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The consequences of traumatic brain injury (TBI) for health-related quality of life (HRQoL) are poorly investigated, and a TBI-specific instrument has not previously been available. The cross-cultural development of a new measure to assess HRQoL after TBI is described here. An international TBI Task Force derived a conceptual model from previous work, constructed an initial item bank of 148 items, and then reduced the item set through two successive multicenter validation studies. The first study, with eight language versions of the QOLIBRI, recruited 1528 participants with TBI, and the second with six language versions, recruited 921 participants. The data from 795 participants from the second study who had complete Glasgow Coma Scale (GCS) and Glasgow Outcome Scale (GOS) data were used to finalize the instrument. The final version of the QOLIBRI consists of 37 items in six scales (see Appendix). Satisfaction is assessed in the areas of “Cognition,” “Self,” “Daily Life and Autonomy,” and “Social Relationships,” and feeling bothered by “Emotions,” and “Physical Problems.” The QOLIBRI scales meet standard psychometric criteria (internal consistency, α = 0.75–0.89, test-retest reliability, rtt = 0.78–0.85). Test-retest reliability (rtt = 0.68–0.87) as well as internal consistency (α = 0.81–0.91) were also good in a subgroup of participants with lower cognitive performance. Although there is one strong HRQoL factor, a six-scale structure explaining additional variance was validated by exploratory and confirmatory factor analyses, and with Rasch modeling. The QOLIBRI is a new cross-culturally developed instrument for assessing HRQoL after TBI that fulfills standard psychometric criteria. It is potentially useful for clinicians and researchers conducting clinical trials, for assessing the impact of rehabilitation or other interventions, and for carrying out epidemiological surveys.

Medical students report high demands, stressors, pressure to perform, and a lack of resources, and are therefore at a higher risk for mental strain and burnout. Due to the COVID-19 pandemic, study conditions have changed, and new challenges have emerged. Thus, this study aimed to examine medical students’ well-being, mental health, and study characteristics before and during the pandemic. Data from 988 Austrian medical students were included into the cross-sectional comparisons, and 63 students were included into the longitudinal analyses (variance analyses/t-tests or appropriate non-parametric tests). Well-being before and during the pandemic did not differ significantly but the peri-pandemic cohort reported higher study satisfaction, more social support from lecturers, and less emotional exhaustion, cognitive demands, and stressors (information problems, organizational stressors, work overload). Longitudinally, work overload was also perceived to be higher before the pandemic; however, study satisfaction was lower. During the pandemic, approximately every seventh student exceeded the cut-off value for generalized anxiety disorder, and approximately every tenth student exceeded the cut-off value for major depression. These unexpected peri-pandemic results concerning constant high well-being, study satisfaction, and the perception of conditions may be based on response shift effects that require further exploration. The scores exceeding the reasonable cut-point for identifying probable cases of generalized anxiety disorder and depression may reflect medical students’ needs, calling for an in-depth analysis if further health promotion is necessary.

Home and telehealth-based interventions are increasingly used in cardiac rehabilitation, a multidisciplinary model of health care. Digital tools such as wearables or digital training diaries are expected to support patients to adhere to recommended lifestyle changes, including physical exercise programs. As previously published, the EPICURE study (effect of digital tools in outpatient cardiac rehabilitation including home training) analyzed the effects of digital tools, that is, a digital training diary, adherence monitoring, and wearables, on exercise capacity during outpatient cardiac rehabilitation phase III (OUT-III) which includes an approximately 12-week home-training phase. The study encompassed 149 Austrian patients, of which 50 used digital tools. The present paper takes a deeper look into the EPICURE data to better understand the relation between the use of digital tools and various psychological, clinical, and physiological parameters, and the relation between these parameters and the improvement of exercise capacity during cardiac rehabilitation. For this work, we analyzed questionnaires concerning the patients' cardiac rehabilitation. On all these parameters we performed 2 analyzes: (1) Comparison of the 2 groups with and without digital tools and (2) correlation with the change in the maximum workload as achieved during the exercise stress test. If data pre- and post OUT-III were available, the change in the respective parameter during OUT-III was determined and group analysis and correlation were applied on data pre OUT-III, data post OUT-III, and the change during OUT-III. We found significant improvements in quality of life in both groups, with no discernible differences between patients with or without digital tools (P=.53). Patients with digital tools perceived significantly higher competence during cardiac rehabilitation (P=.05), and they anticipated higher cardiac risks if nonadherent to physical activity (P=.03). Although, the overall subjectively reported adherence was not significantly different in the 2 groups (P=.50), specific items differed. Patients with digital tools were significantly more likely to do their exercises even when they were tired (P=.01) and less likely to forget their exercises (P=.01). Concerning reasons for (non-) adherence, patients with digital tools reported significantly more often to do their exercises because they enjoyed them (P=.01), whereas they were significantly less likely to stop exercising when muscular pain was worse (P=.01) and to continue doing their exercises when muscular pain improved (P=.02). Finally, patients who reported a high level of concrete planning achieved significantly higher improvements in exercise capacity (r=0.14, P=.04). This comprehensive analysis provides valuable insights into the multifaceted impact of digital tools on outpatient cardiac rehabilitation including home training, shedding light on the importance of digital tools for increased competence and a higher risk perception during cardiac rehabilitation. In addition, the impact of digital tools on adherence and their influence on patient outcomes were assessed in the evolving landscape of digital health interventions.

