Observational Study of Oral Atogepant to Evaluate Real-World Effectiveness in Adult Participants With Migraine

Remimazolam Versus Midazolam for Sedation During Upper GI Endoscopy: a Randomized Controlled Trial

Improved Prescribing for Older Nursing Home Patients

Additional information on the method: We included 2 nursinghome organizations in september, 2 in october, and 3 in november.

FeAsiBility of a Treatment Free Interval in Newly Diagnosed MM Patients Treated With Daratumumab-lenalidomide-dexamethasone (HOVON174MM)

A Study to Investigate the Effect of Lepodisiran on the Reduction of Major Adverse Cardiovascular Events in Adults With Elevated Lipoprotein(a) - ACCLAIM-Lp(a)

Prevention of Anthracycline-Induced Cardiac Dysfunction With Dexrazoxane in Patients With Diffuse Large-B Cell Lymphoma

HO170 DLBCL-ANTICIPATE: "Prevention of ANThracycline-Induced Cardiac dysfunction by dexrazoxane In PATients with diffusE large B-cell lymphoma" is a national randomized controlled trial that will be conducted across 25 Dutch hospitals. This study will include adult patients with DLBCL in which first-line treatment with 6 cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone) is planned (cumulative doxorubicin dose 300 mg/m2). In this trial, we have chosen to include patients with a normal cardiac function before chemotherapy because cardiac dysfunction is a contra-indication for administration of anthracyclines. A total of 324 DLBCL patients will prior to treatment be randomized in a 1:1 ratio to either (1) intravenous dexrazoxane administration in a 10:1 dexrazoxane:doxorubicin ratio prior to each doxorubicin infusion or (2) no cardioprotective treatment (current standard of care). Due to the low pH of the dexrazoxane solution that would jeopardize the blinding no placebo is used. Cardiac function will be screened with echocardiography prior to the initiation of chemotherapy and followed-up at 4- and 12-months post randomization. The primary end point of the study will be the incidence of AICD, defined as a left ventricular ejection fraction (LVEF) decline of ≥10 percentage points from baseline and below 50% (normal reference value for two-dimensional (2D) echocardiography). The secondary endpoint will be the percentage of patients with complete metabolic remission (CMR) after R-CHOP chemotherapy, to reassure that dexrazoxane does not influence the antineoplastic efficacy of doxorubicin. To declare ANTICIPATE successful, the trial must show both the superiority of addition of dexrazoxane on the primary endpoint and non-inferiority on the secondary endpoint. Deep-phenotyping of patient- and treatment-related factors will be performed to evaluate their prognostic value.

