Chronic Rejection Pathology after Orthotopic Lung Transplantation in Mice: The Development of a Murine BOS Model and Its Drawbacks

Almost all animal models for chronic rejection (CR) after lung transplantation (LTx) fail to resemble the human situation. It was our attempt to develop a representative model of CR in mice. Orthotopic LTx was performed in allografts receiving daily immunosuppression with steroids and cyclosporine. Controls included isografts and mice only undergoing thoracotomy (SHAM). Allografts were sacrificed 2, 4, 6, 8, 10 or 12 weeks after LTx. Pulmonary function was measured repeatedly in the 12w allografts, isografts and SHAM mice. Histologically, all allografts demonstrated acute rejection (AR) around the blood vessels and airways two weeks after LTx. This decreased to 50–75% up to 10 weeks and was absent after 12 weeks. Obliterative bronchiolitis (OB) lesions were observed in 25–50% of the mice from 4–12 weeks. Isografts and lungs of SHAM mice were normal after 12 weeks. Pulmonary function measurements showed a decline in FEV0.1, TLC and compliance in the allografts postoperatively (2 weeks) with a slow recovery over time. After this initial decline, lung function of allografts increased more than in isografts and SHAM mice indicating that pulmonary function measurement is not a good tool to diagnose CR in a mouse. We conclude that a true model for CR, with clear OB lesions in about one third of the animals, but without a decline in lung function, is possible. This model is an important step forward in the development of an ideal model for CR which will open new perspectives in unraveling CR pathogenesis and exploring new treatment options

Baseline Patient Characteristics Commonly Captured Before Surgery Do Not Accurately Predict Long-Term Outcomes of Lumbar Microdiscectomy Followed by Physiotherapy

Study Design.Prospective cohort study.Objective.To develop and internally validate prognostic models based on commonly collected preoperative data for good and poor outcomes of lumbar microdiscectomy followed by physiotherapy.Summary of Background Data.Lumbar microdiscectomy followed by physiotherapy is a common intervention for lumbar radiculopathy. Postoperatively, a considerable percentage of people continues to experience pain and disability. Prognostic models for recovery are scarce.Methods.We included 298 patients with lumbar radiculopathy who underwent microdiscectomy followed by physiotherapy. Primary outcomes were recovery and secondary outcomes were pain and disability at 12 months follow-up. Potential prognostic factors were selected from sociodemographic and biomedical data commonly captured preoperatively. The association between baseline characteristics and outcomes was evaluated using multivariable logistic regression analyses.Results.At 12 months follow-up, 75.8% of the participants met the criterion for recovery. Variables in the model for good recovery included: younger age, leg pain greater than back pain, high level of disability, and a disc herniation at another level than L3-L4. The model for poor recovery included: lower educational level, prior back surgery, and disc herniation at L3-L4. Following internal validation, the explained variance (Nagelkerke R 2) and area under the curve for both models were poor (≤0.02 and ≤0.60, respectively). The discriminative ability of the models for disability and pain were also poor.Conclusion.The outcome of microdiscectomy followed by postoperative physiotherapy cannot be predicted accurately by commonly captured preoperative sociodemographic and biomedical factors. The potential value of other biomedical, personal, and external factors should be further investigated.Level of Evidence: 3

Variability in recovery following microdiscectomy and postoperative physiotherapy for lumbar radiculopathy: A latent class trajectory analysis

