Search

Abstract Background The purpose of this qualitative study was to identify emergent rehabilitation innovations and clinician perceptions influencing their implementation and outcomes related to hospital discharge decision-making during the Coronavirus 2019 pandemic. Methods Rehabilitation clinicians were recruited from the Veterans Affairs Health Care System and participated in individual semi-structured interviews guided by the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework. Data were analyzed using a rapid qualitative, deductive team-based approach informed by directed content analysis. Results Twenty-three rehabilitation clinicians representing physical (N = 11) and occupational therapy (N = 12) participated in the study. Three primary themes were generated: (1) Innovation: emerging innovations in discharge processes included perceived increases in team collaboration, shifts in caseload prioritization, and alternative options for post-acute care. (2) Recipients: innovations emerged as approaches to communicating discharge recommendations changed (in-person to virtual) and strong patient/family preferences to discharge to the home challenged collaborative goal setting; and (3) Context: the ability of rehabilitation clinicians to innovate and the form of innovations were influenced by the broader hospital system, interdisciplinary team dynamics, and policy fluctuations. Innovations described by participants included (1) use of technological modalities for interdisciplinary collaboration, (2) expansion of telehealth modalities to deliver care in the home, (3) changes in acute care case prioritization, and (4) alternative options for discharge directly to home. Conclusions Our findings reinforce that rehabilitation clinicians developed innovative strategies to quickly adapt to multiple systems-level factors that were changing in the face of the COVID-19 pandemic. Future research is needed to assess the impact of innovations, remediate unintended consequences, and evaluate the implementation of promising innovations to respond to emerging healthcare delivery needs more rapidly.

Background: Postoperative cognitive decline (POCD) after cardiosurgical interventions are well described through objective psychometric tests. However, a patient’s subjective perception is essential to clinical assessment and quality of life. This study systematically evaluated patient-reported POCD between subjects undergoing coronary artery bypass grafting and heart valve replacement. Methods: This study was a multicentre, prospective questionnaire survey conducted at the cardiac surgery departments at the Kerckhoff Clinic in Bad Nauheim and the University Hospital in Giessen, Germany. We included patients undergoing elective coronary artery bypass grafting (CABG), aortic valve replacement (AVR), mitral valve replacement or reconstruction (MVR), and combined surgery (CABG + valve replacement [VR]) with extracorporeal circulation. The Hospital Anxiety and Depression Scale, the Cognitive Failures Questionnaire (CFQ) for Self-assessment (CFQ-S), and the external assessment (CFQ-foreign [F]) were completed preoperatively, as well as at 3 and 12 months postoperatively. Results: A total of 491 patients were available for analyses (CABG = 182, AVR = 134, MVR = 93, CABG + VR = 82). POCD and postoperative depression increase (PODI) were observed for each surgical procedure. (At the 3-month follow-up: CFQ-S [CABG = 7.1%, AVR = 3.7%, MVR = 9.7%, CABG + VR = 9.8%]; CFQ-F [CABG = 9.9%, AVR = 9.7%, MVR = 9.7%, CABG + VR = 15.9%]; PODI [CABG = 7.7%, AVR = 9.7%, MVR = 6.5%, CABG + VR = 8.5%]. At the 12-month follow-up: CFQ-S [CABG = 6.6%, AVR = 7.5%, MVR = 15.1%, CABG + VR = 7.3%]; CFQ-F [CABG = 7.1%, AVR = 14.9%, MVR = 10.8%, CABG + VR = 9.8%]; PODI [CABG = 10.4%, AVR = 11.2%, MVR = 6.5%, CABG + VR = 4.9%]). No significant between-group effects were observed for the CFQ-S, CFQ-F, or the Hospital Anxiety and Depression Scale. Conclusions: For clinicians, paying attention to patients' self-reported experiences of reduced cognitive function and symptoms of depression following cardiac surgery is important. Such reporting is an indication that interventions such as cognitive training or psychotherapy should be considered. Résumé: Contexte: Le déclin cognitif postopératoire (DCPO) à la suite d’interventions de chirurgie cardiaque est bien décrit par des évaluations psychométriques objectives. Cependant, la perception subjective du patient est essentielle à l’évaluation clinique et à la qualité de vie. Cette étude visait à évaluer de façon systématique le DCPO déclaré par le patient chez des sujets ayant subi un pontage aortocoronarien ou une chirurgie valvulaire. Méthodologie: Cette étude prospective multicentrique par questionnaire a été menée aux services de chirurgie cardiaque de la clinique Kerckhoff de Bad Nauheim et de l’hôpital universitaire de Giessen, en Allemagne. Elle a porté sur des patients ayant subi un pontage aortocoronarien (PAC), un remplacement valvulaire aortique (RVA), un remplacement ou une reconstruction de la valvule mitrale (RVM) ou une chirurgie combinée (PAC et remplacement valvulaire [RV]) avec circulation extracorporelle, en situation non urgente. L’échelle d’évaluation de l’anxiété et de la dépression à l’hôpital (HADS), le questionnaire d’auto-évaluation des déficits cognitifs (CFQ-S) et le questionnaire d’évaluation externe des déficits cognitifs (CFQ-F) ont été remplis avant l’intervention chirurgicale, ainsi que 3 et 12 mois après la chirurgie. Résultats: Au total, les résultats de 491 patients étaient disponibles aux fins d’analyses (PAC = 182, RVA = 134, RVM = 93, PAC et RV = 82). Des cas de DCPO et une augmentation postopératoire des symptômes de dépression (APOD) ont été observés après chacune des interventions chirurgicales. (Lors du suivi après 3 mois : DCPO selon le CFQ-S [PAC = 7,1 %, RVA = 3,7 %, RVM = 9,7 %, PAC + RV = 9,8 %]; DCPO selon le CFQ-F [PAC = 9,9 %, RVA = 9,7 %, RVM = 9,7 %, PAC + RV = 15,9 %]; APOD [PAC = 7,7 %, RVA = 9,7 %, RVM = 6,5 %, PAC + RV = 8,5 %]. Lors du suivi après 12 mois : DCPO selon le CFQ-S [PAC = 6,6 %, RVA = 7,5 %, RVM = 15,1 %, PAC + RV = 7,3 %]; DCPO selon le CFQ-F [PAC= 7,1 %, RVA = 14,9 %, RVM = 10,8 %, PAC+ RV = 9,8 %]; APOD [PAC = 10,4 %, RVA = 11,2 %, RVM = 6,5 %, PAC + RV = 4,9 %]). Aucun effet intergroupe significatif n’a été observé relativement aux questionnaires CFQ-S et CFQ-F ou à l’échelle HADS. Conclusions: Il est important que les cliniciens portent attention aux déclarations des patients en ce qui concerne la diminution des fonctions cognitives et les symptômes de dépression à la suite d’une chirurgie cardiaque. De telles déclarations sont une indication que des interventions comme l’entraînement cognitif ou la psychothérapie doivent être envisagées.

