La Formación de Utrillas en el borde sur de la cuenca Vasco-Cantábrica: aspectos estratigráficos, mineralógicos y genéticos

The Utrillas formation, located in the southem border of the Basque-Cantabrian basin, is mainly composed of sandy materials deposited in a fluvial environment. Two informal units have been distinguished due to field data: a lower coarse-grained unit, interpreted as braider river channel-fills, and a upper fine-grained unit which suggests a meandering river environment. Mineralogy consists of quartz and phyllosilicates, with minor amounts of feldspars. The analysis of tourmalines has pointed two possible sources for these sediments: granitoids and low grade-metasediments. The identified clay minerals are mica and kaolinite. Texturals observations have pointed out an inherited origin for mica, while kaolinite is partly inherited and partly authigenic. This authigenic origin seems to be associated with the alteration of potassic feldspars during the stage of late diagenesis (telodiagenesis).La Formación de Utrillas, aflorante en el borde sur de la cuenca Vasco-Cantábrica, está formada por materiales mayoritariamente areniscosos depositados en un ambiente fluvial. Los datos de campo han permitido distinguir de una manera informal dos unidades: una inferior de granulometría gruesa, representativa de un relleno de canal de tipo trenzado, y una superior más fina que sugiere un entorno de río meandriforme. La mineralogía está compuesta por cuarzo y filosilicatos, con cantidades menores de feldespatos. Como mineral accesorio aparece la turmalina, cuyo análisis ha permitido identificar dos posibles fuentes para los sedimentos: granitoides y metasedimentos de bajo grado. Los minerales de la arcilla presentes son exclusivamente la mica y la caolinita. A partir de criterios texturales, se ha constatado que la mica es de origen heredado, mientras que la caolinita es en parte heredada o bien autigénica, estando asociada a la alteración de feldespato potásico en una etapa de diagénesis tardía (telodiagénesis)

COPD classification models and mortality prediction capacity

Our aim was to assess the impact of comorbidities on existing COPD prognosis scores. Patients and methods: A total of 543 patients with COPD (FEV1 < 80% and FEV1/ FVC <70%) were included between January 2003 and January 2004. Patients were stable for at least 6 weeks before inclusion and were followed for 5 years without any intervention by the research team. Comorbidities and causes of death were established from medical reports or information from primary care medical records. The GOLD system and the body mass index, obstruction, dyspnea and exercise (BODE) index were used for COPD classification. Patients were also classified into four clusters depending on the respiratory disease and comorbidities. Cluster analysis was performed by combining multiple correspondence analyses and automatic classification. Receiver operating characteristic curves and the area under the curve (AUC) were calculated for each model, and the DeLong test was used to evaluate differences between AUCs. Improvement in prediction ability was analyzed by the DeLong test, category-free net reclassification improvement and the integrated discrimination index. Results: Among the 543 patients enrolled, 521 (96%) were male, with a mean age of 68 years, mean body mass index 28.3 and mean FEV1% 55%. A total of 167 patients died during the study follow-up. Comorbidities were prevalent in our cohort, with a mean Charlson index of 2.4. The most prevalent comorbidities were hypertension, diabetes mellitus and cardiovascular diseases. On comparing the BODE index, GOLDABCD, GOLD2017 and cluster analysis for pre-dicting mortality, cluster system was found to be superior compared with GOLD2017 (0.654 vs 0.722, P=0.006), without significant differences between other classification models. When cardiovascular comorbidities and chronic renal failure were added to the existing scores, their prognostic capacity was statistically superior (P<0.001). Conclusion: Comorbidities should be taken into account in COPD management scores due to their prevalence and impact on mortalit