Psychoeducation for Older Adults with Autism

The detection of autism spectrum disorder (ASD) in older adults in Dutch (specialised) mental health care is improving, but underdiagnosis remains. Older adults with ASD experience a low quality of life (QoL) and a high rate of psychopathology across the life span and into old age. Additionally, Dutch and international treatment guidelines advocate psychoeducation (PE) as the first intervention after patients have been diagnosed with ASD. However, as PE for older patients with ASD is hardly available in the Netherlands, access to PE is severely limited for these older adults. Hence, it is important to improve detection and diagnosis of ASD and increase the availability of PE for older adults. The hypotheses of this study are 1) that detection and diagnosis of ASD in older adults will significantly increase following training of professionals and 2) that delivering an adapted and improved PE program for older adults will result in more knowledge and recognition of ASD, a better acceptance of the diagnosis, improved coping with ASD, improved resilience and comorbid general psychological distress, and ultimately in higher quality of life, compared to those patients with ASD that receive no PE. The aim of this study on the one hand is to gain insight into: 1) the effects of providing training and education to mental health care providers in detection and diagnosis of ASD in older adults, with the expectation that this contributes to an increase in the number and proportion of ASD diagnoses in older adults in the Netherlands; 2) the effects of a PE program for older adults with ASD in terms of knowledge and recognition of ASD and traits, a better acceptance of the diagnosis, improved coping with ASD, improved resilience and comorbid general psychological distress - and ultimately higher quality of life; and 3) the experiences of older adults with ASD following the PE program. Study design: The effects of training and education in detection and diagnosis of ASD in older adults, and the effects of the PE program will be evaluated in a Stepped Wedge Trial Design (SWTD), with the intervention sequentially rolled-out in ten (specialised) mental healthcare organisations. Furthermore, a pre-post design will be used to compare the situation before the roll-out period with the situation after the roll-out period in terms of diagnosis and individual outcomes such as knowledge regarding ASD. Qualitative measures will be used to assess the experiences of older adults with ASD who participated in the PE program. Study population: Older adults - aged 60 and over diagnosed with ASD no longer than 12 months before the start of the intervention by a multidisciplinary team according to the Dutch multidisciplinary guidelines, as confirmed by the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders) interview for ASD, or the Netherlands Interview for Diagnosis of ASD in adults (NIDA) as well as a proxy (an individual who provides reports on behalf of, or about, a study participant). The intervention consists of education in detection and diagnosis of ASD in older adults for mental health professionals and of an adapted PE program for older adults with a recent diagnosis of ASD. The PE program consists of seven, two hour group meetings on a weekly basis. Primary study parameter concerns clinical outcomes measuring effects of the psycho-education course in terms of quality of life, acceptance of the diagnosis, knowledge of ASD, recognition of ASD traits, coping with ASD, quantitative autistic traits, resilience, and comorbid psychological distress. Quality of life is assessed by the MHQoL-7 (Mental Health Quality of Life Questionnaire). Acceptance of the diagnosis, knowledge and coping with ASD are assessed with use of the Questionnaire Knowledge, Recognition and Acceptance of Autism Diagnosis (VKHAA). Acceptance of ASD (-diagnosis) is further assessed through the Acceptance Questionnaire (AQ). Autistic traits are assessed through the Social Responsiveness Scale-Adults (SRS-A). Comorbid psychological distress is assessed by the Brief Symptom Inventory (BSI). All these assessments are performed (1) at baseline (following diagnosis and informed consent); (2) before the patient starts with PE (on average three months after baseline; participants in the control group will receive this three months after baseline; (3) after the PE (on average two months after the start of the PE program; participants in the control group will receive this measurement 6 months after baseline); (4) at 9-months follow-up (nine months after second measurement). A proxy, chosen by the study participant, will additionally inform on acceptance, knowledge, recognition, coping and ASD traits through measurements on the VKHAA for informants (VKHAA-N) and SRS-A for informants (SRS-A-N) at two moments that overlap with measurements 2 and 3 of study participants. Secondary study parameters is the number and proportion of ASD diagnoses in the participating centres (collected from the information and registration systems of the mental health care centres) from one year before, during the project, and at one year follow-up. For patients, benefits will be considerable as they will receive a PE program that is recommended by the Dutch multidisciplinary guideline for ASD in adults, and although being the recommended first intervention by treatment guidelines, is not provided to them momentarily. The benefits account for patients who provide informed consent to participate in the research and patients who do not give their consent, since the same treatment will be available for both. The investigators consider the burden of participating in the research, which consists of filling out questionnaires and inviting a proxy of their choice to fill out two of the same questionnaires, to be limited. Firstly, because this will be done in the context of treatment that fits the recommended first intervention by treatment guidelines and thus does not provide an extra mental burden. Moreover, the time needed to fill out these questionnaires is limited: approximately 40 to 60 minutes per measurement point, and there are no indications that risks are involved with regard to the topics of these questionnaires; specifically in a similar study by the study's research group, no adverse events or risks were observed. Additional potential benefits exist in the form of increased detection and diagnosis of ASD in older adults across participating organisations, while the burden of participating in the study hardly exceeds time and effort spent in diagnostic efforts as usual, yet lightens efforts spent on informing patients with an ASD diagnosis as this can be done in a group format rather than on an individual basis. The only extra effort is limited to informing patients about the study with verbal and written information.

Healthcare Utilization in Liver Cirrhosis Patients, a Multicenter Retrospective Cohort Study

A1Check: the External Validation of a Machine Learning Model Predicting Colorectal Anastomotic Leakage

