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The traditional picture of cancer patients as weak individuals requiring maximum rest and protection is beginning to dissolve. Too much focus on the medical side and one’s own vulnerability and mortality might be counterproductive and not doing justice to the complexity of human nature. Unlike cytotoxic and lympho-depleting treatments, immune-engaging therapies strengthen the immune system and are typically less harmful for patients. Thus, cancer patients receiving checkpoint inhibitors are not viewed as being vulnerable per se, at least not in immunological and physical terms. This perspective article advocates a holistic approach to cancer immunotherapy, with an empowered patient in the center, focusing on personal resources and receiving domain-specific support from healthcare professionals. It summarizes recent evidence on non-pharmaceutical interventions to enhance the efficacy of immune checkpoint blockade and improve quality of life. These interventions target behavioral factors such as diet, physical activity, stress management, circadian timing of checkpoint inhibitor infusion, and waiving unnecessary co-medication curtailing immunotherapy efficacy. Non-pharmaceutical interventions are universally accessible, broadly applicable, instantly actionable, scalable, and economically sustainable, creating value for all stakeholders involved. Most importantly, this holistic framework re-emphasizes the patient as a whole and harnesses the full potential of anticancer immunity and checkpoint blockade, potentially leading to survival benefits. Digital therapeutics are proposed to accompany the patients on their mission toward change in lifestyle-related behaviors for creating optimal conditions for treatment efficacy and personal growth.

Cough, a symptom associated with many prevalent respiratory diseases, can serve as a potential biomarker for diagnosis and disease progression. Consequently, the development of cough monitoring systems and, in particular, automatic cough detection algorithms have been studied since the early 2000s. Recently, there has been an increased focus on the efficiency of such algorithms, as implementation on consumer-centric devices such as smartphones would provide a scalable and affordable solution for monitoring cough with contact-free sensors. Current algorithms, however, are incapable of discerning between coughs of different individuals and, thus, cannot function reliably in situations where potentially multiple individuals have to be monitored in shared environments. Therefore, we propose a weakly supervised metric learning approach for cougher recognition based on smartphone audio recordings of coughs. Our approach involves a triplet network architecture, which employs convolutional neural networks (CNNs). The CNNs of the triplet network learn an embedding function, which maps Mel spectrograms of cough recordings to an embedding space where they are more easily distinguishable. Using audio recordings of nocturnal coughs from asthmatic patients captured with a smartphone, our approach achieved a mean accuracyof 88 % ( ± 10 % SD) on two-way identification tests with 12 enrollment samples and accuracy of 80 % and an equal error rate (EER) of 20 % on verification tests. Furthermore, our approach outperformed human raters with regard to verification tests on average by 8% in accuracy, 4% in false acceptance rate (FAR), and 12% in false rejection rate (FRR). Our code and models are publicly available.

Background We showed excellent adherence and satisfaction with our telehealth care (TC) approach for COPD. Here, the results of a consecutive randomized controlled trial are presented. Methods Patients were randomly assigned to TC or standard care (SC). During TC, patients answered six daily questions online, and focused on the early recognition of exacerbations, in addition to SC. Results The mean increase in COPD assessment test (CAT) was 1.8 vs. 3.6 points/year in the TC and SC groups, respectively (P = 0.0015). Satisfaction with care (VAS) at baseline was 8.2; at the end of SC, 8.5 (P = 0.062); and after TC, 8.8 (P < 0.001). We detected significantly more moderate exacerbations during TC. Conclusion Whilst receiving TC, the slope of the CAT increase – an indicator of the naturally progressive course of COPD – was reduced by 50%. Satisfaction with care increased with TC. The higher number of detected moderate exacerbations probably indicates a higher diagnostic sensitivity than without TC.

