz, viable, extrapolable y escalable, aun teniendo en cuenta ciertas limitaciones propias del SEO (dependencia de las herramientas utilizadas, ubicación geográfica) y del vocabulario utilizado. Con todo, el modelo ha permitido observar el posicionamiento web de las universidades desde un punto de vista multinivel, donde destacan la UPV y la UV dentro de la muestra analizada. Por último, las tipologías más destacadas son las páginas de grados, máster e investigación.[EN] The objective of this work is to generate a method of multidimensional analysis adapted to the university structure to analyze web positioning and visibility of universities. For it, the design of a multidimensional and multilevel vocabulary is proposed of 170 faceted keywords (assigned to 9-10 categories) and personalized to each university dimension (Research, Teaching and Transfer), forming a total of 290 queries. The validity of the vocabulary is applied to a sample formed by the five Valencian public universities (UPV, UV, UJI, UA, UMH). Between the most outstanding results, it is observed how the UPV and the UV position its better, standing out in teaching and research. On the contrary, the UMH is the one with the worst web positioning. Universities with fewer results (UJI and UA) stand out on the other hand in transfer. The analysis model is shown to be effective, feasible, extrapolable and scalable, even taking into account certain limitations of SEO (dependence on the tools used, geographical location) and of the vocabulary used. All in all, the model has allowed us to observe the web positioning of universities from a point of view multilevel, where the UPV and the UV within the sample stand out analyzed. Finally, the most important types are the pages of degrees, master's degree and research.Gonzalez Llinares, J. (2018). Propuesta y aplicación de un modelo de análisis de posicionamiento académico web (A-SEO): el caso de las universidades públicas valencianas. http://hdl.handle.net/10251/111668TFG

Universidades en Google: hacia un modelo de análisis multinivel del posicionamiento web académico: material complementario

Material complementario con datos brutos utilizados en artículo aceptado para su publicación en la Revista Española de Documentación Científica. Se incluye la taxonomía de consultas realizada, las combinaciones de palabras clave y consultas efectuadas, los resultados de posicionamiento de universidades públicas valencianas en Google (top 20) así como la clasificación temática del primer sitio web posicionado de cada universidad para cada consulta.Gonzalez-Llinares, J.; Font Julián, CI.; Orduña Malea, E. (2020). Universidades en Google: hacia un modelo de análisis multinivel del posicionamiento web académico: material complementario. https://doi.org/10.4995/Dataset/10251/13872

Universidades en Google: hacia un modelo de análisis multinivel del posicionamiento web académico

We propose a model of analysis of the web positioning of universities based on a vocabulary of keywords categorized according to the different university mission; it is applied to a university (Universitat Politècnica de València) to check its suitability. From a vocabulary of 164 keywords, 290 web queries were built and executed on Google, collecting the first 20 results obtained for each query. The results confirm that the universities obtain a variable web positioning according to the dimension linked to the web query and that the web pages related to teaching (especially Degrees) obtain the best ranks, even when executing web queries oriented to research. However, a low position is observed not only for the UPV, but also for all the Spanish on-site public universities (only a 27% of the Top 20 ranks correspond to these universities). It is concluded that a multilevel analysis is necessary to study the web positioning of the universities and that the proposed model is both viable and scalable. However certain limitations must be taken into account, as the dependence of the vocabulary used and the high variability of data, that must be considered in the design of this type of analysis models.Se propone un modelo de análisis del posicionamiento web de universidades basado en un vocabulario de palabras clave categorizadas según las distintas misiones universitarias, que se aplica a una universidad (Universitat Politècnica de València) para comprobar su idoneidad. A partir de un vocabulario de 164 palabras clave se construyeron 290 consultas web que fueron ejecutadas en Google, recopilando los 20 primeros resultados obtenidos para cada consulta. Los resultados confirman que las universidades obtienen un posicionamiento web variable en función de la dimensión vinculada a la consulta web y que las páginas web vinculadas a la docencia (especialmente Grados) son las que mejor posicionan, incluso para consultas web orientadas a investigación. Con todo, se observa un posicionamiento bajo no sólo para la UPV sino para las universidades públicas presenciales españolas (sólo el 27% del total de resultados en el Top 20 corresponde a alguna de estas universidades). Se concluye que el análisis multinivel es necesario para estudiar el posicionamiento web de las universidades y que el modelo propuesto es viable y escalable. No obstante, se han identificado ciertas limitaciones (dependencia del vocabulario utilizado y alta variabilidad de datos) que deben tenerse en cuenta en el diseño de este tipo de modelos de análisis

