The De Jong Gierveld short scales for emotional and social loneliness: tested on data from 7 countries in the UN generations and gender surveys

Loneliness concerns the subjective evaluation of the situation individuals are involved in, characterized either by a number of relationships with friends and colleagues which is smaller than is considered desirable (social loneliness), as well as situations where the intimacy in confidant relationships one wishes for has not been realized (emotional loneliness). To identify people who are lonely direct questions are not sufficient; loneliness scales are preferred. In this article, the quality of the three-item scale for emotional loneliness and the three-item scale for social loneliness has been investigated for use in the following countries participating in the United Nations “Generations and Gender Surveys”: France, Germany, the Netherlands, Russia, Bulgaria, Georgia, and Japan. Sample sizes for the 7 countries varied between 8,158 and 12,828. Translations of the De Jong Gierveld loneliness scale have been tested using reliability and validity tests including a confirmatory factor analysis to test the two-dimensional structure of loneliness. Test outcomes indicated for each of the countries under investigation reliable and valid scales for emotional and social loneliness, respectively

Automatic Prediction of Recurrence of Major Cardiovascular Events: A Text Mining Study Using Chest X-Ray Reports

Background and Objective. Electronic health records (EHRs) contain free-text information on symptoms, diagnosis, treatment, and prognosis of diseases. However, this potential goldmine of health information cannot be easily accessed and used unless proper text mining techniques are applied. The aim of this project was to develop and evaluate a text mining pipeline in a multimodal learning architecture to demonstrate the value of medical text classification in chest radiograph reports for cardiovascular risk prediction. We sought to assess the integration of various text representation approaches and clinical structured data with state-of-the-art deep learning methods in the process of medical text mining. Methods. We used EHR data of patients included in the Second Manifestations of ARTerial disease (SMART) study. We propose a deep learning-based multimodal architecture for our text mining pipeline that integrates neural text representation with preprocessed clinical predictors for the prediction of recurrence of major cardiovascular events in cardiovascular patients. Text preprocessing, including cleaning and stemming, was first applied to filter out the unwanted texts from X-ray radiology reports. Thereafter, text representation methods were used to numerically represent unstructured radiology reports with vectors. Subsequently, these text representation methods were added to prediction models to assess their clinical relevance. In this step, we applied logistic regression, support vector machine (SVM), multilayer perceptron neural network, convolutional neural network, long short-term memory (LSTM), and bidirectional LSTM deep neural network (BiLSTM). Results. We performed various experiments to evaluate the added value of the text in the prediction of major cardiovascular events. The two main scenarios were the integration of radiology reports (1) with classical clinical predictors and (2) with only age and sex in the case of unavailable clinical predictors. In total, data of 5603 patients were used with 5-fold cross-validation to train the models. In the first scenario, the multimodal BiLSTM (MI-BiLSTM) model achieved an area under the curve (AUC) of 84.7%, misclassification rate of 14.3%, and F1 score of 83.8%. In this scenario, the SVM model, trained on clinical variables and bag-of-words representation, achieved the lowest misclassification rate of 12.2%. In the case of unavailable clinical predictors, the MI-BiLSTM model trained on radiology reports and demographic (age and sex) variables reached an AUC, F1 score, and misclassification rate of 74.5%, 70.8%, and 20.4%, respectively. Conclusions. Using the case study of routine care chest X-ray radiology reports, we demonstrated the clinical relevance of integrating text features and classical predictors in our text mining pipeline for cardiovascular risk prediction. The MI-BiLSTM model with word embedding representation appeared to have a desirable performance when trained on text data integrated with the clinical variables from the SMART study. Our results mined from chest X-ray reports showed that models using text data in addition to laboratory values outperform those using only known clinical predictors

Intracranial arteriosclerosis and the risk of dementia:A population-based cohort study

BACKGROUNDThe impact of intracranial arteriosclerosis on dementia remains largely unclear.METHODSIn 2339 stroke-free and dementia-free participants (52.2% women, mean age 69.5 years) from the general population, we assessed intracranial carotid artery calcification (ICAC) and vertebrobasilar artery calcification (VBAC) as proxy for arteriosclerosis. Associations with dementia were assessed using Cox models. In addition, indirect effects through cerebral small vessel disease (cSVD) and subcortical brain structure volumes were assessed using causal mediation analyses.RESULTSDuring a median of 13.4 years (25th–75th percentiles 9.9–14.5) of follow-up, 282 participants developed dementia. Both ICAC presence (hazard ratio [HR]: 1.53, 95% confidence interval [CI]: 1.00–2.32]) and volume (HR per standard deviation: 1.19, 95% CI: 1.01–1.40) increased dementia risk. For VBAC, severe calcifications increased dementia risk (HR for third vs first volume tertile: 1.89, 95% CI: 1.00–3.59). These effects were mediated partly through increased cSVD (percentage mediated for ICAC: 13% and VBAC: 24%).DISCUSSIONIntracranial arteriosclerosis increases the risk of dementia

Can HRCT be used as a marker of airway remodelling in children with difficult asthma?

