PURPOSE: The Nasality Severity Index 2.0 (NSI 2.0) forms a new, multiparametric approach in the assessment of hypernasality. To enable clinical implementation of this index, the short- and long-term test-retest reliability of this index was explored. METHODS: In 40 normal-speaking adults (mean age 32y, SD 11, 18-56y) and 29 normal-speaking children (mean age 8y, SD 2, 4-12y), the acoustic parameters included in the NSI 2.0 (i.e. nasalance of the vowel /u/ and an oral text, and the voice low tone to high tone ratio (VLHR) of the vowel /i/) were obtained twice at the same test moment and during a second assessment two weeks later. After determination of the NSI 2.0, a comprehensive set of statistical measures was applied to determine its reliability. RESULTS: Long-term variability of the NSI 2.0 and its parameters was slightly higher compared to the short-term variability, both in adults and in children. Overall, a difference of 2.82 for adults and 2.68 for children between the results of two consecutive measurements can be interpreted as a genuine change. With an ICC of 0.84 in adults and 0.77 in children, the NSI 2.0 additionally shows an excellent relative consistency. No statistically significant difference was withheld in the reliability of test-retest measurements between adults and children. CONCLUSION: Reliable test-retest measurements of the NSI 2.0 can be performed. Consequently, the NSI 2.0 can be applied in clinical practice, in which successive NSI 2.0 scores can be reliably compared and interpreted. LEARNING OUTCOMES: The reader will be able to describe and discuss both the short-term and long-term test-retest reliability of the Nasality Severity Index 2.0, a new multiparametric approach to hypernasality, and its parameters. Based on this information, the NSI 2.0 can be applied in clinical practice, in which successive NSI 2.0 scores, e.g. before and after surgery or speech therapy, can be compared and interpreted.
PURPOSE: The Nasality Severity Index 2.0 (NSI 2.0) forms a new, multiparametric approach in the assessment of hypernasality. To enable clinical implementation of this index, the short- and long-term test-retest reliability of this index was explored. METHODS: In 40 normal-speaking adults (mean age 32y, SD 11, 18-56y) and 29 normal-speaking children (mean age 8y, SD 2, 4-12y), the acoustic parameters included in the NSI 2.0 (i.e. nasalance of the vowel /u/ and an oral text, and the voice low tone to high tone ratio (VLHR) of the vowel /i/) were obtained twice at the same test moment and during a second assessment two weeks later. After determination of the NSI 2.0, a comprehensive set of statistical measures was applied to determine its reliability. RESULTS: Long-term variability of the NSI 2.0 and its parameters was slightly higher compared to the short-term variability, both in adults and in children. Overall, a difference of 2.82 for adults and 2.68 for children between the results of two consecutive measurements can be interpreted as a genuine change. With an ICC of 0.84 in adults and 0.77 in children, the NSI 2.0 additionally shows an excellent relative consistency. No statistically significant difference was withheld in the reliability of test-retest measurements between adults and children. CONCLUSION: Reliable test-retest measurements of the NSI 2.0 can be performed. Consequently, the NSI 2.0 can be applied in clinical practice, in which successive NSI 2.0 scores can be reliably compared and interpreted. LEARNING OUTCOMES: The reader will be able to describe and discuss both the short-term and long-term test-retest reliability of the Nasality Severity Index 2.0, a new multiparametric approach to hypernasality, and its parameters. Based on this information, the NSI 2.0 can be applied in clinical practice, in which successive NSI 2.0 scores, e.g. before and after surgery or speech therapy, can be compared and interpreted.
Scar contractures are a common complication after burn injuries. These contractures are characterized by impairment of joint mobility, leading to a risk for limitations during daily activities, and restrictions in participation in society. Qualifying its severity is not well established in burn care. This study, therefore, examined different approaches to determine the severity of limited mobility in the knee joint due to scar contracture.To determine the severity of burn scar contractures development of the knee over time, the following approaches were analyzed: prevalence, the degree of limitation, the ability to perform basic daily activities, and the need for reconstructive surgery. Range of motion data of the knee joint was extracted from a 12-month prospective multicenter cohort study in the Netherlands.Based on prevalence, mean degree of limitation, and the classification based on mathematical division, limitations in knee flexion would be seen as giving the most problems. On the other hand, when classified in terms of impact on function, limitations in extension were found to be giving most problems, although flexion limitations interfered slightly longer with the basic activities of standing, walking, and climbing stairs.Depending on the chosen approach, the severity of burn scar contractures is projected differently. Interpreting the severity of a burn scar contracture of the knee, preferably should be based on a function-based classification system of the degree of range of motion impairment, activity limitations and participation restrictions in society. Because that does justice to the real impact of burn scar contracture on the individual burn survivor.
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.
