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Concreteness of words has been studied extensively in psycholinguistic literature. A number of datasets have been created with average values for perceived concreteness of words. We show that we can train a regression model on these data, using word embeddings and morphological features, that can predict these concreteness values with high accuracy. We evaluate the model on 7 publicly available datasets. Only for a few small subsets of these datasets prediction of concreteness values are found in the literature. Our results clearly outperform the reported results for these datasets.
The Logical Observation Identifiers, Names and Codes (LOINC) is a common terminology used for standardizing laboratory terms. Within the consortium of the HiGHmed project, LOINC is one of the central terminologies used for health data sharing across all university sites. Therefore, linking the LOINC codes to the site-specific tests and measures is one crucial step to reach this goal. In this work we report our ongoing efforts in implementing LOINC to our laboratory information system and research infrastructure, as well as our challenges and the lessons learned. 407 local terms could be mapped to 376 LOINC codes of which 209 are already available to routine laboratory data. In our experience, mapping of local terms to LOINC is a widely manual and time consuming process for reasons of language and expert knowledge of local laboratory procedures.
Background
Chronic obstructive pulmonary disease (COPD) causes significant morbidity and mortality worldwide. Estimation of incidence, prevalence and disease burden through routine insurance data is challenging because of under-diagnosis and under-treatment, particularly for early stage disease in health care systems where outpatient International Classification of Diseases (ICD) diagnoses are not collected. This poses the question of which criteria are commonly applied to identify COPD patients in claims datasets in the absence of ICD diagnoses, and which information can be used as a substitute. The aim of this systematic review is to summarize previously reported methodological approaches for the identification of COPD patients through routine data and to compile potential criteria for the identification of COPD patients if ICD codes are not available.
Methods
A systematic literature review was performed in Medline via PubMed and Google Scholar from January 2000 through October 2018, followed by a manual review of the included studies by at least two independent raters. Study characteristics and all identifying criteria used in the studies were systematically extracted from the publications, categorized, and compiled in evidence tables.
Results
In total, the systematic search yielded 151 publications. After title and abstract screening, 38 publications were included into the systematic assessment. In these studies, the most frequently used (22/38) criteria set to identify COPD patients included ICD codes, hospitalization, and ambulatory visits. Only four out of 38 studies used methods other than ICD coding. In a significant proportion of studies, the age range of the target population (33/38) and hospitalization (30/38) were provided. Ambulatory data were included in 24, physician claims in 22, and pharmaceutical data in 18 studies. Only five studies used spirometry, two used surgery and one used oxygen therapy.
Conclusions
A variety of different criteria is used for the identification of COPD from routine data. The most promising criteria set in data environments where ambulatory diagnosis codes are lacking is the consideration of additional illness-related information with special attention to pharmacotherapy data. Further health services research should focus on the application of more systematic internal and/or external validation approaches.
Objective
To revise the German guidelines and recommendations for ensuring Good Epidemiological Practice (GEP) that were developed in 1999 by the German Society for Epidemiology (DGEpi), evaluated and revised in 2004, supplemented in 2008, and updated in 2014.
Methods
The executive board of the DGEpi tasked the third revision of the GEP. The revision was arrived as a result of a consensus-building process by a working group of the DGEpi in collaboration with other working groups of the DGEpi and with the German Association for Medical Informatics, Biometry and Epidemiology, the German Society of Social Medicine and Prevention (DGSMP), the German Region of the International Biometric Society (IBS-DR), the German Technology, Methods and Infrastructure for Networked Medical Research (TMF), and the German Network for Health Services Research (DNVF). The GEP also refers to related German Good Practice documents (e.g. Health Reporting, Cartographical Practice in the Healthcare System, Secondary Data Analysis).
Results
The working group modified the 11 guidelines (after revision: 1 ethics, 2 research question, 3 study protocol and manual of operations, 4 data protection, 5 sample banks, 6 quality assurance, 7 data storage and documentation, 8 analysis of epidemiological data, 9 contractual framework, 10 interpretation and scientific publication, 11 communication and public health) and modified and supplemented the related recommendations. All participating scientific professional associations adopted the revised GEP.
Conclusions
The revised GEP are addressed to everyone involved in the planning, preparation, execution, analysis, and evaluation of epidemiological research, as well as research institutes and funding bodies.
Background: Compromised immune function, associated with human immune deficiency virus (HIV) infection, is improved by antiretroviral therapy (ART) which also decreases bone mineral density (BMD), and possibly the quality of life (QoL). However, physical (aerobic/resistance) exercises, were reported to induce reverse effects in uninfected individuals and were appraised in the literature for evidence of similar benefits in people living with HIV/AIDS(PLWHA). The main study objective was to evaluate the impact of physical (aerobic and resistance) exercises on CD4+ count,
BMD and QoL in PLWHA.
Methods: A systematic review was conducted using the Cochrane Collaboration protocol. Searching databases, up to June 2017, only randomized control trials investigating the effects of either aerobic, resistance or a combination of both exercise types with a control/other intervention(s) for a period of at least 4 weeks among adults living with HIV, were included. Two independent reviewers determined the eligibility of the studies. Data were extracted and risk of bias (ROB) was assessed with the Cochrane Collaboration ROB tool. Meta-analyses were conducted using random effect models using the Review Manager (RevMan) computer software.
Results: Nineteen studies met inclusion criteria(n = 491 participants at study completion) comprising male and female with age range 22–66 years. Two meta-analyses across 13 sub-group comparisons were performed. However, there were no RCTs on the impact of physical exercises on BMD in PLWHA. The result showed no significant change in CD4+ count unlike a significant effect of 5.04 point (95%CI:-8.49,-3.74,p = 0.00001) for role activity limitation due to physical health (QoL sub-domain). Overall, the GRADE evidence for this review was of moderate quality.