BACKGROUND: Whole airway wall thickening on high resolution computed tomography (HRCT) is reported to parallel thickening of the bronchial epithelial reticular basement membrane (RBM) in adult asthmatics. A similar relationship in children with difficult asthma (DA), in whom RBM thickening is a known feature, may allow the use of HRCT as a non-invasive marker of airway remodelling. We evaluated this relationship in children with DA. METHODS: 27 children (median age 10.5 [range 4.1-16.7] years) with DA, underwent endobronchial biopsy from the right lower lobe and HRCT less than 4 months apart. HRCTs were assessed for bronchial wall thickening (BWT) of the right lower lobe using semi-quantitative and quantitative scoring techniques. The semi-quantitative score (grade 0-4) was an overall assessment of BWT of all clearly identifiable airways in HRCT scans. The quantitative score (BWT %; defined as [airway outer diameter - airway lumen diameter]/airway outer diameter x100) was the average score of all airways visible and calculated using electronic endpoint callipers. RBM thickness in endobronchial biopsies was measured using image analysis. 23/27 subjects performed spirometry and the relationships between RBM thickness and BWT with airflow obstruction evaluated. RESULTS: Median RBM thickness in endobronchial biopsies was 6.7(range 4.6-10.0) microm. Median qualitative score for BWT of the right lower lobe was 1(range 0-1.5) and quantitative score was 54.3 (range 48.2-65.6)%. There was no relationship between RBM thickness and BWT in the right lower lobe using either scoring technique. No relationship was found between FEV1 and BWT or RBM thickness. CONCLUSION: Although a relationship between RBM thickness and BWT on HRCT has been found in adults with asthma, this relationship does not appear to hold true in children with D

Prognostic value of heart valve calcifications for cardiovascular events in a lung cancer screening population

To assess the prognostic value of aortic valve and mitral valve/annulus calcifications for cardiovascular events in heavily smoking men without a history of cardiovascular disease. Heavily smoking men without a cardiovascular disease history who underwent non-contrast-enhanced low-radiation-dose chest CT for lung cancer screening were included. Non-imaging predictors (age, smoking status and pack-years) were collected and imaging-predictors (calcium volume of the coronary arteries, aorta, aortic valve and mitral valve/annulus) were obtained. The outcome was the occurrence of cardiovascular events. Multivariable Cox proportional-hazards regression was used to calculate hazard-ratios (HRs) with 95 % confidence interval (CI). Subsequently, concordance-statistics were calculated. In total 3111 individuals were included, of whom 186 (6.0 %) developed a cardiovascular event during a follow-up of 2.9 (Q1-Q3, 2.7-3.3) years. If aortic (n = 657) or mitral (n = 85) annulus/valve calcifications were present, cardiovascular event incidence increased to 9.0 % (n = 59) or 12.9 % (n = 11), respectively. HRs of aortic and mitral valve/annulus calcium volume for cardiovascular events were 1.46 (95 % CI, 1.09-1.84) and 2.74 (95 % CI, 0.92-4.56) per 500 mm(3). The c-statistic of a basic model including age, pack-years, current smoking status, coronary and aorta calcium volume was 0.68 (95 % CI, 0.63-0.72), which did not change after adding heart valve calcium volume. Aortic valve calcifications are predictors of future cardiovascular events. However, there was no added prognostic value beyond age, number of pack-years, current smoking status, coronary and aorta calcium volume for short term cardiovascular events

Multi‐decadal coastline dynamics in Suriname controlled by migrating subtidal mudbanks

This is the final version. Available from Wiley via the DOI in this record. DATA AVAILABILITY STATEMENT The pre-processing scripts that are used to define outliers for coastline position estimates and annual change metrics are available through Github: https://github.com/jobbo90/offshore_boundary/ releases/tag/v0.2 The reported coastline position estimates and indications of mudbank presence can be found in the online GEE repository (v02), which also includes the scripts used to derive these indicators: https://code.earthengine.google.com/?accept_repo=users/jobdevries90/ MangroMud The UAV drone datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.For the development of climate-resilient coastal management strategies, which focus on challenges in the decades to come, it is critical to incorporate spatial and temporal variability of coastline changes. This is particularly true for the mud-dominated coastline of Suriname, part of the Guianas, where migrating subtidal mudbanks cause a cyclic instability of erosion and accretion of the coast that can be directly related to interbank and bank phases. The coastline hosts extensive mangrove forests, providing valuable ecosystem services to local communities. Recent studies on mudbank dynamics in Suriname predominantly focused on large-scale trends without accounting for local variability, or on local changes considering the dynamics of a single mudbank over relatively short time scales. Here we use a remote sensing approach, with sufficient spatial and temporal resolution and full spatial and temporal coverage, to quantify the influence of mudbank migration on spatiotemporal coastline dynamics along the entire coast of Suriname. We show that migration of six to eight subtidal mudbanks in front of the Suriname coast has a strong imprint on local coastline dynamics between 1986 and 2020, with an average 32 m/yr accretion during mudbank presence and 4 m/yr retreat of the coastline during mudbank absence. Yet, coastal erosion can still occur when mudbanks are present and coastal aggregation may happen in the absence of mudbanks, exemplifying local variability and thus suggesting the importance of other drivers of coastline changes. The novel remote sensing workflow allowed us to analyse local spatial and temporal variations in the magnitude and timing of expanding and retreating trajectories. Our results demonstrate that it is essential that all coastal behaviours, including changes that cannot be explained by the migration of mudbanks, are included in multi-decadal management frameworks that try to explain current variability, and predict future coastline changes in Suriname.NWO WOTRO Joint Sustainability Development Goal Research Progra