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Abstract Introduction Asthma is one of the most common chronic diseases in childhood and is generally characterized by exercise induced bronchoconstriction (EIB). Assessing EIB is time consuming and expensive as it requires a fully equipped pulmonary function laboratory. Analysis of volatile organic compounds (VOCs) in breath is a novel technique for examining biomarkers which may associate with asthma features. The aim of this pilot study was to identify potential markers in the relationship between EIB and VOCs. Methods Children between four and 14 years old were asked to provide a breath sample prior to undergoing an exercise challenge test to assess for EIB. Results Breath samples were collected and analyzed in 46 asthmatic children, 21 with EIB and 25 without EIB (NO-EIB). Molecular features (MFs) were not significantly different between EIB and NO-EIB controls. 29 of the 46 children were corticosteroid naïve, 10 with EIB and 13 without. In the corticosteroid naïve group EIB was associated with increased MF23 and MF14 in the lower breath sample (p-value

Abstract Background With the ageing population, the number of older trauma patients has increased. The aim of this study was to assess non-surgical health care costs of older trauma patients and to identify which characteristics of older trauma patients were associated with high health care costs. Methods Trauma patients aged ≥65 years who were admitted to a hospital in Noord-Brabant, the Netherlands, were included in the Brabant Injury Outcome Surveillance (BIOS) study. Non-surgical in-hospital and up to 24- months post-hospital health care use were obtained from hospital registration data and collected with the iMTA Medical Consumption Questionnaire which patients completed 1 week and 1, 3, 6, 12 and 24 months after injury. Log-linked gamma generalized linear models were used to identify cost-driving factors. Results A total of 1910 patients were included in the study. Mean total health care costs per patient were €12,190 ranging from €8390 for 65–69 year-olds to €15,550 for those older than 90 years. Main cost drivers were the post-hospital costs due to home care and stay at an institution. Falls (72%) and traffic injury (15%) contributed most to the total health care costs, although costs of cause of trauma varied with age and sex. In-hospital costs were especially high in patients with high injury severity, frailty and comorbidities. Age, female sex, injury severity, frailty, having comorbidities and having a hip fracture were independently associated with higher post-hospital health care costs. Conclusions In-hospital health care costs were chiefly associated with high injury severity. Several patient and injury characteristics including age, high injury severity, frailty and comorbidity were associated with post-hospital health care costs. Both fall-related injuries and traffic-related injuries are important areas for prevention of injury in the older population.

Abstract Background Of all older patients that opt for elective colorectal surgery, approximately one-third has one or more postoperative complications, particularly those patients with a low cardiorespiratory fitness (ventilatory anaerobic threshold (VAT)

Abstract Background Asthma is one of the most common chronic diseases in childhood. Regular follow-up of physiological parameters in the home setting, in relation to asthma symptoms, can provide complementary quantitative insights into the dynamics of the asthma status. Despite considerable interest in asthma home-monitoring in children, there is a paucity of scientific evidence, especially on multi-parameter monitoring approaches. Therefore, the aim of this study is to investigate whether asthma control can be accurately assessed in the home situation by combining parameters from respiratory physiology sensors. Methods Sixty asthmatic and thirty non-asthmatic children were enrolled in the observational WEARCON-study. Asthma control was assessed according to GINA guidelines by the paediatrician. All children were also evaluated during a 2-week home-monitoring period with wearable devices; a physical activity tracker, a handheld spirometer, smart inhalers, and an ambulatory electrocardiography device to monitor heart and respiratory rate. Multiple logistic regression analysis was used to determine which diagnostic measures were associated with asthma control. Results 24 of the 27 uncontrolled asthmatic children and 29 of the 32 controlled asthmatic children could be accurately identified with this model. The final model showed that a larger variation in pre-exercise lung function (OR = 1.34 95%-CI 1.07–1.68), an earlier wake-up-time (OR = 1.05 95%-CI 1.01–1.10), more reliever use (OR = 1.11 95%-CI 1.03–1.19) and a longer respiratory rate recovery time (OR = 1.12 95%-CI 1.05–1.20) were significant contributors to the probability of having uncontrolled asthma. Conclusions Home-monitoring of physiological parameters correlates with paediatrician assessed asthma control. The constructed multivariate model identifies 88.9% of all uncontrolled asthmatic children, indicating a high potential for monitoring of asthma control. This may allow healthcare professionals to assess asthma control at home. Trial registration Netherlands Trail Register, NL6087 . Registered 14 February 2017.

Abstract Background Within trauma care measurement of changes in health-related quality of life (HRQL) is used in understanding patterns of recovery over time. However, conventionally-measured change in HRQL may not always reflect the change in HRQL as perceived by the patient. Recall bias and response shift may contribute to disagreement between conventional and retrospective change in HRQL. This study aimed to measure conventional and retrospective change of HRQL and assess to which extent recall bias and response shift contribute to disagreement between these two in a heterogeneous sample of adult trauma patients. Methods A sample of trauma patients (≥18 years) who attended the Emergency Department and were admitted to an Intensive Care unit or ward of one of ten Dutch hospitals received postal questionnaires 1 week (T1) and 3 months (T2) post-injury. At T1 and T2 participants completed the EQ-5D-3 L and EQ-VAS for their current health status. At T2 participants also filled out a recall and then-test regarding their health status at T1. The responses were used to assess conventional and retrospective change, recall bias and response shift. Wilcoxon signed rank tests were used to examine conventional and retrospective change on a group level. The intraclass correlation coefficient (ICC) was used to examine individual agreement between conventional and retrospective change. Uni- and multivariate linear regression analysis were used to investigate the association between background factors and recall bias and response shift. Results The EQ-5D-3 L, recall and then-test were completed by 550 patients. Mean EQ-5D-3 L summary score improved from 0.48 at T1 to 0.74 at T2. Mean EQ-VAS score improved from 56 at T1 to 73 at T2. Retrospective change was significantly higher than conventional change (EQ-5D-3 L: Z = -5.2, p

Abstract Background Serial electrocardiography aims to contribute to electrocardiogram (ECG) diagnosis by comparing the ECG under consideration with a previously made ECG in the same individual. Here, we present a novel algorithm to construct dedicated deep-learning neural networks (NNs) that are specialized in detecting newly emerging or aggravating existing cardiac pathology in serial ECGs. Methods We developed a novel deep-learning method for serial ECG analysis and tested its performance in detection of heart failure in post-infarction patients, and in the detection of ischemia in patients who underwent elective percutaneous coronary intervention. Core of the method is the repeated structuring and learning procedure that, when fed with 13 serial ECG difference features (intra-individual differences in: QRS duration; QT interval; QRS maximum; T-wave maximum; QRS integral; T-wave integral; QRS complexity; T-wave complexity; ventricular gradient; QRS-T spatial angle; heart rate; J-point amplitude; and T-wave symmetry), dynamically creates a NN of at most three hidden layers. An optimization process reduces the possibility of obtaining an inefficient NN due to adverse initialization. Results Application of our method to the two clinical ECG databases yielded 3-layer NN architectures, both showing high testing performances (areas under the receiver operating curves were 84% and 83%, respectively). Conclusions Our method was successful in two different clinical serial ECG applications. Further studies will investigate if other problem-specific NNs can successfully be constructed, and even if it will be possible to construct a universal NN to detect any pathologic ECG change.