Background: Multimodal prehabilitation programs are effective at reducing complications after colorectal surgery in patients with a high risk of postoperative complications due to low aerobic capacity and/or malnutrition. However, high implementation fidelity is needed to achieve these effects in real-life practice. This study aimed to investigate the implementation fidelity of an evidence-based prehabilitation program in the real-life context of a Dutch regional hospital.Methods: In this observational cohort study with multiple case analyses, all patients who underwent colorectal surgery from January 2023 to June 2023 were enrolled. Patients meeting the criteria for low aerobic capacity or malnutrition were advised to participate in a prehabilitation program. According to recent scientific insights and the local care context, this program consisted of four exercise modalities and three nutrition modalities. Implementation fidelity was investigated by evaluating: (1) coverage (participation rate), (2) duration (number of days between the start of prehabilitation and surgery), (3) content (delivery of prescribed intervention modalities), and (4) frequency (attendance of sessions and compliance with prescribed parameters). An aggregated percentage of content and frequency was calculated to determine overall adherence.Results: Fifty-eight patients intended to follow the prehabilitation care pathway, of which 41 performed a preoperative risk assessment (coverage 80%). Ten patients (24%) were identified as high-risk and participated in the prehabilitation program (duration of 33-84 days). Adherence was high (84-100%) in five and moderate (72-73%) in two patients. Adherence was remarkably low (25%, 53%, 54%) in three patients who struggled to execute the prehabilitation program due to multiple physical and cognitive impairments.Conclusion: Implementation fidelity of an evidence-based multimodal prehabilitation program for high-risk patients preparing for colorectal surgery in real-life practice was moderate because adherence was high for most patients, but low for some patients. Patients with low adherence had multiple impairments, with consequences for their preparation for surgery. For healthcare professionals, it is recommended to pay attention to high-risk patients with multiple impairments and further personalize the prehabilitation program. More knowledge about identifying and treating high-risk patients is needed to provide evidence-based recommendations and to obtain higher effectiveness.
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In this PhD thesis, we aimed to improve understanding of the study progression and success of autistic students in higher education by comparing them to students with other disabilities and students without disabilities. We studied their background and enrollment characteristics, whether barriers in progression existed, how and when possible barriers manifested themselves in their student journey, and how institutions should address these issues. We found autistic students to be different from their peers but not worse as expected based on existing findings. We expect we counterbalanced differences because we studied a large data set spanning seven cohorts and performed propensity score weighting. Most characteristics of autistic students at enrollment were similar to those of other students, but they were older and more often male. They more often followed an irregular path to higher education than students without disabilities. They expected to study full time and spend no time on extracurricular activities or paid work. They expected to need more support and were at a higher risk of comorbidity than students with other disabilities. We found no difficulties with participation in preparatory activities. Over the first bachelor year, the grade point averages (GPAs) of autistic students were most similar to the GPAs of students without disabilities. Credit accumulation was generally similar except for one of seven periods, and dropout rates revealed no differences. The number of failed examinations and no-shows among autistic students was higher at the end of the first semester. Regarding progression and degree completion, we showed that most outcomes (GPAs, dropout rates, resits, credits, and degree completion) were similar in all three groups. Autistic students had more no-shows in the second year than their peers, which affected degree completion after three years. Our analysis of student success prediction clarified what factors predicted their success or lack thereof for each year in their bachelor program. For first-year success, study choice issues were the most important predictors (parallel programs and application timing). Issues with participation in pre-education (absence of grades in pre-educational records) and delays at the beginning of autistic students’ studies (reflected in age) were the most influential predictors of second-year success and delays in the second and final year of their bachelor program. Additionally, academic performance (average grades) was the strongest predictor of degree completion within three years. Our research contributes to increasing equality of opportunities and the development of support in higher education in three ways. First, it provides insights into the extent to which higher education serves the equality of autistic students. Second, it clarifies which differences higher education must accommodate to support the success of autistic students during their student journey. Finally, we used the insights into autistic students’ success to develop a stepped, personalized approach to support their diverse needs and talents, which can be applied using existing offerings.
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Abstract from article: The Dutch healthcare system has changed towards a system of regulated competition to contain costs and to improve efficiency and quality of care. This paper provides: (1) a brief as-is overview of the changes for primary care, based on explorative literature reviews; (2) provides noteworthy remarks as for the way primary and secondary healthcare is organised; (3) an example of an E-health portal illustrating implemented processes within the Dutch context and (4) a proposed research agenda on various e-health topics. Noteworthy remarks are: (1) government, insurer, healthcare provider and patient are main actors within the Dutch healthcare system; (2) general practitioners (GP’s) are gatekeepers to secondary and other care providers; (3) the illustrated portal with a patient oriented design, provides access to applications implemented at care providers resulting in increased electronic availability and increased patient satisfaction; (4) a variety of fragmented information systems at health care providers exists, which leaves room for standardisation and increased efficiency. We end with suggestions for future research.