A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: A cohort study

Background: Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD. Methods: We conducted a prospective cohort study including participants from 16 hospitals in Spain. COPD patients with an exacerbation attending the emergency department (ED) of any of the hospitals between June 2008 and September 2010 were recruited. Patients were randomly divided into derivation (50 %) and validation samples (50 %). A CART based on a recursive partitioning algorithm was created in the derivation sample and applied to the validation sample. Results: Two thousand four hundred eighty-seven patients, 1252 patients in the derivation sample and 1235 in the validation sample, were enrolled in the study. Based on the results of the univariate analysis, five variables (baseline dyspnea, cardiac disease, the presence of paradoxical breathing or use of accessory inspiratory muscles, age, and Glasgow Coma Scale score) were used to build the CART. Mortality rates 30 days after discharge ranged from 0 % to 55 % in the five CART classes. The lowest mortality rate was for the branch composed of low baseline dyspnea and lack of cardiac disease. The highest mortality rate was in the branch with the highest baseline dyspnea level, use of accessory inspiratory muscles or paradoxical breathing upon ED arrival, and Glasgow score <15. The area under the receiver-operating curve (AUC) in the derivation sample was 0.835 (95 % CI: 0.783, 0.888) and 0.794 (95 % CI: 0.723, 0.865) in the validation sample. CART was improved to predict 60-days mortality risk by adding the Charlson Comorbidity Index, reaching an AUC in the derivation sample of 0.817 (95 % CI: 0.776, 0.859) and 0.770 (95 % CI: 0.716, 0.823) in the validation sample. Conclusions: We identified several easy-to-determine variables that allow clinicians to classify eCOPD patients by short term mortality risk, which can provide useful information for establishing appropriate clinical care. Trial registration: NCT02434536

Combining statistical techniques to predict post-surgical risk of 1-year mortality for patients with colon cancer

Introduction: Colorectal cancer is one of the most frequently diagnosed malignancies and a common cause of cancer-related mortality. The aim of this study was to develop and validate a clinical predictive model for1-year mortality among patients with colon cancer who survive for at least 30 days after surgery. Methods: Patients diagnosed with colon cancer who had surgery for the first time and who survived 30 days after the surgery were selected prospectively. The outcome was mortality within 1 year. Random forest, genetic algorithms and classification and regression trees were combined in order to identify the variables and partition points that optimally classify patients by risk of mortality. The resulting decision tree was categorized into four risk categories. Split-sample and bootstrap validation were performed. Results: A total of 1945 patients were enrolled in the study. The variables identified as the main predictors of 1-year mortality were presence of residual tumour, ASA risk score, pathological tumour staging, Charlson comorbidity index, intraoperative complications, adjuvant chemotherapy and recurrence of tumour. The model was internally validated; the area under the curve (AUC) was 0.896 in the derivation sample and 0.835 in the validation sample. Risk categorization leads to AUC values of 0.875 and 0.832 in the derivation and validation samples, respectively. Optimal cut-off point of estimated risk had a sensitivity of 0.889 and a specificity of 0.758. Conclusions: The decision-tree was a simple, interpretable, valid and accurate prediction rule of 1-year mortality among colon cancer patients who survived for at least 30 days after surgery.Instituto de Salud Carlos III (PS09/00314, PS09/00910, PS09/00746, PS09/00805, PI09/90460, PI09/90490, PI09/90453, PI09/90441, PI09/90397 and the thematic networks REDISSEC - Red de Investigación en Servicios de Salud en Enfermedades Crónicas), co-funded by European Regional Development Fund/European Social Fund (ERDF/ESF "Investing in your future"); Research Committee of the Hospital Galdakao Department of Health and the Department of Education, Language Policy and Culture from the Basque Government (2010111098, IT620-13) MINECO and FEDER (MTM2013-40941-P, MTM2016-74931-P)

Chronic obstructive pulmonary disease subtypes. transitions over time

Background Although subtypes of chronic obstructive pulmonary disease are recognized, it is unknown what happens to these subtypes over time. Our objectives were to assess the stability of cluster-based subtypes in patients with stable disease and explore changes in clusters over 1 year. Methods Multiple correspondence and cluster analysis were used to evaluate data collected from 543 stable patients included consecutively from 5 respiratory outpatient clinics. Results Four subtypes were identified. Three of them, A, B, and C, had marked respiratory profiles with a continuum in severity of several variables, while the fourth, subtype D, had a more systemic profile with intermediate respiratory disease severity. Subtype A was associated with less dyspnea, better health-related quality of life and lower Charlson comorbidity scores, and subtype C with the most severe dyspnea, and poorer pulmonary function and quality of life, while subtype B was between subtypes A and C. Subtype D had higher rates of hospitalization the previous year, and comorbidities. After 1 year, all clusters remained stable. Generally, patients continued in the same subtype but 28% migrated to another cluster. Together with movement across clusters, patients showed changes in certain characteristics (especially exercise capacity, some variables of pulmonary function and physical activity) and changes in outcomes (quality of life, hospitalization and mortality) depending on the new cluster they belonged to Conclusions Chronic obstructive pulmonary disease clusters remained stable over 1 year. Most patients stayed in their initial subtype cluster, but some moved to another subtype and accordingly had different outcomes

