There are about 13332 clinical studies being (or have been) conducted in Netherlands. The country of the clinical trial is determined by the location of where the clinical research is being studied. Most studies are often held in multiple locations & countries.
The purpose of this trial is to investigate if tralokinumab changes the metabolism of selected CYP substrates in adults with moderate-to-severe AD after: - 14 weeks of treatment with tralokinumab - a single dose of tralokinumab
The study is designed to explore the safety and tolerability as well as diagnostic 89Zr-girentuximab for imaging CCRC by PET/CT. This study does not offer any treatment for patients with CCRC; therefore, patients will be offered state of the art therapeutic options after imaging with the study drug 89Zr-girentuximab. Cancer treatment will not be delayed by study participation.
Approximately 25% of patients with type 1 diabetes have lost the capacity to timely detect hypoglycaemia, a condition referred to as impaired awareness of hypoglycaemia (IAH) that causes a six-fold higher risk of severe, potentially hazardous, hypoglycaemia. IAH is usually the end-result of a process of habituation to recurrent hypoglycaemia that is potentially reversible. Treatment with sodium glucose cotransporter (SGLT)-2 inhibitors (SGLT-2i) in addition to insulin therapy may decrease the incidence of hypoglycaemia in patients with type 1 diabetes. This study will test the hypothesis that treatment with the SGLT-2 inhibitor, dapagliflozin, added to basal-bolus insulin therapy will improve awareness of hypoglycaemia in patients with type 1 diabetes and IAH. In a randomized doubleblind placebo-controlled cross-over trial, patients will be treated for 8 weeks with dapagliflozin (or placebo), after which hypoglycemic symptoms and counterregulatory hormone responses will be examined during a hyperinsulinemic hypoglycemic glucose clamp study.
A phase 2 study in two parts (A & B) designed to evaluate the effect of MEDI0382 on Hepatic Glycogen Metabolism in subjects with Type 2 Diabetes Mellitus (T2DM). Approximately 20 subjects will be enrolled in Part A and approximately 30 subjects in Part B.
Grip&Health: randomised trial which will examine the effect of theory-based multicomponent behavioural intervention for reducing stress, smoking and improving financial health and perceived health of low-SES residents in Rotterdam. Between January 2018 and July 2018, a total of 300 participants will be recruited and randomised either to a stress management program (SM), stress management with a buddy program (SM-B) or a control condition. The investigators hypothesise that compared to participants in the control condition, participants in the intervention arms will demonstrate reduced stress, reduced smoking and improved financial health and perceived health.
Endometrial cancer (EC) is the most frequent gynecological malignancy but there is currently lack of both non-invasive diagnostic tools and novel markers to stratify patients based on their risk of future recurrence. Patient care could be improved by advances in these two aspects. In the present study, the investigators aim to identify diagnostic serum metabolite and protein biomarker signatures for early detection of cancer in asymptomatic high-risk population and prognostic biomarkers for selection of patients with poor prognosis.
Given the lack of knowledge on lipodystrophies, the medical and social responsibility for the persons affected by it calls for the monitoring of the progression over long periods of time. Sensible clinical and basic research into rare diseases such as lipodystrophy is only possible in multi-location networks with sufficient case numbers. Also, reliable information on the incidence of certain manifestation patterns, health status, etc. is of utmost importance for health care and health policy in this rare disease. Therefore, the European Consortium of Lipodystrophies (ECLip), an association of European experts on lipodystrophy, has launched a registry (OSSE) for lipodystrophies which is committed to help to improve the research conditions by consolidating this kind of information in a registry.