Objectives: The clinical course of lumbar radiculopathy following microdiscectomy and post-operative physiotherapy varies substantially. No prior studies assessed this variability by deriving outcome trajectories. The primary aims of this study were to evaluate the variability in long-term recovery after lumbar microdiscectomy followed by post-operative physiotherapy and to identify outcome trajectories. The secondary aim was to assess whether demographic, clinical characteristics and patient-reported outcome measures routinely collected at baseline could predict poor outcome trajectories. Methods: We conducted a prospective cohort study with a 24-month follow-up. We included 479 patients with clinical signs and symptoms of lumbar radiculopathy confirmed by Magnetic Resonance Imaging findings, who underwent microdiscectomy and post-operative physiotherapy. Outcomes were leg pain and back pain measured with Visual Analogue Scales, and disability measured with the Roland-Morris Disability Questionnaire. Descriptive statistics were performed to present the average and the individual clinical course. A latent class trajectory analysis was conducted to identify leg pain, back pain, and disability outcome trajectories. The best number of clusters was determined using the Bayesian Information Criterion, Akaike's information criteria, entropy, and overall interpretability. Prediction models for poor outcome trajectories were assessed using multivariable logistic regression analyses. Results: Several outcome trajectories were identified. Most patients were assigned to the ‘large improvement’ trajectory (leg pain: 79.3%; back pain: 70.2%; disability: 59.5% of patients). Smaller proportions of patients were assigned to the ‘moderate improvement’ trajectory (leg pain: 7.9%; back pain: 10.6%; disability: 20.7% of patients), the ‘minimal improvement’ trajectory (leg pain: 4.9%, back pain: 6.7%, disability: 16.3% of patients) and the ‘relapse’ trajectory (leg pain: 7.9%; back pain: 12.5%; disability: 3.5%). Approximately one-third of patients (32.6%) belonged to one or more than one poor outcome trajectory. Patients with previous treatment (prior back surgery, injection therapy, and medication use) and those who had higher baseline pain and disability scores were more likely to belong to the poor outcome trajectories in comparison to the large improvement trajectories in back pain, leg pain and disability, and the moderate improvement trajectory in disability. The explained variance (Nagelkerke R2) of the prediction models ranged from 0.06 to 0.13 and the discriminative ability (Area Under the Curve) from 0.66 to 0.73. Conclusion: The clinical course of lumbar radiculopathy varied following microdiscectomy and post-operative physiotherapy, and several outcome trajectories could be identified. Although most patients were allocated to favorable trajectories, one in three patients was assigned to one or more poor outcome trajectories following microdiscectomy and post-operative physiotherapy for lumbar radiculopathy. Routinely gathered data were unable to predict the poor outcome trajectories accurately. Prior to surgery, clinicians should discuss the high variability and the distinctive subgroups that are present in the clinical course with their patients

Study and simulation of DC micro grid topologies in Caspoc

As the impact of our actions on the climate become more and more clear and environmental awareness is rising, the quest for increasing efficiency and lower environmental impact becomes very important. Efficiency is particularly important in the field of electricity consumption, which keeps on rising as electrification of our transportation, houses, offices and more continues worldwide. These loads and sustainable sources have one thing in common: Direct Current. To successfully respond to this growing usage of direct current (DC) systems it is important to provoke an evolution in the provision of DC infrastructure. The goal of this paper is to create a methodology to calculate and evaluate the power losses in both traditional AC grids and DC microgrids. This is done through simulation models made by Caspoc, a software for modeling and simulating physical systems in analog/power electronics, electric power generation/conversion/distribution and mechatronics. The results are compared on the quantifiable indicator: energy savings. The impact of cable losses and different converters is calculated through the simulation. This methodology and simulation strategy can be the basis for the optimal grid design in other infrastructures and cases. The model will be validated with intensive tests of household equipment in a later stage of the project, this paper focuses on the model and methodology itself. DOI: 10.1109/DUE.2014.682776

A Clinical Journey Mobile Health App for Perioperative Patients:Cross-sectional Study

BACKGROUND: Mobile eHealth apps are important tools in personal health care management. The Patient Journey app was developed to inform patients with musculoskeletal disorders during their perioperative period. The app contains timely information, video exercises, and functional tasks. Although the Patient Journey app and other health apps are widely used, little research is available on how patients appreciate these apps. OBJECTIVE: The primary aim of this study was to evaluate the user-friendliness of the Patient Journey app in terms of its usability and the attitudes of users toward the app. The secondary aim was to evaluate positive and negative user experiences. METHODS: A web-based questionnaire was sent to 2114 patients scheduled for surgery for a musculoskeletal disorder. Primary outcomes were usability (measured with the System Usability Scale) and user attitudes regarding the Patient Journey app (assessed with the second part of the eHealth Impact Questionnaire). The secondary outcomes were evaluated with multiple choice questions and open-ended questions, which were analyzed via inductive thematic content analyses. RESULTS: Of the 940 patients who responded, 526 used the Patient Journey app. The usability of the app was high (System Usability Scale: median 85.0, IQR 72.5-92.5), and users had a positive attitude toward the Information and Presentation provided via the app (eHealth Impact Questionnaire: median 78.0, IQR 68.8-84.4). The app did not adequately improve the users' confidence in discussing health with others (eHealth Impact Questionnaire: median 63.9, IQR 50.0-75.0) or motivation to manage health (eHealth Impact Questionnaire: median 61.1, IQR 55.6-72.2). Three core themes emerged regarding positive and negative user experiences: (1) content and information, (2) expectations and experiences, and (3) technical performance. Users experienced timely information and instructions positively and found that the app prepared and guided them optimally through the perioperative period. Negative user experiences were overly optimistic information, scarcely presented information about pain (medication), lack of reference data, insufficient information regarding clinical course deviations and complications, and lack of interaction with clinicians. CONCLUSIONS: The Patient Journey app is a usable, informative, and presentable tool to inform patients with musculoskeletal disorders during their perioperative period. The qualitative analyses identified aspects that can further improve the user experiences of the app