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Despite significant efforts, the COVID-19 pandemic has put enormous pressure on health care systems around the world, threatening the quality of patient care. Telemonitoring offers the opportunity to carefully monitor patients with a confirmed or suspected case of COVID-19 from home and allows for the timely identification of worsening symptoms. Additionally, it may decrease the number of hospital visits and admissions, thereby reducing the use of scarce resources, optimizing health care capacity, and minimizing the risk of viral transmission. In this paper, we present a COVID-19 telemonitoring care pathway developed at a tertiary care hospital in the Netherlands, which combined the monitoring of vital parameters with video consultations for adequate clinical assessment. Additionally, we report a series of medical, scientific, organizational, and ethical recommendations that may be used as a guide for the design and implementation of telemonitoring pathways for COVID-19 and other diseases worldwide.

BackgroundDespite the increase in use and high expectations of digital health solutions, scientific evidence about the effectiveness of electronic health (eHealth) and other aspects such as usability and accuracy is lagging behind. eHealth solutions are complex interventions, which require a wide array of evaluation approaches that are capable of answering the many different questions that arise during the consecutive study phases of eHealth development and implementation. However, evaluators seem to struggle in choosing suitable evaluation approaches in relation to a specific study phase. ObjectiveThe objective of this project was to provide a structured overview of the existing eHealth evaluation approaches, with the aim of assisting eHealth evaluators in selecting a suitable approach for evaluating their eHealth solution at a specific evaluation study phase. MethodsThree consecutive steps were followed. Step 1 was a systematic scoping review, summarizing existing eHealth evaluation approaches. Step 2 was a concept mapping study asking eHealth researchers about approaches for evaluating eHealth. In step 3, the results of step 1 and 2 were used to develop an “eHealth evaluation cycle” and subsequently compose the online “eHealth methodology guide.” ResultsThe scoping review yielded 57 articles describing 50 unique evaluation approaches. The concept mapping study questioned 43 eHealth researchers, resulting in 48 unique approaches. After removing duplicates, 75 unique evaluation approaches remained. Thereafter, an “eHealth evaluation cycle” was developed, consisting of six evaluation study phases: conceptual and planning, design, development and usability, pilot (feasibility), effectiveness (impact), uptake (implementation), and all phases. Finally, the “eHealth methodology guide” was composed by assigning the 75 evaluation approaches to the specific study phases of the “eHealth evaluation cycle.” ConclusionsSeventy-five unique evaluation approaches were found in the literature and suggested by eHealth researchers, which served as content for the online “eHealth methodology guide.” By assisting evaluators in selecting a suitable evaluation approach in relation to a specific study phase of the “eHealth evaluation cycle,” the guide aims to enhance the quality, safety, and successful long-term implementation of novel eHealth solutions.

PURPOSE Chest pain frequently poses a diagnostic challenge for general practitioners (GPs). Utilizing risk stratification tools might help GPs to rule out acute coronary syndrome (ACS) and make appropriate referral decisions. We conducted a systematic review of studies evaluating risk stratification tools for chest pain in primary care settings, both with and without troponin assays. Our aims were to assess the performance of tools for ruling out ACS and to provide a comprehensive review of the current evidence. METHODS We searched PubMed and Embase for articles up to October 9, 2023 concerning adult patients with acute chest pain in primary care settings, for whom risk stratification tools (clinical decision rules [CDRs] and/or single biomarker tests) were used. To identify eligible studies, a combination of active learning and backward snowballing was applied. Screening, data extraction, and quality assessment (following the Quality Assessment of Diagnostic Accuracy Studies-2 tool) were performed independently by 2 researchers. RESULTS Of the 1,204 studies screened, 14 were included in the final review. Nine studies validated 7 different CDRs without troponin. Sensitivities ranged from 75.0% to 97.0%, and negative predictive values (NPV) ranged from 82.4% to 99.7%. None of the CDRs outperformed the unaided judgment of GP's. Five studies reported on strategies using troponin measurements. Studies using high-sensitivity troponin showed highest diagnostic accuracy with sensitivity 83.3% to 100% and NPV 98.8% to 100%. CONCLUSION Clinical decision rules without troponin and the use of conventional troponin showed insufficient sensitivity to rule out ACS in primary care and are not recommended as standalone tools. High-sensitivity troponin strategies are promising, but studies are limited. Further prospective validation in primary care is needed before implementation. Key words: acute coronary syndrome; chest pain; clinical decision rules; primary health care; troponin, https://doi.org/10.1370/afm.3141 INTRODUCTION Chest pain often poses a diagnostic challenge for general practitioners (GPs). While chest pain is the hallmark symptom of acute coronary syndrome (ACS), it is often caused by [...]

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci.

Background: Lifestyle intervention programmes target behavioural risk factors that contribute to cardiovascular diseases (CVDs). Unfortunately, sustainable implementation of these programmes can be challenging. Gaining insights into the barriers and facilitators for successful implementation is important for maximising public health impact of these interventions. The Healthy Heart (HH) programme is an example of a combined lifestyle intervention programme. Aim: To analyse the reach, adoption, and implementation of the HH programme. Design & setting: A mixed-methods study conducted in a general practice setting in The Netherlands. Method: Quantitative data were collected from the Healthy Heart study (HH study), a non-randomised cluster stepped-wedge trial to assess the effect of the HH programme on patients at high risk of developing CVDs at practice level. Qualitative data were obtained through focus groups. Results: Out of 73 approached general practices, 55 implemented the HH programme. A total of 1082 patients agreed to participate in the HH study, of whom 64 patients were referred to the HH programme and 41 patients participated. Several barriers for participation were identified such as time investment, lack of risk perception, and being confident in changing lifestyle on their own. Important barriers for healthcare providers (HCPs) to refer a patient were time investment, lack of information to sufficiently inform patients, and preconceived notions regarding which patients the programme was suitable for. Conclusion: This study has offered insights from a patient and HCP perspective regarding barriers and facilitators for implementation of the group-based lifestyle intervention programme. The identified barriers and facilitators, and the suggested improvements, can be used by others who wish to implement a similar programme. [ABSTRACT FROM AUTHOR]

Physical inactivity is already present among patients with chronic obstructive pulmonary disease (COPD) of mild or moderate airflow obstruction. Most previous studies that reported on determinants of physical activity in COPD included patients with severe COPD. Therefore, this study aimed to explore which patient characteristics were related to physical activity in COPD patients with mild or moderate airflow obstruction. Cross-sectional analyses were performed on patients selected from the population-based Netherlands Epidemiology of Obesity study. Patients were included if they had a physician-diagnosed COPD GOLD 0-2 or had newly diagnosed COPD GOLD 1-2. Physical activity was evaluated using the Short Questionnaire to Assess Health-Enhancing Physical Activity (SQUASH) questionnaire and reported in hours per week of metabolic equivalents (MET-h/week). Associations between sociodemographic, lifestyle, clinical and functional characteristics were examined using regression analysis. 323 patients were included in research (77 with physiciandiagnosed and 246 with newly diagnosed COPD). We found that physical activity was positively associated with pulmonary function: FEV1 (regression coefficient 0.40 (95% CI 0.09,0.71)) and FVC (regression coefficient 0.34 (95% CI 0.06,0.61)). Physical activity was associated with anxiety (regression coefficient =0.9 (95% CI 0.3,1.6)) only for physician-diagnosed patients. Lung function and anxiety level determine the level of physical activity among COPD patients with mild or moderate airflow obstruction. Thus, adjusting physical activity plans accordingly could help to increase physical activity level of the patients. [ABSTRACT FROM AUTHOR]