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- Comprehensive Cancer Center Mainfranken, University Hospital Würzburg, Würzburg, Germany (1)
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The aim of this study was to investigate the prognostic value of 18F-fluoro-deoxyglucose positron emission tomography–computed tomography (18F-FDG-PET/CT) in 37 patients with a history of multiple myeloma (MM) and suspected or confirmed recurrence after stem cell transplantation (SCT). All patients had been heavily pre-treated. Time to progression (TTP) and overall survival (OS) were correlated to a number of different PET-derived as well as clinical parameters. Impact on patient management was assessed.
Absence of FDG-avid MM foci was a positive prognostic factor for both TTP and OS (p<0.01). Presence of >10 focal lesions correlated with both TTP (p<0.01) and OS (p<0.05). Interestingly, presence of >10 lesions in the appendicular skeleton proved to have the strongest association with disease progression. Intensity of glucose uptake and presence of extramedullary disease were associated with shorter TTP (p=0.037 and p=0.049, respectively). Manifestations in soft tissue structures turned out to be a strong negative predictor for both, TTP and OS (p<0.01, respectively). PET resulted in a change of management in 30% of patients.
Our data underline the prognostic value of 18F-FDG-PET/CT in MM patients also in the setting of post-SCT relapse. PET/CT has a significant impact on patient management.
Background: Over the recent years, technological advances of wrist-worn fitness trackers heralded a new era in the continuous monitoring of vital signs. So far, these devices have primarily been used for sports.
Objective: However, for using these technologies in health care, further validations of the measurement accuracy in hospitalized patients are essential but lacking to date.
Methods: We conducted a prospective validation study with 201 patients after moderate to major surgery in a controlled setting to benchmark the accuracy of heart rate measurements in 4 consumer-grade fitness trackers (Apple Watch 7, Garmin Fenix 6 Pro, Withings ScanWatch, and Fitbit Sense) against the clinical gold standard (electrocardiography).
Results: All devices exhibited high correlation (r≥0.95; P<.001) and concordance (rc≥0.94) coefficients, with a relative error as low as mean absolute percentage error <5% based on 1630 valid measurements. We identified confounders significantly biasing the measurement accuracy, although not at clinically relevant levels (mean absolute error<5 beats per minute).
Conclusions: Consumer-grade fitness trackers appear promising in hospitalized patients for monitoring heart rate.
Background
International research for acute myocardial infarction lacks comparisons of whole health systems. We assessed time trends for care and outcomes in Sweden and the UK.
Methods
We used data from national registries on consecutive patients registered between 2004 and 2010 in all hospitals providing care for acute coronary syndrome in Sweden and the UK. The primary outcome was all-cause mortality 30 days after admission. We compared effectiveness of treatment by indirect casemix standardisation. This study is registered with ClinicalTrials.gov, number NCT01359033.
Findings
We assessed data for 119 786 patients in Sweden and 391 077 in the UK. 30-day mortality was 7·6% (95% CI 7·4–7·7) in Sweden and 10·5% (10·4–10·6) in the UK. Mortality was higher in the UK in clinically relevant subgroups defined by troponin concentration, ST-segment elevation, age, sex, heart rate, systolic blood pressure, diabetes mellitus status, and smoking status. In Sweden, compared with the UK, there was earlier and more extensive uptake of primary percutaneous coronary intervention (59% vs 22%) and more frequent use of β blockers at discharge (89% vs 78%). After casemix standardisation the 30-day mortality ratio for UK versus Sweden was 1·37 (95% CI 1·30–1·45), which corresponds to 11 263 (95% CI 9620–12 827) excess deaths, but did decline over time (from 1·47, 95% CI 1·38–1·58 in 2004 to 1·20, 1·12–1·29 in 2010; p=0·01).
Interpretation
We found clinically important differences between countries in acute myocardial infarction care and outcomes. International comparisons research might help to improve health systems and prevent deaths.
Background: Sudden cardiac death is common and accounts largely for the excess mortality of patients on maintenance dialysis. It is unknown whether aldosterone and cortisol increase the incidence of sudden cardiac death in dialysis patients.
Methods and results: We analysed data from 1255 diabetic haemodialysis patients participating in the German Diabetes and Dialysis Study (4D Study). Categories of aldosterone and cortisol were determined at baseline and patients were followed for a median of 4 years. By Cox regression analyses, hazard ratios (HRs) were determined for the effect of aldosterone, cortisol, and their combination on sudden death and other adjudicated cardiovascular outcomes. The mean age of the patients was 66 ± 8 years (54% male). Median aldosterone was <15 pg/mL (detection limit) and cortisol 16.8 µg/dL. Patients with aldosterone levels >200 pg/mL had a significantly higher risk of sudden death (HR: 1.69; 95% CI: 1.06–2.69) compared with those with an aldosterone <15 pg/mL. The combined presence of high aldosterone (>200 pg/mL) and high cortisol (>21.1 µg/dL) levels increased the risk of sudden death in striking contrast to patients with low aldosterone (<15 pg/mL) and low cortisol (<13.2 µg/dL) levels (HR: 2.86, 95% CI: 1.32–6.21). Furthermore, all-cause mortality was significantly increased in the patients with high levels of both hormones (HR: 1.62, 95% CI: 1.01–2.62).