Frank Rassouli,1,* Peter Tinschert,2,* Filipe Barata,3 Claudia Steurer-Stey,4,5 Elgar Fleisch,2,3 Milo Alan Puhan,4 Florent Baty,1 Tobias Kowatsch,2,3 Martin Hugo Brutsche1 1Lung Center, Cantonal Hospital St. Gallen, St. Gallen, Switzerland; 2Center for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland; 3Center for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland; 4Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland; 5mediX Group Practice Zurich, Zurich, Switzerland*These authors contributed equally to this workCorrespondence: Frank RassouliLung Center, Cantonal Hospital St. Gallen, Rorschacher Strasse 95, St. Gallen CH-9007, SwitzerlandTel +41 71 494 60 20Email Frank.Rassouli@kssg.chIntroduction: The nature of nocturnal cough is largely unknown. It might be a valid marker for asthma control but very few studies characterized it as a basis for better defining its role and its use as clinical marker. This study investigated prevalence and characteristics of nocturnal cough in asthmatics over the course of four weeks.Methods: In two centers, 94 adult patients with physician-diagnosed asthma were recruited. Patient-reported outcomes and nocturnal sensor data were collected by a smartphone with a chat-based study app.Results: Patients coughed in 53% of 2212 nights (range: 0– 345 coughs/night). Median coughs per hour were 0 (IQR 0– 1). Nocturnal cough rates showed considerable inter-individual variance. The highest counts were measured in the first 30 min in bed (4.5-fold higher than rest of night). Eighty-six percent of coughs were part of a cough cluster. Clusters consisted of a median of two coughs (IQR 2– 4). Nocturnal cough was persistent within patient.Conclusion: To the best of the authors’ knowledge, this study is the first to describe prevalence and

Peter Tinschert,1,* Frank Rassouli,2,* Filipe Barata,3 Claudia Steurer-Stey,4,5 Elgar Fleisch,1,3 Milo Alan Puhan,4 Tobias Kowatsch,1,3 Martin Hugo Brutsche2 1Center for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland; 2Lung Center, Cantonal Hospital St. Gallen, St. Gallen, Switzerland; 3Center for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland; 4Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland; 5mediX Group Practice Zurich, Zurich, Switzerland*These authors contributed equally to this workCorrespondence: Peter TinschertCenter for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, Dufourstrasse 40a, CH-9000, St. Gallen, SwitzerlandTel +41 76 403 34 66Email peter.tinschert@unisg.chIntroduction: Objective markers for asthma, that can be measured without extra patient effort, could mitigate current shortcomings in asthma monitoring. We investigated whether smartphone-recorded nocturnal cough and sleep quality can be utilized for the detection of periods with uncontrolled asthma or meaningful changes in asthma control and for the prediction of asthma attacks.Methods: We analyzed questionnaire and sensor data of 79 adults with asthma. Data were collected in situ for 29 days by means of a smartphone. Sleep quality and nocturnal cough frequencies were measured every night with the Pittsburgh Sleep Quality Index and by manually annotating coughs from smartphone audio recordings. Primary endpoint was asthma control assessed with a weekly version of the Asthma Control Test. Secondary endpoint was self-reported asthma attacks.Results: Mixed-effects regression analyses showed that nocturnal cough and sleep quality were statistically significantly associated with asthma control on a between- and within-patient level (p < 0.05). Decision trees indicated

BACKGROUND: Asthma is one of the most prevalent chronic respiratory diseases. Despite increased investment in treatment, little progress has been made in the early recognition and treatment of asthma exacerbations over the last decade. Nocturnal cough monitoring may provide an opportunity to identify patients at risk for imminent exacerbations. Recently developed approaches enable smartphone-based cough monitoring. These approaches, however, have not undergone longitudinal overnight testing nor have they been specifically evaluated in the context of asthma. Also, the problem of distinguishing partner coughs from patient coughs when two or more people are sleeping in the same room using contact-free audio recordings remains unsolved. OBJECTIVE: The objective of this study was to evaluate the automatic recognition and segmentation of nocturnal asthmatic coughs and cough epochs in smartphone-based audio recordings that were collected in the field. We also aimed to distinguish partner coughs from patient coughs in contact-free audio recordings by classifying coughs based on sex. METHODS: We used a convolutional neural network model that we had developed in previous work for automated cough recognition. We further used techniques (such as ensemble learning, minibatch balancing, and thresholding) to address the imbalance in the data set. We evaluated the classifier in a classification task and a segmentation task. The cough-recognition classifier served as the basis for the cough-segmentation classifier from continuous audio recordings. We compared automated cough and cough-epoch counts to human-annotated cough and cough-epoch counts. We employed Gaussian mixture models to build a classifier for cough and cough-epoch signals based on sex. RESULTS: We recorded audio data from 94 adults with asthma (overall: mean 43 years; SD 16 years; female: 54/94, 57%; male 40/94, 43%). Audio data were recorded by each participant in their everyday environment using a smartphone placed n

