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Background Helicobacter pylori (H. pylori) is a gram-negative gastrointestinal pathogen that colonises the human stomach and is considered a major risk factor for gastric cancer and mucosa-associated lymphoid tissue lymphoma. Furthermore, H. pylori is a potential trigger of a wide spectrum of extragastric cancer entities, extraintestinal chronic inflammatory processes and autoimmune diseases. In the present study, we evaluated the association between H. pylori infection and its eradication with the development of subsequent gastrointestinal and non-gastrointestinal cancer.Methods We identified 25 317 individuals with and 25 317 matched individuals without a diagnosis of H. pylori from the Disease Analyzer database (IQVIA). A subsequent cancer diagnosis was analysed using Kaplan-Meier and conditional Cox-regression analysis as a function of H. pylori and its eradication.Results After 10 years of follow-up, 12.8% of the H. pylori cohort and 11.8% of the non-H. pylori cohort were diagnosed with cancer (p=0.002). Results were confirmed in regression analysis (HR: 1.11; 95% CI 1.04 to 1.18). Moreover, a non-eradicated H. pylori status (HR: 1.18; 95% CI 1.07 to 1.30) but not an eradicated H. pylori status (HR: 1.06; 95% CI 0.97 to 1.15) was associated with a subsequent diagnosis of cancer. In subgroup analyses, H. pylori eradication was negatively associated with bronchus and lung cancer (HR: 0.60; 95% CI 0.44 to 0.83).Conclusion Our data from a large outpatient cohort in Germany reveal a distinct association between H. pylori infection and the subsequent development of cancer. These data might help to identify patients at risk and support eradication strategies in the future.

Conclusion: Our study provides detailed insight into the incidence, patient-related risk factors, endoscopic treatment, and in-hospital mortality in a sizeable AVH collective in Germany. These data might help improve risk stratification and treatment strategies for AVH patients in the future.

The Index of Cognitive Activity (ICA) was introduced as a promising pupillary workload measure for field investigations since, unlike pupil dilation, it is not affected by illumination. Recent studies have investigated the ICA for task-evoked cognitive workload with contradictory findings. However, few studies investigated the influence of illumination on the ICA. Therefore, to examine inconsistencies regarding the reliability for workload measurement and the effects of light, a meta-analysis was conducted based on a structured literature review. The meta-analysis considered k = 14 studies with a total sample size of N = 751 participants. Results showed significant effects for workload (r = 0.61) and light (r = 0.45) on the ICA. Since moderating effects were found for several between-study differences, it seems likely that different cognitive processes and settings affect the indicator and should be considered in empirical investigations. According to the findings, the ICA is a reliable indicator for task-evoked workload. However, light influences were found which indicates that evidence-based conclusions regarding the ICA's practical applicability require further research.

BackgroundImmune checkpoint inhibitors (ICIs) have led to a paradigm shift in cancer therapy, improving outcomes in the treatment of various malignancies. However, not all patients benefit to the same extend from ICI. Reliable tools to predict treatment response and outcome are missing. Soluble urokinase plasminogen activator receptor (suPAR) is a marker of immune activation, whose levels are prognostic in various cancers. We evaluated circulating suPAR levels as a novel predictive and prognostic biomarker in patients receiving ICI therapy for solid tumors.MethodsA total of n = 87 patients receiving ICI therapy for different solid malignancies as well as 32 healthy controls were included into this study. Serum levels of suPAR were measured by ELISA prior to and sequentially at two time points during ICI therapy.ResultsBaseline suPAR serum levels were significantly higher in solid tumor patients compared to healthy controls. Importantly, patients with low suPAR levels both before or during ICI treatment were more likely to have a favorable response to treatment at three and six months, respectively. This finding was confirmed by multivariate binary logistic regression analysis including several clinicopathological parameters. Moreover, circulating suPAR levels before and during therapy were an independent prognostic factor for overall survival (OS). As such, patients with initial suPAR levels above our ideal prognostic cut-off value (4.86 ng/ml) had a median OS of only 160 days compared to 705 days for patients with suPAR levels below this cut-off value. Finally, low baseline suPAR levels identified a subgroup of patients who experienced ICI-related side effects which in turn were associated with favorable treatment response and outcome.ConclusionOur data suggest that measurements of suPAR serum levels are a previously unknown, easily accessible tool to predict individual treatment response and outcome to ICI therapy. Circulating suPAR might therefore be implemented into stratification algorithms to identify the ideal candidates for ICI treatment.