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Immunocompromised patients with acute respiratory distress syndrome: Secondary analysis of the LUNG SAFE database

Background: The aim of this study was to describe data on epidemiology, ventilatory management, and outcome of acute respiratory distress syndrome (ARDS) in immunocompromised patients. Methods: We performed a post hoc analysis on the cohort of immunocompromised patients enrolled in the Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE) study. The LUNG SAFE study was an international, prospective study including hypoxemic patients in 459 ICUs from 50 countries across 5 continents. Results: Of 2813 patients with ARDS, 584 (20.8%) were immunocompromised, 38.9% of whom had an unspecified cause. Pneumonia, nonpulmonary sepsis, and noncardiogenic shock were their most common risk factors for ARDS. Hospital mortality was higher in immunocompromised than in immunocompetent patients (52.4% vs 36.2%; p &lt; 0.0001), despite similar severity of ARDS. Decisions regarding limiting life-sustaining measures were significantly more frequent in immunocompromised patients (27.1% vs 18.6%; p &lt; 0.0001). Use of noninvasive ventilation (NIV) as first-line treatment was higher in immunocompromised patients (20.9% vs 15.9%; p = 0.0048), and immunodeficiency remained independently associated with the use of NIV after adjustment for confounders. Forty-eight percent of the patients treated with NIV were intubated, and their mortality was not different from that of the patients invasively ventilated ab initio. Conclusions: Immunosuppression is frequent in patients with ARDS, and infections are the main risk factors for ARDS in these immunocompromised patients. Their management differs from that of immunocompetent patients, particularly the greater use of NIV as first-line ventilation strategy. Compared with immunocompetent subjects, they have higher mortality regardless of ARDS severity as well as a higher frequency of limitation of life-sustaining measures. Nonetheless, nearly half of these patients survive to hospital discharge. Trial registration: ClinicalTrials.gov, NCT02010073. Registered on 12 December 2013

Outcomes of Patients Presenting with Mild Acute Respiratory Distress Syndrome Insights from the LUNG SAFE Study

BACKGROUND: Patients with initial mild acute respiratory distress syndrome are often underrecognized and mistakenly considered to have low disease severity and favorable outcomes. They represent a relatively poorly characterized population that was only classified as having acute respiratory distress syndrome in the most recent definition. Our primary objective was to describe the natural course and the factors associated with worsening and mortality in this population. METHODS: This study analyzed patients from the international prospective Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE) who had initial mild acute respiratory distress syndrome in the first day of inclusion. This study defined three groups based on the evolution of severity in the first week: "worsening" if moderate or severe acute respiratory distress syndrome criteria were met, "persisting" if mild acute respiratory distress syndrome criteria were the most severe category, and "improving" if patients did not fulfill acute respiratory distress syndrome criteria any more from day 2. RESULTS: Among 580 patients with initial mild acute respiratory distress syndrome, 18% (103 of 580) continuously improved, 36% (210 of 580) had persisting mild acute respiratory distress syndrome, and 46% (267 of 580) worsened in the first week after acute respiratory distress syndrome onset. Global in-hospital mortality was 30% (172 of 576; specifically 10% [10 of 101], 30% [63 of 210], and 37% [99 of 265] for patients with improving, persisting, and worsening acute respiratory distress syndrome, respectively), and the median (interquartile range) duration of mechanical ventilation was 7 (4, 14) days (specifically 3 [2, 5], 7 [4, 14], and 11 [6, 18] days for patients with improving, persisting, and worsening acute respiratory distress syndrome, respectively). Admissions for trauma or pneumonia, higher nonpulmonary sequential organ failure assessment score, lower partial pressure of alveolar oxygen/fraction of inspired oxygen, and higher peak inspiratory pressure were independently associated with worsening. CONCLUSIONS: Most patients with initial mild acute respiratory distress syndrome continue to fulfill acute respiratory distress syndrome criteria in the first week, and nearly half worsen in severity. Their mortality is high, particularly in patients with worsening acute respiratory distress syndrome, emphasizing the need for close attention to this patient population.status: publishe