Psychosocial, emotional, and physical problems can emerge after traumatic brain injury (TBI), potentially impacting health-related quality of life (HRQoL). Until now, however, neither the discriminatory power of disease-specific (QOLIBRI) and generic (SF-36) HRQoL nor their correlates have been compared in detail. These aspects as well as some psychometric item characteristics were studied in a sample of 795 TBI survivors. The Shannon H ' index absolute informativity, as an indicator of an instrument’s power to differentiate between individuals within a specific group or health state, was investigated. Psychometric performance of the two instruments was predominantly good, generally higher, and more homogenous for the QOLIBRI than for the SF-36 subscales. Notably, the SF-36 “Role Physical,” “Role Emotional,” and “Social Functioning” subscales showed less satisfactory discriminatory power than all other dimensions or the sum scores of both instruments. The absolute informativity of disease-specific as well as generic HRQoL instruments concerning the different groups defined by different correlates differed significantly. When the focus is on how a certain subscale or sum score differentiates between individuals in one specific dimension/health state, the QOLIBRI can be recommended as the preferable instrument.

BackgroundDespite high success rates, flap failure remains an inherent risk in microvascular breast reconstruction. Identifying patients who are at high risk for flap failure would enable us to recommend alternative reconstructive techniques. However, as flap failure is a rare event, identification of risk factors is statistically challenging. Machine learning is a form of artificial intelligence that automates analytical model building. It has been proposed that machine learning can build superior prediction models when the outcome of interest is rare.MethodsIn this study we evaluate machine learning resampling and decision-tree classification models for the prediction of flap failure in a large retrospective cohort of microvascular breast reconstructions.ResultsA total of 1012 patients were included in the study. Twelve patients (1.1%) experienced flap failure. The ROSE informed oversampling technique and decision-tree classification resulted in a strong prediction model (AUC 0.95) with high sensitivity and specificity. In the testing cohort, the model maintained acceptable specificity and predictive power (AUC 0.67), but sensitivity was reduced. The model identified four high-risk patient groups. Obesity, comorbidities and smoking were found to contribute to flap loss. The flap failure rate in high-risk patients was 7.8% compared with 0.44% in the low-risk cohort (p = 0.001).ConclusionsThis machine-learning risk prediction model suggests that flap failure may not be a random event. The algorithm indicates that flap failure is multifactorial and identifies a number of potential contributing factors that warrant further investigation.

The aim of this study is to validate the Danish, Norwegian and Swedish versions of the self-administered MacNew Heart Disease Health-related Quality of Life questionnaire in patients with ischemic heart disease. The MacNew questionnaire, the Short Form SF-36, and the Hospital Anxiety and Depression Scale were completed at baseline by 976 patients (Denmark n = 353, Norway n = 328, Sweden n = 295) with a diagnosis of angina (n = 335), myocardial infarction (n = 352), or heart failure (n = 289). Each language version of the Macnew satisfied reliability criteria with Cronbach's α values for the total group data (0.90–0.94) as well as the diagnostic group data (0.91–0.96). The test–retest correlations exceeded the criteria for group comparison (r ≥ 0.70) in Danish and Norwegian patients. The multidimensionality of the MacNew was confirmed although the original three-factor solution did not fully meet the criteria for good fit. Convergent and discriminative validity were confirmed in each language and diagnosis group with the exception of discriminative validity in Swedish angina patients. The psychometric properties of the Danish, Norwegian, and Swedish versions of the MacNew are largely confirmed. The MacNew can be recommended as a specific instrument for assessing and evaluating HRQL in Danish, Norwegian, and Swedish patients with angina, MI, and heart failure. However, the MacNew factor structure needs to be revisited in future studies.

