How to inform at-risk relatives?:Attitudes of 1379 Dutch patients, relatives, and members of the general population

The uptake of predictive DNA testing in families with a hereditary disease is <50%. Current practice often relies on the proband to inform relatives about the possibility of predictive DNA testing, but not all relatives are informed adequately. To enable informed decision-making concerning predictive DNA testing, the approach used to inform at-risk relatives needs to be optimized. This study investigated the preferences of patients, relatives, and the general population from the Netherlands on how to inform relatives at risk of autosomal dominant diseases. Online surveys were sent to people with autosomal dominant neuro-, onco-, or cardiogenetic diseases and their relatives via patient organizations (n = 379), and to members of the general population via a commercial panel (n = 1,000). Attitudes of the patient and population samples generally corresponded. A majority believed that initially only first-degree relatives should be informed, following the principles of a cascade screening approach. Most participants also thought that probands and healthcare professionals (HCPs) should be involved in informing relatives, and a large proportion believed that HCPs should contact relatives directly in cases where patients are unwilling to inform, both for untreatable and treatable conditions. Participants from the patient sample were of the opinion that HCPs should actively offer support. Our findings show that both patients and HCPs should be involved in informing at-risk relatives of autosomal dominant diseases and suggest that relatives' 'right to know' was considered a dominant issue by the majority of participants. Further research is needed on how to increase proactive support in informing of at-risk relatives

Event Log Sampling for Predictive Monitoring

Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant interest to the process stakeholders. However, state-of-the-art methods for predictive monitoring require the training of complex machine learning models, which is often inefficient. This paper proposes an instance selection procedure that allows sampling training process instances for prediction models. We show that our sampling method allows for a significant increase of training speed for next activity prediction methods while maintaining reliable levels of prediction accuracy.Comment: 7 pages, 1 figure, 4 tables, 34 reference

Know What You Stream: Generating Event Streams from CPN Models in ProM 6

Abstract. The field of process mining is concerned with supporting the analysis, improvement and understanding of business processes. A range of promising techniques have been proposed for process mining tasks such as process discovery and conformance checking. However there are challenges, originally stemming from the area of data mining, that have not been investigated extensively in context of process mining. In particular the incorporation of data stream mining techniques w.r.t. process mining has received little attention. In this paper, we present new developments that build on top of previous work related to the integration of data streams within the process mining framework ProM. We have developed means to use Coloured Petri Net (CPN) models as a basis for eventstream generation. The newly introduced functionality greatly enhances the use of event-streams in context of process mining as it allows us to be actively aware of the originating model of the event-stream under analysis

Тактика лечения эректильной дисфункции у мужчин без партнерши

Обосновывается актуальность проблемы оказания помощи мужчинам с эректильной дисфункцией, не имеющим сексуальной партнерши. Описаны предложенные автором подходы к коррекции нарушения сексуального здоровья мужчин и лечебные тактики.The importance of the issue of rendering the aid to the men with erectile dysfunction who do not have a female partner is substantiated. The author describes the original approaches to correction of the sexual health in the men and therapeutic tactics

Stratification of COPD patients towards personalized medicine:reproduction and formation of clusters

BACKGROUND: The global initiative for chronic obstructive lung disease (GOLD) 2020 emphasizes that there is only a weak correlation between FEV(1), symptoms and impairment of the health status of patients with chronic obstructive pulmonary disease (COPD). Various studies aimed to identify COPD phenotypes by cluster analyses, but behavioral aspects besides smoking were rarely included. METHODS: The aims of the study were to investigate whether (i) clustering analyses are in line with the classification into GOLD ABCD groups; (ii) clustering according to Burgel et al. (Eur Respir J. 36(3):531–9, 2010) can be reproduced in a real-world COPD cohort; and (iii) addition of new behavioral variables alters the clustering outcome. Principal component and hierarchical cluster analyses were applied to real-world clinical data of COPD patients newly referred to secondary care (n = 155). We investigated if the obtained clusters paralleled GOLD ABCD subgroups and determined the impact of adding several variables, including quality of life (QOL), fatigue, satisfaction relationship, air trapping, steps per day and activities of daily living, on clustering. RESULTS: Using the appropriate corresponding variables, we identified clusters that largely reflected the GOLD ABCD groups, but we could not reproduce Burgel’s clinical phenotypes. Adding six new variables resulted in the formation of four new clusters that mainly differed from each other in the following parameters: number of steps per day, activities of daily living and QOL. CONCLUSIONS: We could not reproduce previously identified clinical COPD phenotypes in an independent population of COPD patients. Our findings therefore indicate that COPD phenotypes based on cluster analysis may not be a suitable basis for treatment strategies for individual patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-022-02256-7

Understanding the diagnostic delay in rare diseases

According to the European definition, rare diseases are life-threatening or chronically debilitating conditions that affect only 5 out of 10,000 people in the European Union. It is estimated that there are around 6000-8000 different rare diseases, affecting 6-8% of the population in the course of their lives. For the Netherlands, this means that about 1 million people are affected by a rare disease, or one in 17 people. Patients with rare diseases indicate that they often have a long and uncertain diagnostic journey behind them, while the first symptoms present in childhood in 75% of the rare diseases. In this perspective, we discuss some of the results from the research report 'Scherperzicht op diagnostischevertragingbijzeldzameaandoeningen' in which the diagnostic journey for patients with rare diseases is mapped out with figures. We also make recommendations to speed up the diagnostic process for patients with rare diseases.</p