Conclusions: There was evidence that engaging in moderate intensity aerobic exercises (55–85% Maximum heart rate-MHR), for 30–60 min, two to five times/week for 6–24 weeks significantly improves role activity limitation due to physical health problems, otherwise physical(aerobic or/and resistance) exercises have no significant effects on CD4+ count and other domains of QoL. Also, there is lack of evidence on the impact of exercises on BMD in PLWHA due to the paucity of RCTs. The moderate grade evidence for this review suggests that further research may likely have an important impact on our confidence in the estimate of effects and may change the estimate.
Background: Available preliminary data on menopause does not relate changes in body fat mass (BFM) and handgrip strength (HGS) (an indicator of body/muscle strength) to gait parameters.
Objective: To determine the relationship between BFM, HGS and gait parameters, namely, stride length (SL) (an indicator of walking balance/postural stability), stride frequency (SF), and velocity (V) (gait out- put), to guide gait training.
Methods: Ninety consenting (45 postmenopausal and 45 premenopausal) female staffof the University of Nigeria Teaching Hospital, Enugu, were randomly selected and assessed for BFM and HGS with a hydration monitor and dynamometer, respectively, in an observational study. The mean of 2 trials of the number of steps and time taken to cover a 10-m distance at normal speed was used to calculate SF, SL, and V. Data were analyzed using an independent t test and a Pearson correlation coefficient at P < 0.05.
Results: Premenopausal (BFM = 42.93% [12.61%], HGS = 27.89 [7.52] kg, stride ratio = 1.43, and velocity = 1.04 [0.01] m/sec) and postmenopausal (BFM = 41.55% [12.71%], HGS = 30.91 [7.07] kg, stride ratio = 1.44, and velocity = 1.06 [0.01] m/sec) women showed no significant differences in gait output/velocity ( t = 0.138; P = 0.89; d = 0.029). At postmenopause, BFM was significantly and negatively ( r = –0.369; r 2 = 0.1362; P = 0.013) correlated with SL, whereas HGS was positively and significantly ( r = 0.323; r 2 = 0.104; P = 0.030) correlated with gait output at premenopause.
Conclusions: BFM may adversely influence walking balance at postmenopause, whereas HGS may enhance gait output at premenopause but not postmenopause. Therefore, muscle strengthening alone may not enhance gait output in postmenopausal women without balance training.
Background
In the past years, it became apparent that health status and performance differ considerably within dairy farms in Northern Germany. In order to obtain clues with respect to possible causes of these differences, a case-control study was performed. Case farms, which showed signs of health and performance problems, and control farms, which had none of these signs, were compared. Risk factors from different areas such as health management, housing, hygiene and nutrition were investigated as these are known to be highly influential. The aim of this study was to identify major factors within these areas that have the strongest association with health and performance problems of dairy herds in Northern Germany.
Results
In the final model, a lower energy density in the roughage fraction of the diet, more pens with dirty lying areas and a low ratio of cows per watering spaces were associated with a higher risk for herd health problems. Moreover, case farms were affected by infections with intestinal parasites, lungworms, liver flukes and Johne’s Disease numerically more often than control farms. Case farms more often had pens with raised cubicles compared to the deep bedded stalls or straw yards found in control farms. In general, the hygiene of the floors and beddings was worse in case farms. Concerning nutrition, the microbiological and sensory quality of the provided silages was often insufficient, even in control farms. Less roughage was provided to early lactating cows and the feed was pushed to the feeding fence less frequently in case farms than in control farms.
Conclusions
The results show that milk yield and health status were associated with various factors from different areas stressing the importance of all aspects of management for good animal health and performance. Moreover, this study confirmed well-known risk factors for health problems and performance losses. These should better be taken heed of in herd health management.
In the present paper we sketch an automated procedure to compare different versions of a contract. The contract texts used for this purpose are structurally differently composed PDF files that are converted into structured XML files by identifying and classifying text boxes. A classifier trained on manually annotated contracts achieves an accuracy of 87% on this task. We align contract versions and classify aligned text fragments into different similarity classes that enhance the manual comparison of changes in document versions. The main challenges are to deal with OCR errors and different layout of identical or similar texts. We demonstrate the procedure using some freely available contracts from the City of Hamburg written in German. The methods, however, are language agnostic and can be applied to other contracts as well.
For the analysis of contract texts, validated model texts, such as model clauses, can be used to identify used contract clauses. This paper investigates how the similarity between titles of model clauses and headings extracted from contracts can be computed, and which similarity measure is most suitable for this. For the calculation of the similarities between title pairs we tested various variants of string similarity and token based similarity. We also compare two additional semantic similarity measures based on word embeddings using pre-trained embeddings and word embeddings trained on contract texts. The identification of the model clause title can be used as a starting point for the mapping of clauses found in contracts to verified clauses.
Due to demographic change the number of serious kidney diseases and thus required transplantations will increase. The increased demand for donor organs and a decreasing supply of these organs underline the necessity for effective early rejection diagnostic measures to improve the lifetime of transplants. Expert systems might improve rejection diagnostics but for the development of such systems data models are needed that encompass the relevant information to enable optimal data aggregation and evaluation. Results of a literature review concerning published data models and information systems concerned with kidney transplant rejection diagnostic lead to a set of data elements even if no papers could be identified that publish data models explicitly.