This paper presents the empirical validation of the time accuracy of the process building block system MTM-HWD® (Human Work Design). The analysis is based on process data collected from 62 different workplaces in German manufacturing companies. The accuracy of the process system is analyzed by studying the frequency of employed process building blocks in the data collection procedure. Subsequently, the differences between the MTM-HWD® and MTM-1 cycle times are evaluated. The findings show that there is no significant difference from samples of prior MTM-1 studies with respect to the frequency of employed MTM-1 process building blocks. It is shown that there is a systematic difference and a linear relationship between the MTM-HWD® and MTM-1 time data. However, it is demonstrated that the relatively larger MTM-HWD® times do not differ more than 5 % from the MTM-1 times when considering the 95 % confidence interval of the mean. These results meet the development aims in terms of the defined accuracy of the method of ± 5 % in comparison to MTM-1.

Abstract Background Fall incidents are a major problem for patients and healthcare. The “Aachen Fall Prevention App” (AFPA) represents the first mobile Health (mHealth) application (app) empowering older patients (persons 50+ years) to self-assess and monitor their individual fall risk. Self-assessment is based on the “Aachen Fall Prevention Scale,” which consists of three steps. First, patients answer ten standardized yes–no questions (positive criterion ≥ 5 “Yes” responses). Second, a ten-second test of free standing without compensatory movement is performed (positive criterion: compensatory movement). Finally, during the third step, patients rate their subjective fall risk on a 10-point Likert scale, based on the results of steps one and two. The purpose of this app is (1) to offer a low-threshold service through which individuals can independently monitor their individual fall risk and (2) to collect data about how a patient-centered mHealth app for fall risk assessment is used in the field. Results The results represent the first year of an ongoing field study. From December 2015 to December 2016, 197 persons downloaded the AFPA (iOS™ and Android™; free of charge). N = 111 of these persons voluntarily shared their data and thereby participated in the field study. Data from a final number of n = 79 persons were analyzed due to exclusion criteria (age, missing objective fall risk, missing self-assessment). The objective fall risk and the self-assessed subjective risk measured by the AFPA showed a significant positive relationship. Conclusions The “Aachen Fall Prevention App” (AFPA) is an mHealth app released for iOS and Android. This field study revealed the AFPA as a promising tool to raise older adults’ awareness of their individual fall risk by means of a low-threshold patient-driven fall risk assessment tool.

Self-measurement and documentation of blood-glucose are critical elements of diabetes management, particularly in regimes including insulin. In this study, we analyze the usability of iBG-STAR, the first blood glucose meter connectable to a smartphone. This technology records glucometer measurements, removing the burden of documentation from diabetic patients. This study assesses the potential for implementation of iBG-STAR in routine care. Twelve long-term diabetic patients (4 males; median age of 66.5 years) were enrolled in the study. N = 4/12 reported diabetic polyneuropathy. Reported subjective mental workload for all tasks related to iBG-STAR was on average lower than 12 points, corresponding to the verbal code 'nearly no effort needed'. A "Post Study System Usability Questionnaire", evaluated the glucometer at an average value of 2.06 (SD = 1.02) on a 7-Likert-scale (1 = 'I fully agree' to 7 = 'I completely disagree') for usability. These results represent a positive user-experience. Patients with polyneuropathy may experience physical difficulties in completing the tasks, thereby affecting usability. Technologically savvy patients (n = 6) with a positive outlook on diabetes assessed the product as a suitable tool for themselves and would recommend to other diabetic patients. The main barrier to regular use was treating physicians' inability to retrieve digitally recorded data. This barrier was due to a shortcoming in interoperability of mobile devices and medical information systems.

PURPOSE:A wealth of mobile applications are designed to support users in their drug intake. When developing software for patients, it is important to understand the differences between individuals who have, who will or who might never adopt mobile interventions. This study analyzes demographic and health-related factors associated with real-life "longer usage" and the "usage-intensity per day" of the mobile application "Medication Plan". METHODS:Between 2010-2012, the mobile application "Medication Plan" could be downloaded free of charge from the Apple-App-Store. It was aimed at supporting the regular and correct intake of medication. Demographic and health-related data were collected via an online questionnaire. This study analyzed captured data. RESULTS:App-related activities of 1799 users (1708 complete data sets) were recorded. 69% (1183/1708) applied "Medication Plan" for more than a day. 74% were male (872/1183), the median age 45 years. Variance analysis showed a significant effect of the users' age with respect to duration of usage (p = 0.025). While the mean duration of use was only 23.3 days for users younger than 21 years, for older users, there was a substantial increase over all age cohorts up to users of 60 years and above (103.9 days). Sex and educational status had no effect. "Daily usage intensity" was directly associated with an increasing number of prescribed medications and increased from an average of 1.87 uses per day and 1 drug per day to on average 3.71 uses per day for users stating to be taking more than 7 different drugs a day (p