Cardiovascular diseases are the leading cause of death worldwide and are partly caused by modifiable risk factors. Cardiac rehabilitation addresses several of these modifiable risk factors, such as physical inactivity and reduced exercise capacity. However, despite its proven short-term merits, long-term adherence to healthy lifestyle changes is disappointing. With regards to exercise training, it has been shown that rehabilitation supplemented by a) home-based exercise training and b) supportive digital tools can improve adherence. In our multi-center study (ClincalTrials.gov Identifier: NCT04458727), we analyzed the effect of supportive digital tools like digital diaries and/or wearables such as smart watches, activity trackers, etc. on exercise capacity during cardiac rehabilitation. Patients after completion of phase III out-patient cardiac rehabilitation, which included a 3 to 6-months lasting home-training phase, were recruited in five cardiac rehabilitation centers in Austria. Retrospective rehabilitation data were analyzed, and additional data were generated via patient questionnaires. 107 patients who did not use supportive tools and 50 patients using supportive tools were recruited. Already prior to phase III rehabilitation, patients with supportive tools showed higher exercise capacity (  = 186 ± 53 W) as compared to patients without supportive tools (142 ± 41 W,  < 0.001). Both groups improved their , significantly during phase III rehabilitation, and despite higher baseline of patients with supportive tools their improved significantly more (  = 19 ± 18 W) than patients without supportive tools (  = 9 ± 17 W,  < 0.005). However, after adjusting for baseline differences, the difference in did no longer reach statistical significance. Therefore, our data did not support the hypothesis that the additional use of digital tools like digital diaries and/or wearables during home training leads to further improvement in P during and after phase III cardiac rehabilitation. Further studies with larger sample size, follow-up examinations and a randomized, controlled design are required to assess merits of digital interventions during cardiac rehabilitation.

Chronic postsurgical pain (CPSP), an often unanticipated result of necessary and even life-saving procedures, develops in 5-10% of patients one-year after major surgery. Substantial advances have been made in identifying patients at elevated risk of developing CPSP based on perioperative pain, opioid use, and negative affect, including depression, anxiety, pain catastrophizing, and posttraumatic stress disorder-like symptoms. The Transitional Pain Service (TPS) at Toronto General Hospital (TGH) is the first to comprehensively address the problem of CPSP at three stages: 1) preoperatively, 2) postoperatively in hospital, and 3) postoperatively in an outpatient setting for up to 6 months after surgery. Patients at high risk for CPSP are identified early and offered coordinated and comprehensive care by the multidisciplinary team consisting of pain physicians, advanced practice nurses, psychologists, and physiotherapists. Access to expert intervention through the Transitional Pain Service bypasses typically long wait times for surgical patients to be referred and seen in chronic pain clinics. This affords the opportunity to impact patients' pain trajectories, preventing the transition from acute to chronic pain, and reducing suffering, disability, and health care costs. In this report, we describe the workings of the Transitional Pain Service at Toronto General Hospital, including the clinical algorithm used to identify patients, and clinical services offered to patients as they transition through the stages of surgical recovery. We describe the role of the psychological treatment, which draws on innovations in Acceptance and Commitment Therapy that allow for brief and effective behavioral interventions to be applied transdiagnostically and preventatively. Finally, we describe our vision for future growth.

Future climate projections show a marked increase in Greenland Ice Sheet (GrIS) runoff during the 21 st century, a direct consequence of the Polar Amplification signal. Regional climate models (RCMs) are a widely used tool to downscale ensembles of projections from global climate models (GCMs) to assess the impact of global warming on GrIS melt and sea level rise contribution. Initial results of the CMIP6 GCM model intercomparison project have revealed a greater 21 st century temperature rise than in CMIP5 models. However, so far very little is known about the subsequent impacts on the future GrIS surface melt and therefore sea level rise contribution. Here, we show that the total GrIS sea level rise contribution from surface mass loss in our high-resolution (15 km) regional climate projections is 17.8  ±  7.8 cm in SSP585, 7.9 cm more than in our RCP8.5 simulations using CMIP5 input. We identify a +1.3 °C greater Arctic Amplification and associated cloud and sea ice feedbacks in the CMIP6 SSP585 scenario as the main drivers. Additionally, an assessment of the GrIS sea level contribution across all emission scenarios highlights, that the GrIS mass loss in CMIP6 is equivalent to a CMIP5 scenario with twice the global radiative forcing. The potential contribution of Greenland Ice Sheet to sea level rise in the future is known to be substantial. Here, the authors undertake new modelling showing that the Greenland Ice Sheet sea level rise contribution is 7.9 cm more using the CMIP6 SSP585 scenario compared to CMIP5 using multiple RCP8.5 simulations.