Abstract Background Obesity is a known cardiovascular risk factor and associated with higher postoperative complication rates in patients undergoing cardiac surgery. In heart failure (HF), conflicting evidence in terms of survival has been reported, whereas sarcopenia is associated with poor prognosis. An increasing number of HF patients require left ventricular assist device (LVAD) implantations. The postoperative mortality has improved in recent years but is still relatively high. The impact of body composition on outcome in this population remains unclear. The aim of this investigation was to examine the preoperative computed tomography (CT) body composition as a predictor of the postoperative outcome in advanced HF patients, who receive LVAD implantations. Methods Preoperative CT scans of 137 patients who received LVADs between 2015 and 2020 were retrospectively analysed using an artificial intelligence (AI)‐powered automated software tool based on a convolutional neural network, U‐net, developed for image segmentation (Visage Version 7.1, Visage Imaging GmbH, Berlin, Germany). Assessment of body composition included visceral and subcutaneous adipose tissue areas (VAT and SAT), psoas and total abdominal muscle areas and sarcopenia (defined by lumbar skeletal muscle indexes). The body composition parameters were correlated with postoperative major complication rates, survival and postoperative 6‐min walk distance (6MWD) and quality of life (QoL). Results The mean age of patients was 58.21 ± 11.9 years; 122 (89.1%) were male. Most patients had severe HF requiring inotropes (Interagency Registry for Mechanically Assisted Circulatory Support [INTERMACS] profile I–III, 71.9%) secondary to coronary artery diseases or dilated cardiomyopathy (96.4%). Forty‐four (32.1%) patients were obese (body mass index ≥ 30 kg/m2), 96 (70.1%) were sarcopene and 19 (13.9%) were sarcopene obese. Adipose tissue was associated with a significantly higher risk of postoperative infections (VAT 172.23 cm2 [54.96, 288.32 cm2] vs. 124.04 cm2 [56.57, 186.25 cm2], P = 0.022) and in‐hospital mortality (VAT 168.11 cm2 [134.19, 285.27 cm2] vs. 135.42 cm2 [49.44, 227.91 cm2], P = 0.033; SAT 227.28 cm2 [139.38, 304.35 cm2] vs. 173.81 cm2 [97.65, 254.16 cm2], P = 0.009). Obese patients showed no improvement of 6MWD and QoL within 6 months postoperatively (obese: +0.94 ± 161.44 months, P = 0.982; non‐obese: +166.90 ± 139.00 months, P

Most applications of virtual reality and technology used in counseling occur in the context of client intervention and treatment. This article presents how virtual enhanced education tools such as virtual reality, augmented reality, and 360° videos provide a stage for constructing creative opportunities for experiential learning in counselor education.