Pathogenic Potential of Hic1-Expressing Cardiac Stromal Progenitors

The cardiac stroma contains multipotent mesenchymal progenitors. However, lineage relationships within cardiac stromal cells are poorly defined. Here, we identified heart-resident PDGFRa(+) SCA-1(+) cells as cardiac fibro/adipogenic progenitors (cFAPs) and show that they respond to ischemic damage by generating fibrogenic cells. Pharmacological blockade of this differentiation step with an anti-fibrotic tyrosine kinase inhibitor decreases post-myocardial infarction (post-MI) remodeling and leads to improvement in cardiac function. In the undamaged heart, activation of cFAPs through lineage-specific deletion of the gene encoding the quiescence-associated factor HIC1 reveals additional pathogenic potential, causing fibrofatty infiltration within the myocardium and driving major pathological features pathognomonic in arrhythmogenic cardiomyopathy (AC). In this regard, cFAPs contribute to multiple pathogenic cell types within cardiac tissue and therapeutic strategies aimed at modifying their activity are expected to have tremendous benefit for the treatment of diverse cardiac diseases

Impact of outdoor air pollution on severity and mortality in COVID-19 pneumonia

The relationship between exposure to air pollution and the severity of coronavirus disease 2019 (COVID-19) pneumonia and other outcomes is poorly understood. Beyond age and comorbidity, risk factors for adverse outcomes including death have been poorly studied. The main objective of our study was to examine the relationship between exposure to outdoor air pollution and the risk of death in patients with COVID-19 pneumonia using individual-level data. The secondary objective was to investigate the impact of air pollutants on gas exchange and systemic inflammation in this disease. This cohort study included 1548 patients hospitalised for COVID-19 pneumonia between February and May 2020 in one of four hospitals. Local agencies supplied daily data on environmental air pollutants ($PM_{10}$, $PM_{2.5}$, $O_3$, $NO_2$, $NO$ and $NO_X$) and meteorological conditions (temperature and humidity) in the year before hospital admission (from January 2019 to December 2019). Daily exposure to pollution and meteorological conditions by individual postcode of residence was estimated using geospatial Bayesian generalised additive models. The influence of air pollution on pneumonia severity was studied using generalised additive models which included: age, sex, Charlson comorbidity index, hospital, average income, air temperature and humidity, and exposure to each pollutant. Additionally, generalised additive models were generated for exploring the effect of air pollution on C-reactive protein (CRP) level and Sp$O_2$/Fi$O_2$ at admission. According to our results, both risk of COVID-19 death and CRP level increased significantly with median exposure to $PM_{10}$, $NO_2$, $NO$ and $NO_X$, while higher exposure to $NO_2$, $NO$ and $NO_X$ was associated with lower Sp$O_2$/Fi$O_2$ ratios. In conclusion, after controlling for socioeconomic, demographic and health-related variables, we found evidence of a significant positive relationship between air pollution and mortality in patients hospitalised for COVID-19 pneumonia. Additionally, inflammation (CRP) and gas exchange (Sp$O_2$/Fi$O_2$) in these patients were significantly related to exposure to air pollution

Relationships between quality of life and family function in caregiver

<p>Abstract</p> <p>Background</p> <p>There are caregivers who see their quality of life (QoL) impaired due to the demands of their caregiving tasks, while others manage to adapt and overcome the crises successfully. The influence of the family function in the main caregiver's situation has not been the subject of much evaluation. The aim of this study is to analyse the relationship between the functionality of the family and the QoL of caregivers of dependent relatives.</p> <p>Methods</p> <p>We conducted a cross-sectional study including 153 caregivers. Setting: Two health centers in the city of Salamanca(Spain). Caregiver variables analysed: demographic characteristics, care recipient features; family functionality (Family APGAR-Q) and QoL (Ruiz-Baca-Q) perceived by the caregiver. Five multiple regressions are performed considering global QoL and each of the four QoL dimensions as dependent variables. The Canonical Correspondence Analysis (CCA) was used to study the influence of the family function questionnaire on QoL.</p> <p>Results</p> <p>Family function is the only one of the variables evaluated that presented an association both with global QoL and with each of the four individual dimensions (p < 0.05). Using the CCA, we found that the physical and mental well-being dimensions are the ones which present a closer relationship with family functionality, while social support is the quality dimension that is least influenced by the Family APGAR-Q.</p> <p>Conclusion</p> <p>We find an association between family functionality and the caregiver's QoL. This relation holds for both the global measure of QoL and each of its four individual dimensions.</p