Conclusions: The joint presence of high aldosterone and high cortisol levels is strongly associated with sudden cardiac death as well as all-cause mortality in haemodialysed type 2 diabetic patients. Whether a blockade of the mineralocorticoid receptor decreases the risk of sudden death in these patients must be examined in future trials.
Ambalytics: a scalable and distributed system architecture concept for bibliometric network analyses
(2021)
A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations within a given field. With bibliometric analyses, researchers can acquire quantitatively valuable knowledge about a research area by using bibliographic information on academic publications provided by bibliographic data providers. Bibliometric analyses include the calculation of bibliometric networks to describe affiliations or similarities of bibliometric entities (e.g., authors) and group them into clusters representing subareas or communities. Calculating and visualizing bibliometric networks is a nontrivial and time-consuming data science task that requires highly skilled individuals. In addition to domain knowledge, researchers must often provide statistical knowledge and programming skills or use software tools having limited functionality and usability. In this paper, we present the ambalytics bibliometric platform, which reduces the complexity of bibliometric network analysis and the visualization of results. It accompanies users through the process of bibliometric analysis and eliminates the need for individuals to have programming skills and statistical knowledge, while preserving advanced functionality, such as algorithm parameterization, for experts. As a proof-of-concept, and as an example of bibliometric analyses outcomes, the calculation of research fronts networks based on a hybrid similarity approach is shown. Being designed to scale, ambalytics makes use of distributed systems concepts and technologies. It is based on the microservice architecture concept and uses the Kubernetes framework for orchestration. This paper presents the initial building block of a comprehensive bibliometric analysis platform called ambalytics, which aims at a high usability for users as well as scalability.
o build, run, and maintain reliable manufacturing machines, the condition of their components has to be continuously monitored. When following a fine-grained monitoring of these machines, challenges emerge pertaining to the (1) feeding procedure of large amounts of sensor data to downstream processing components and the (2) meaningful analysis of the produced data. Regarding the latter aspect, manifold purposes are addressed by practitioners and researchers. Two analyses of real-world datasets that were generated in production settings are discussed in this paper. More specifically, the analyses had the goals (1) to detect sensor data anomalies for further analyses of a pharma packaging scenario and (2) to predict unfavorable temperature values of a 3D printing machine environment. Based on the results of the analyses, it will be shown that a proper management of machines and their components in industrial manufacturing environments can be efficiently supported by the detection of anomalies. The latter shall help to support the technical evangelists of the production companies more properly.
Process models are crucial artifacts in many domains, and hence, their proper comprehension is of importance. Process models mediate a plethora of aspects that are needed to be comprehended correctly. Novices especially face difficulties in the comprehension of process models, since the correct comprehension of such models requires process modeling expertise and visual observation capabilities to interpret these models correctly. Research from other domains demonstrated that the visual observation capabilities of experts can be conveyed to novices. In order to evaluate the latter in the context of process model comprehension, this paper presents the results from ongoing research, in which gaze data from experts are used as Eye Movement Modeling Examples (EMMEs) to convey visual observation capabilities to novices. Compared to prior results, the application of EMMEs improves process model comprehension significantly for novices. Novices achieved in some cases similar performances in process model comprehension to experts. The study's insights highlight the positive effect of EMMEs on fostering the comprehension of process models.
Background: Tinnitus is often described as the phantom perception of a sound and is experienced by 5.1% to 42.7% of the population worldwide, at least once during their lifetime. The symptoms often reduce the patient's quality of life. The TrackYourTinnitus (TYT) mobile health (mHealth) crowdsensing platform was developed for two operating systems (OS)-Android and iOS-to help patients demystify the daily moment-to-moment variations of their tinnitus symptoms. In all platforms developed for more than one OS, it is important to investigate whether the crowdsensed data predicts the OS that was used in order to understand the degree to which the OS is a confounder that is necessary to consider.
Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.
Health-related quality of life (HRQL) among migrant populations can be associated with acculturation (i.e., the process of adopting, acquiring and adjusting to a new cultural environment). Since there is a lack of longitudinal studies, we aimed to describe HRQL changes among adults of Turkish descent living in Berlin and Essen, Germany, and their association with acculturation. Participants of a population-based study were recruited in 2012–2013 and reinvited six years later to complete a questionnaire. Acculturation was assessed at baseline using the Frankfurt acculturation scale (integration, assimilation, separation and marginalization). HRQL was assessed at baseline (SF-8) and at follow-up (SF-12) resulting in a physical (PCS) and mental (MCS) sum score. Associations with acculturation and HRQL were analyzed with linear regression models using a time-by-acculturation status interaction term. In the study 330 persons were included (65% women, mean age ± standard deviation 43.3 ± 11.8 years). Over the 6 years, MCS decreased, while PCS remained stable. While cross-sectional analyses showed associations of acculturation status with both MCS and PCS, temporal changes including the time interaction term did not reveal associations of baseline acculturation status with HRQL. When investigating HRQL in acculturation, more longitudinal studies are needed to take changes in both HRQL and acculturation status into account.