Study procedure The aim of the study is to externally validate a machine learning model predicting colorectal anastomotic leakage. The prediction model that will be externally validated, is developed on a prospective database. This database contained data of 2,483 colorectal cancer patients who underwent a surgical procedure between January 2016 and April 2021 in 14 hospitals, both rural and academic in four different countries (the Netherlands, Italy, Belgium, Australia). Some 189 patients (7.6%) developed colorectal anastomotic leakage. The models predicted risk of colorectal anastomotic leakage intraoperatively, just prior to the construction of the anastomosis, using a total of 31 variables. These variables contain both preoperatively available data and the variables regarding the intraoperative condition of the patient. The models were internally validated using 10-fold cross validation and subsequently tested on 20% of unseen data of the database. The area under the curve - receiver operating characteristics (AUROC) of the best performing machine learning model on the test set was 0.84, with a sensitivity of 0.86, specificity of 0.78, a positive predictive value of 0.24 and a negative predictive value of 0.99. During this prospective simulation study there are no direct benefits or risks for participating patients. This prospective simulation study will be non-interventional, the prediction models do not alter the original daily practice and in this phase, it is not intended to be used as a diagnostic device. Intraoperatively, just prior to the construction of the anastomosis, the prediction model will predict, using patient, tumor, and intraoperatively variables (listed in the Data Dictionary paragraph), the probability of anastomotic leakage. SAS Viya is used for development of the machine learning model. During the prospective simulation study, the scores of these predictions are only available to the principle and research investigators, and thus unknown to the participating hospitals or operating surgeons in order to prevent any influence on current daily practice in this stage of the research. Thirty days postoperatively, data of the patients regarding the occurrence of anastomotic leakage will be collected. AUROC, sensitivity, specificity, and accuracy then will be calculated based on the number of patients assessed as true positive, true negative, false positive or false negative. After a minimum of 100 events and 100 non-events, the external validation is completed and the final AUROC, sensitivity and specificity scores will be presented. Quality assurance plan, data checks, source data verification Data will be handled confidentially and anonymously. Data will be pseudo-anonymized for the principal investigator and the research investigators. Pseudo-anonymized data are entered in a Castor database. A data dictionary is attached to the original dataset with metadata to describe the data. All participating hospitals have a Data Sharing Agreement to safely share data of included patients with the principal investigator and the research investigators. A data management plan will be created according to our institute's polices with the assistance of a data management expert, along with the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines.The characteristics of the collected and generated data is clinical data extracted from the electronic health records. This contains continuous, nominal, and dichotomous variables. Data will not be reused or coupled to existing data. Informed consent of patients is necessary to predict the outcome using the developed model. Privacy policies and laws are applicable to this project. The project will also comply with all data protection principles as is defined in the General Data Protection Regulation. The anonymized dataset can be accessed via a Castor database. Long term data will be saved in the Amsterdam University Medical Center repository with help of the research data management (RDM) department. The data will be saved for five years after the project has ended. Data dictionary The following variables will be collected: i. Patient and tumor characteristics Age; sex; body mass index; American Society of Anesthesiologists (ASA) classification; intoxications (smoking and/or alcohol consumption); medical history of diabetes; steroid use (not nasal); hemoglobin; benign or malignant disease. If there is malignant disease: TNM-stage, tumor distance from anal verge, neoadjuvant treatment. ii. Perioperative characteristics Surgical procedure, surgical approach; conversion; occurrence of intraoperative event (hypoxic events, hypercarbia, bradycardia, hypotension, embolism, reanimation, more extensive resection than planned, serosa lesions, bladder and ureteral injuries, intraoperative bleeding, splenectomy) iii. Characteristics just prior to the creation of the anastomosis Patient temperature; time of antibiotic administration; administration of vasopressors; blood loss; O2 saturation; mean arterial pressure; fluid administration; urine production; presence of fecal contamination; subjective assessment of local perfusion; epidural analgesia; dosing movements; time from incision until the creation of the anastomosis, intention to create stoma. iv. Postoperative characteristics Colorectal anastomotic leakage within 30 days and length of hospital stay. Standard Operating procedures Patients eligible for inclusion are detected in the first multidisciplinary team meeting. If eligible, the surgeon will inform and discuss this study with the patient in the preoperative consultation for surgery. If the patient consents to participation, written informed consent is required. The patient may withdraw this consent at any time. Sample size calculation In the participating hospitals, around 100 to 400 colorectal resections are performed annually, with an approximate incidence of anastomotic leakage of 5 to 15%. Multiple studies demonstrated a minimum of 100 events and 100 nonevents as an appropriate sample size for external validation. With an expected total of 1,200 patients included annually and a leakage percentage around 10%, including 100 events takes approximately one to two years. Handling missing data The machine learning model will make a prediction in patients with more than 80% of the required data available. Missing data are imputed using predictive mean matching with ten iterations. Statistical analysis plan The external validation will be performed on at least 100 events (anastomotic leakage) and 100 non-events (no anastomotic leakage). The machine learning model with the best predictive performance in terms of AUROC will be used as the implementation model. Colorectal anastomotic leakage rate will be compared in a multivariate logistic regression model. All analyses will be carried out under the supervision of a clinical epidemiologist.

Nasal Bridle Versus Nasal Patch for Fixation of Nasoenteral Feeding Tubes