Abstract Background Several software tools have been developed for gated PET imaging that use distinct algorithms to analyze tracer uptake, myocardial perfusion, and left ventricle volumes and function. Studies suggest that different software tools cannot be used interchangeably in humans. In this study, we sought to compare the left ventricular parameters in gated 18F-FDG PET/CT imaging in mice by three commercially available software tools: PMOD, MIM, and QGS. Methods and results Healthy mice underwent ECG-gated 18F-FDG imaging using a small-animal nanoPET/CT (Mediso) under isoflurane narcosis. Reconstructed gates PET images were subsequently analyzed in three different software tools, and cardiac volume and function (end-diastolic (EDV), end-systolic volumes (ESV), stroke volume (SV), and ejection fraction (EF)) were evaluated. While cardiac volumes correlated well between PMOD, MIM, and QGS, the left ventricular parameters and cardiac function differed in agreement using Bland–Altman analysis. EDV in PMOD vs. QGS: r = 0.85; p 0.9 underlining repeatability in using PMOD, MIM, and QGS for cardiac volume and function assessment. Conclusions All three commercially available software tools are feasible in small animal cardiac volume assessment in gated 18F-FDG PET/CT imaging. However, due to software-related differences in agreement analysis for cardiac volumes and function, PMOD, MIM, and QGS cannot be used interchangeably in murine research.

Among functional imaging methods, metabolic connectivity (MC) is increasingly used for investigation of regional network changes to examine the pathophysiology of neurodegenerative diseases such as Alzheimer's disease (AD) or movement disorders. Hitherto, MC was mostly used in clinical studies, but only a few studies demonstrated the usefulness of MC in the rodent brain. The goal of the current work was to analyze and validate metabolic regional network alterations in three different mouse models of neurodegenerative diseases (β-amyloid and tau) by use of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) imaging. We compared the results of FDG-µPET MC with conventional VOI-based analysis and behavioral assessment in the Morris water maze (MWM). The impact of awake versus anesthesia conditions on MC read-outs was studied and the robustness of MC data deriving from different scanners was tested. MC proved to be an accurate and robust indicator of functional connectivity loss when sample sizes ≥12 were considered. MC readouts were robust across scanners and in awake/ anesthesia conditions. MC loss was observed throughout all brain regions in tauopathy mice, whereas β-amyloid indicated MC loss mainly in spatial learning areas and subcortical networks. This study established a methodological basis for the utilization of MC in different β-amyloid and tau mouse models. MC has the potential to serve as a read-out of pathological changes within neuronal networks in these models.

We report two cases of rare invasive tumors presenting with transvenous and intracardiac extensions. In one instance, an unusual invasive thymoma type A penetrated into the heart chamber; the other case was an extension of a myxoma into the right atrium that was associated with superior vena cava syndrome. Our interest was stimulated by the rarity of these clinicopathological observations and the unusual clinical features of diagnostic and therapeutic methods presented by these cases.

Introduction: Large datasets are required to ensure reliable non-invasive glioma assessment with radiomics-based machine learning methods. This can often only be achieved by pooling images from different centers. Moreover, trained models should perform with high accuracy when applied to data from different centers. In this study, the impact of reconstruction settings and segmentation methods on radiomic features derived from amino acid and TSPO PET images of glioma patients was examined. Additionally, the ability to model and thus reduce feature differences was investigated. Methods: [18F]FET and [18F]GE-180 PET data were acquired from 19 glioma patients. For each acquisition, 10 reconstruction settings and 9 segmentation methods were included to emulate multicentric data. Statistical robustness measures were calculated before and after ComBat harmonization. Differences between features due to setting variations were assessed using Friedman test, coefficient of variation (CV) and inter-rater reliability measures, including intraclass and Spearman’s rank correlation coefficients and Fleiss’ Kappa. Results: According to Friedman analyses, most features (>60%) showed significant differences. Yet, CV and inter-rater reliability measures indicated higher robustness. ComBat resulted in almost complete harmonization (>87%) according to Friedman test and little to no improvement according to CV and inter-rater reliability measures. [18F]GE-180 features were more sensitive to reconstruction settings than [18F]FET features. Conclusions: According to Friedman test, feature distributions could be successfully aligned using ComBat. However, depending on settings, changes in patient ranks were observed for some features and could not be eliminated by harmonization. Thus, for clinical utilization it is recommended to exclude affected features.