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).
Organ-on-a-chip technology holds great promise to revolutionize pharmaceutical drug discovery and development which nowadays is a tremendously expensive and inefficient process. It will enable faster, cheaper, physiologically relevant, and more reliable (standardized) assays for biomedical science and drug testing. In particular, it is anticipated that organ-on-a-chip technology can substantially replace animal drug testing with using the by far better models of true human cells. Despite this great potential and progress in the field, the technology still lacks standardized protocols and robust chip devices, which are absolutely needed for this technology to bring the abovementioned potential to fruition. Of particular interest is heart-on-a-chip for drug and cardiotoxicity screening. There is presently no preclinical test system predicting the most important features of cardiac safety accurately and cost-effectively. The main goal of this project is to fabricate standardized, robust generic heart-on-a-chip demonstrator devices that will be validated and further optimized to generate new physiologically relevant models to study cardiotoxicity in vitro. To achieve this goal various aspects will be considered, including (i) the search for alternative chip materials to replace PDMS, (ii) inner chip surface modification and treatment (chemistry and topology), (iii) achieving 2D/3D cardiomyocyte (long term) cell culture and cellular alignment within the chip device, (iv) the possibility of integrating in-line sensors in the devices and, finally, (v) the overall chip design. The achieved standardized heart-on-a-chip technology will be adopted by pharmaceutical industry. This proposed project offers a unique opportunity for the Netherlands, and Twente in particular, which has relevant expertise, potential, and future perspective in this field as it hosts world-leading companies pioneering various core aspects of the technology that are relevant for organs-on-chips, combined with two world-leading research institutes within the University of Twente.
communicative participation, language disordersOBJECTIVE(S)/RESEARCH QUESTION(S) Speech and language therapists (SLTs) are the primary care professionals to treat language and communication disorders. Their treatment is informed by a variety of outcome measures. At present, diagnosis, monitoring of progress and evaluation are often based on performance-based and clinician-reported outcomes such as results of standardized speech, language, voice, or communication tests. These tests typically aim to capture how well the person can produce or understand language in a controlled situation, and therefore only provide limited insight in the person’s challenges in life. Performance measures do not incorporate the unobservable feelings such as a patient's effort, social embarrassment, difficulty, or confidence in communication. Nor do they address language and communication difficulties experienced by the person themselves, the impact on daily life or allow patients to set goals related to their own needs and wishes. The aim of our study is give our patients a voice and empower SLTs to incorporate their patient's perspective in planning therapy. We will Aangemaakt door ProjectNet / Generated by ProjectNet: 08-12-2020 12:072Subsidieaanvraag_digitaal / Grant Application_digitaalDossier nummer / Dossier number: 80-86900-98-041DEFINITIEFdevelop a valid and reliable patient-reported outcome measure that provides information on communicative participation of people with communication disorders and integrate this item bank in patient specific goal setting in speech and language therapy. Both the item bank and the goal setting method will be adapted in cocreation with patients to enable access for people with communication difficulties.STUDY DESIGN Mixed methods research design following the MRC guidance for process evaluation of complex interventions, using PROMIS methodology including psychometric evaluation and an iterative user-centered design with qualitative co-creation methods to develop accessible items and the goal setting method.RESEARCH POPULATION Children, adolescents and adults with speech, language, hearing, and voice disorders.OUTCOME MEASURES An online patient-reported outcome measure on communicative participation, the Communicative Participation Item Bank (CPIB), CPIB items that are accessible for people with language understanding difficulties, a communicative-participation person-specific goal setting method developed with speech and language therapists and patients and tested on usability and feasibility in clinical practice, and a course for SLTs explaining the use of the goal-setting method in their clinical reasoning process.RELEVANCE This study answers one of the prioritized questions in the call for SLTs to systematically and reliably incorporate the clients’ perspective in their daily practice to improve the quality of SLT services. At present patient reported outcomes play only a small role in speech and language therapy because 1) measures (PROMS) are often invalid, not implemented and unsuitable for clinical practice and 2) there is a knowledge gap in how to capture and interpret outcomes from persons with language disorders.
