Aggressive incidents occur frequently in health care facilities, such as psychiatric care and forensic psychiatric hospitals. Previous research suggests that civil psychiatric inpatients may display more aggression than forensic inpatients. However, there is a lack of research comparing these groups on the incident severity, even though both frequency and severity of aggression influence the impact on staff members. The purpose of this study is to compare the frequency and severity of inpatient aggression caused by forensic and civil psychiatric inpatients in the same Dutch forensic psychiatric hospital. Data on aggressive incidents occurring between January 1, 2014, and December 31, 2017, were gathered from hospital files and analyzed using the Modified Overt Aggression Scale, including sexual aggression (MOAS+). Multilevel random intercept models were used to analyze differences between forensic and civil psychiatric patients in severity of aggressive incidents. In all, 3,603 aggressive incidents were recorded, caused by 344 different patients. Civil psychiatric patients caused more aggressive incidents than forensic patients and female patients caused more inpatient aggression compared with male patients. Female forensic patients were found to cause the most severe incidents, followed by female civil psychiatric patients. Male forensic patients caused the least severe incidents. The findings have important clinical implications, such as corroborating the need for an intensive treatment program for aggressive and disruptive civil psychiatric patients, as well as emphasizing the importance of gender-responsive treatment
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Background Children with speech sound disorders (SSD) are at higher risk of communication breakdown, but the impact of having an SSD may vary from child to child. Determining the severity of SSD helps speech-language therapists (SLTs) to recognise the extent of the problem and to identify and prioritise children who require intervention. Aims This study aimed to identify severity factors for SSD in order to develop a multifactorial Speech Sound Disorder Severity Construct (SSDSC) using SLTs’ views and the International Classification of Functioning, Disability and Health (ICF). Method In an explorative five-staged qualitative study, the research question was answered: ‘How do SLTs determine the severity of SSD in children?’. A total of 91 SLTs from The Netherlands participated in data collection and analysis. The iterative process included three different qualitative research methodologies (thematic analysis [TA], constructivist grounded theory [CGT] and content analysis [CA]) to ensure validation of the results by means of method triangulation. Results SLTs considered nine themes: intelligibility, speech accuracy, persistence, the child's perception, impact, communicative participation, concomitant factors, professional point of view, and environmental factors. The themes were summarised in three main severity factors: (I) Speech accuracy, (II) The child's perception of the impact of their speech, and (III) Intelligibility in communication. Other severity factors were concomitant factors and impact. Expertise and support were identified as facilitators or barriers that may worsen or relieve the severity of SSD. Conclusions This study highlights the need for SLTs to rethink how they think about severity as a simplistic construct reflecting only speech accuracy. It is recommended that a broader holistic approach to measuring severity is adopted.
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Purpose: The aim of this study was to evaluate how Scheimpflug-derived parameters of eyes with Fuchs endothelial corneal dystrophy (FECD) are influenced by Descemet membrane endothelial keratoplasty (DMEK) depending on FECD severity and the presence of subclinical edema. Methods: A retrospective cohort study including 115 eyes (115 patients) that underwent DMEK for FECD and a control group of 27 eyes with nonpathological corneas was conducted. Preoperative and 6 months postoperative Scheimpflug imaging was used to analyze pachymetry, presence of tomographic features (loss of isopachs/displacement of the thinnest point/focal posterior depression), and corneal backscatter. FECD severity was based on the modified Krachmer scale and the absence/presence of subclinical edema. Results: Scheimpflug-derived pachymetry, tomographic, and corneal backscatter parameters were correlated with FECD severity, and all changed from preoperatively to postoperatively (all P < 0.05). Postoperative central corneal thickness, anterior and posterior corneal backscatter, and presence of focal posterior depression remained different from the control group (all P < 0.05). Of eyes without preoperative clinical edema (n = 75), 18.7% showed 0 or 1 tomographic feature (no edema group) and 82.4% had 2 or 3 features (subclinical edema group). Compared with the control group, postoperative best-corrected visual acuity for the “no edema” group did not differ (0.03 ± 0.12 vs. −0.02 ± 0.08 logarithm of the minimum angle of resolution, P = 0.150) but was worse for the subclinical edema group (0.06 ± 0.08 vs. −0.02 ± 0.08 logarithm of the minimum angle of resolution, P = 0.001). Conclusions: For eyes without preoperative edema, more parameters reversed back to ‘normal’ levels than for eyes with (sub)clinical edema. Although most analyzed parameters correlated with FECD severity, corneal tomography might be best suited for objective grading of disease severity to aid in surgical decision-making.
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Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
In the SensEQuake project, the Research Centre for Built Environment NoorderRuimte of Hanze University of Applied Sciences, StabiAlert, Target Holding and NHL Stenden Leeuwarden are investigating the following question:How can we provide relevant and understandable information to support decision makers when an earthquake has occurred?In case of a crisis such as an earthquake, parties such as the provincial government, large company sites, airports or hospitals need information on the scope and severity of the effect of the crisis.Systematic updates of the actual situation on site are of the essence for emergency services. At present only a small amount of the data necessary for this information needed is being collected. And the data that is collected is not processed into relevant and easily understandable information for the decision makers. This project aims to fill this gap.The objective of the project is to integrate the existing sensor technologies into a decision support system, allowing a wider and more immediate use of sensor data for public interest, particularly in crisis times.A heat-map will be produced based on scenario earthquakes and loss (hazard and risk assessment) estimation tools. After running several scenario quakes, critical points in respect to the expected damages and the distribution of existing sensors will be defined. More sensors in critical locations will also be placed to create a high enough resolution.