Background: Pneumococcal pneumonia is a disease of the extremes of age. However, as other traditional risk factors for pneumococcal pneumonia also increase with older age, it is unclear if older age itself should be an indication for pneumococcal vaccination. Therefore, we assessed the effect of age on risk for hospitalization for pneumonia and for pneumococcal pneumonia. Methods: Using a national hospitalization dataset, all patients ≥16 years hospitalized in a Swiss hospital with a diagnosis of pneumonia or pneumococcal pneumonia between 2002 and 2015 were included. Multivariable logistic regression analysis was used to test the association between age (≥50 or ≥65 years) and hospitalization for pneumonia or pneumococcal pneumonia after adjusting for pneumococcal vaccine indications. Similar analyses were performed for effect of age on length of stay (LOS) and mortality. Results: Among a total of 17,619,016 hospitalizations a diagnosis of pneumonia was present in 421,760 (2.4%) and a diagnosis of pneumococcal pneumonia in 21,610 (0.12%). Age ≥50 years (OR: 3.52 and 2.12, respectively; p for both <0.001) and age ≥65 years (OR: 2.98 and 1.80, respectively; p for both <0.001) as well as most Swiss pneumococcal vaccine indications were independent predictors of hospitalization with a pneumonia and pneumococcal pneumonia diagnosis, respectively. Older age with both age cut-offs were associated with increased LOS (≥50 years: aRR: 1.19 and 1.24, respectively; age ≥65 years: aRR: 1.60 and 1.20, respectively; p < 0.001 for all) and mortality (≥50 years: aOR: 4.73 and 2.84, respectively; age ≥65 years: aOR: 2.38 and 2.69, respectively, p < 0.001 for all) in patients with a pneumonia and pneumococcal pneumonia diagnosis, respectively. The effects of pneumococcal vaccine indications decreased with older age. The incidences of hospitalizations with a pneumonia diagnosis and a pneumococcal pneumonia diagnosis increased significantly from the pre-vaccine era to the PCV7 era and t

INTRODUCTION Nocturnal cough is a burdensome asthma symptom. However, knowledge about the prevalence of nocturnal cough in asthma is limited. Furthermore, prior research has shown that nocturnal cough and impaired sleep quality are associated with asthma control, but the association between these two symptoms remains unclear. This study further investigates the potential of these symptoms as markers for asthma control and the accuracy of automated, smartphone-based passive monitoring for nocturnal cough detection and sleep quality assessment. METHODS AND ANALYSIS The study is a multicentre, longitudinal observational study with two stages. Sensor and questionnaire data of 94 individuals with asthma will be recorded for 28 nights by means of a smartphone. On the first and the last study day, a participant's asthma will be clinically assessed, including spirometry and fractionated exhaled nitric oxide levels. Asthma control will be assessed by the Asthma Control Test and sleep quality by means of the Pittsburgh Sleep Quality Index. In addition, nocturnal coughs from smartphone microphone recordings will be labelled and counted by human annotators. Relatively unrestrictive eligibility criteria for study participation are set to support external validity of study results. Analysis of the first stage is concerned with the prevalence and trends of nocturnal cough and the accuracies of smartphone-based automated detection of nocturnal cough and sleep quality. In the second stage, patient-reported asthma control will be predicted in a mixed effects regression model with nocturnal cough frequencies and sleep quality of past nights as the main predictors. ETHICS AND DISSEMINATION The study was reviewed and approved by the ethics commission responsible for research involving humans in eastern Switzerland (BASEC ID: 2017-01872). All study data will be anonymised on study termination. Results will be published in medical and technical peer-reviewed journals. TRIAL REGISTRATION N