Outcome of acute hypoxaemic respiratory failure: insights from the LUNG SAFE Study

Background: Current incidence and outcome of patients with acute hypoxaemic respiratory failure requiring mechanical ventilation in the intensive care unit (ICU) are unknown, especially for patients not meeting criteria for acute respiratory distress syndrome (ARDS). Methods: An international, multicentre, prospective cohort study of patients presenting with hypoxaemia early in the course of mechanical ventilation, conducted during four consecutive weeks in the winter of 2014 in 459 ICUs from 50 countries (LUNG SAFE). Patients were enrolled with arterial oxygen tension/inspiratory oxygen fraction ratio ≤300 mmHg, new pulmonary infiltrates and need for mechanical ventilation with a positive end-expiratory pressure of ≥5 cmH2O. ICU prevalence, causes of hypoxaemia, hospital survival and factors associated with hospital mortality were measured. Patients with unilateral versus bilateral opacities were compared. Findings: 12 906 critically ill patients received mechanical ventilation and 34.9% with hypoxaemia and new infiltrates were enrolled, separated into ARDS (69.0%), unilateral infiltrate (22.7%) and congestive heart failure (CHF; 8.2%). The global hospital mortality was 38.6%. CHF patients had a mortality comparable to ARDS (44.1% versus 40.4%). Patients with unilateral-infiltrate had lower unadjusted mortality, but similar adjusted mortality compared to those with ARDS. The number of quadrants on chest imaging was associated with an increased risk of death. There was no difference in mortality comparing patients with unilateral-infiltrate and ARDS with only two quadrants involved. Interpretation: More than one-third of patients receiving mechanical ventilation have hypoxaemia and new infiltrates with a hospital mortality of 38.6%. Survival is dependent on the degree of pulmonary involvement whether or not ARDS criteria are reached

Mechanical ventilation in patients with cardiogenic pulmonary edema: a sub-analysis of the LUNG SAFE study

Background: Patients with acute respiratory failure caused by cardiogenic pulmonary edema (CPE) may require mechanical ventilation that can cause further lung damage. Our aim was to determine the impact of ventilatory settings on CPE mortality. Methods: Patients from the LUNG SAFE cohort, a multicenter prospective cohort study of patients undergoing mechanical ventilation, were studied. Relationships between ventilatory parameters and outcomes (ICU discharge/hospital mortality) were assessed using latent mixture analysis and a marginal structural model. Results: From 4499 patients, 391 meeting CPE criteria (median age 70 [interquartile range 59-78], 40% female) were included. ICU and hospital mortality were 34% and 40%, respectively. ICU survivors were younger (67 [57-77] vs 74 [64-80] years, p &lt; 0.001) and had lower driving (12 [8-16] vs 15 [11-17] cmH2O, p &lt; 0.001), plateau (20 [15-23] vs 22 [19-26] cmH2O, p &lt; 0.001) and peak (21 [17-27] vs 26 [20-32] cmH2O, p &lt; 0.001) pressures. Latent mixture analysis of patients receiving invasive mechanical ventilation on ICU day 1 revealed a subgroup ventilated with high pressures with lower probability of being discharged alive from the ICU (hazard ratio [HR] 0.79 [95% confidence interval 0.60-1.05], p = 0.103) and increased hospital mortality (HR 1.65 [1.16-2.36], p = 0.005). In a marginal structural model, driving pressures in the first week (HR 1.12 [1.06-1.18], p &lt; 0.001) and tidal volume after day 7 (HR 0.69 [0.52-0.93], p = 0.015) were related to survival. Conclusions: Higher airway pressures in invasively ventilated patients with CPE are related to mortality. These patients may be exposed to an increased risk of ventilator-induced lung injury. Trial registration Clinicaltrials.gov NCT02010073

Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis

International audienceTwo acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. Methods: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. Findings: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90–0·95) in EARLI and 0·88 (0·84–0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81–0·94] vs 0·92 [0·88–0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). Interpretation: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. Funding: US National Institutes of Health and European Society of Intensive Care Medicine