Each year approximately 3000 patients are admitted to the intensive care unit (ICU) in the University Medical Center Groningen (UMCG). In-hospital mortality of patients with emergency admission approaches 25%. Predicting outcome in the first hours after ICU admission, however, remains a challenge. An vast amount of scoring systems has been developed for mortality prediction. Well known models, such as the LODS, MODS, CCI, SOFA, ODIN and the different generations of the APACHE, MPM and SAPS, are increasingly compared with new models, such as the SICULA, ICNARC, ANZROD and SMS-ICU. The predictive value of scoring systems deteriorates over time due to changes in patient characteristics and treatment, making it crucial to update existing models or develop new models. Other reasons given for the need of models are the complexity and lack of availability of variables in some of the existing scoring systems, the better discriminating value while using simple, standardly measured variables, and the limited generalizability of some scoring systems in different patient populations. Not only are simple systems (such as the CIS and SMS-ICU) found to be at least as predictive for mortality as complex models such as the APACHE IV, but, while using simplified systems, mortality can also be reasonably predicted within only a few hours after admission. Both simplicity and the potential to predict mortality shortly after admission increase the usability, and consequently the reliability, of those prediction models. This increases the potential of those models to be used in practice. Most studies however compare only two to four models in their patient population and lack in their description of the performance of the different models. Parameters necessary to compare the performance of models are at least calibration, discrimination, negative predicting value, positive predicting value, sensitivity and specificity. Lacking an adequate description of the performance of the model limits to what extent the study can be used to compare models in different populations. Thus, all usable models should be compared with newly build models, and the performance of the different models should be extensively described to allow comparison of the models. Not only models based on simple, readily available variables available within hours after admission are promising, but also the concept of combining measurements straight after ICU admission with information on the course of illness. It is likely that the course of a variable over time is more indicative than a static measurement. This study will provide a structure in which every patient admitted to the ICU will be investigated and included within 3 hours and after 12 hours after admission, making longitudinal measurements and various add-on studies possible. Longitudinal measurements are the first example of an add-on study; another example is the capability of nurses and physicians to predict outcome. Current evidence suggests that physicians might predict mortality more accurately than scorings systems. This finding may, however, be highly biased, since at least physicians play a major role in end-of-life decision making. More recent studies also focus on the accuracy of nurses in predicting mortality, with diverse outcomes. The role of other health care professionals, like residents and students, remain to be studied. Implementing a systematic data collection process is the first step towards making data-driven research possible, a growing need in medical disciplines such as critical care, which requires increasingly more accurate prognostic models. Therefore, the aim of this study is to systematically collect data of all selected variables, thus minimizing incompleteness, and allowing for the calculation of mortality prediction scores according to currently available mortality or severity of disease prediction models. Moreover, during investigation reliability of measurements could be checked for validity. This creates the possibility to compare the performance of all models in one population and identify models which are useful to predict severity of disease. A registry will be created with this primary objective which also provides the opportunity to start multiple ''add-on'' studies for specific research questions. Examples of add-on studies are 1) the association between time-dependent variables which are longitudinally measured, and mortality/acute and chronic co-morbidity, 2) the association between fluid status and acute kidney injury, and 3) not only the capability of the treating physician to predict mortality, but also the capability of the nurses, residents and students to do so. Purpose: The purpose of this study is to expand the infrastructure for a registry with longitudinal and repeated measurements, shortly after admittance, which is flexible to incorporate temporarily added specific research questions on the outcome of critically ill patients.
The primary purpose of this study is to investigate the evolution of Right Ventricular (RV) function before and after left ventricular assist device (LVAD) implantation, using novel echocardiographic quantification of RV size and function in combination with comprehensive hemodynamic, laboratory and clinical parameters. The findings of the study will enhance prediction of early and late development of postoperative right-sided heart failure (RHF) and subsequent mortality and morbidity. The secondary purpose of the study is to combine echocardiographic, hemodynamic, laboratory, and clinical data to define optimal management strategies of RHF after LVAD implantation.
More than 200,000 new cases of renal cancer are diagnosed in the world each year, with more than 63,000 new cases in Europe alone. Of those, renal cell carcinoma (RCC) is the most common type in adults, making up more than 90% of the cases. Deciding on the benign or malignant nature of some RCC on the basis of medical images (CT, MRI, US) is an issue, which often leads to unnecessary surgery, morbidity and costs. A categorization for renal cysts was introduced in the late 1980s known as the Bosniak classification. The Bosniak classification system classifies them into groups that are benign (I and II) and those that need surgical resection (III and IV), based on specific imaging features. However, defining the malignancy of category III lesions still remains a challenge. Though Bosniak classification for renal cysts is used worldwide and underwent a number of modifications, Bosniak III cysts still have almost a 1:1 chance of being malignant. So the problem is that approximately half of the Bosniak category III cystic lesions prove to be benign after surgery. The proposed project aims to develop a quantitative image analysis (QIA) based multifactorial decision support system (mDSS) capable of classifying renal cysts with high accuracy into benign or malignant status, thus reducing the amount of unnecessary surgeries performed. Using standard-of-care CT images and clinical parameters, the customized DSS will then guide experts in planning a safe and effective diagnostic and treatment strategy for all RCC patients.