55 research outputs found
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Gas Flow Shaping via Novel Modular Nozzle System (MoNoS) Augments kINPen-Mediated Toxicity and Immunogenicity in Tumor Organoids
Medical gas plasma is an experimental technology for anticancer therapy. Here, partial gas ionization yielded reactive oxygen and nitrogen species, placing the technique at the heart of applied redox biomedicine. Especially with the gas plasma jet kINPen, anti-tumor efficacy was demonstrated. This study aimed to examine the potential of using passive flow shaping to enhance the medical benefits of atmospheric plasma jets (APPJ). We used an in-house developed, proprietary Modular Nozzle System (MoNoS; patent-pending) to modify the flow properties of a kINPen. MoNoS increased the nominal plasma jet-derived reactive species deposition area and stabilized the air-plasma ratio within the active plasma zone while shielding it from external flow disturbances or gas impurities. At modest flow rates, dynamic pressure reduction (DPR) adapters did not augment reactive species deposition in liquids or tumor cell killing. However, MoNoS operated at kINPen standard argon fluxes significantly improved cancer organoid growth reduction and increased tumor immunogenicity, as seen by elevated calreticulin and heat-shock protein expression, along with a significantly spurred cytokine secretion profile. Moreover, the safe application of MoNoS gas plasma jet adapters was confirmed by their similar-to-superior safety profiles assessed in the hen’s egg chorioallantoic membrane (HET-CAM) coagulation and scar formation irritation assay
The Brain Monitoring with Information Technology (BrainIT) collaborative network:: Past, Present and Future Direction
The BrainIT group works collaboratively on developing standards for collection and analyses of data from brain injured patients and to facilitate a more efficient infrastructure for assessing new health care technology with the primary objective of improving patient care. European Community funding supported meetings over a year to discuss and define a core dataset to be collected from patients with traumatic brain injury using IT based methods. In this paper, we give an overview of the aims and future directions of the group as well as present the results of an EC funded study with the aim of testing the feasibility of collecting this core dataset across a number of European sites and discuss the future direction of this research network. Over a three year period, data collection client and web-server based tools were developed and core data (grouped into 9 categories) were collected from 200 head-injured patients by local nursing staff in 22 European neuro-intensive care centres. Data were uploaded through the BrainIT web site and random samples of received data were selected automatically by computer for validation by data validation (DV) staff against primary sources held in each local centre. Validated data were compared with originally transmitted data and percentage error rates calculated by data category. Feasibility was assessed in terms of the proportion of missing data, accuracy of data collected andlimitations reported by users of the IT methods. Thirteen percent of data files required cleaning. Thirty “one-off” demographic and clinical data elements had significant amounts of missing data (> 15%). Validation staff conducted 19,461 comparisons between uploaded database data with local data sources and error rates were commonly less than or equal to 6%, the exception being the surgery data class where an unacceptably high error rate of 34% was found. Nearly 10,000therapies were successfully recorded with start-times but approximately a third had inaccurate or missing end times which limits the analysis of duration of therapy. Over 40,000 events and procedures were recorded but events with long durations (such as transfers) were more likely to have “end-times” missed. The BrainIT core dataset is a rich dataset for hypothesis generation and post-hoc analyses provided studies avoid known limitations in the dataset. Limitations in the current IT based data collection tools have been identified and have been addressed. In order for multi-centre data collection projects to be viable the resource intensive validation procedures will require a more automated process and this may include direct electronic access to hospital based clinical data sources for both validation purposes and for minimising the duplication of data entry. This type of infrastructure may foster and facilitate the remote monitoring of patient management and protocol adherence in future trials of patient management and monitoring. 
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Cognitive rehabilitation, self-management, psychotherapeutic and caregiver support interventions in progressive neurodegenerative conditions: a scoping review
BACKGROUND: Despite their potentially significant impact, cognitive disability may be overlooked in a number of progressive neurodegenerative conditions, as other difficulties dominate the clinical picture.
OBJECTIVE: We examined the extent, nature and range of the research evidence relating to cognitive rehabilitation, self-management, psychotherapeutic and caregiver support interventions in Parkinsonian disorders, multiple sclerosis (MS), frontotemporal dementias (FTD), motor neuron disease and Huntington’s disease.
METHODS: Scoping review based on searches of MEDLINE and CINAHL up to 15 March 2016.
RESULTS: We included 140 eligible papers. Over half of the studies, and almost all the randomised controlled trials, related to MS, while a number of single case studies described interventions for people with FTD. CR interventions addressed functional ability, communication and interaction, behaviour or memory. The majority of psychotherapy interventions involved cognitive behavioural therapy for depression or anxiety. Self-management interventions were mainly available for people with MS. There were few reports of interventions specific to caregivers. Numerous methodological challenges were identified.
CONCLUSIONS: The limited range of studies for all conditions except MS suggests a need firstly to synthesise systematically the available evidence across conditions and secondly to develop well-designed studies to provide evidence about the effectiveness of CR and other psychological interventions
GestaltMatcher Database - A global reference for facial phenotypic variability in rare human diseases
The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.</p
Quality indicators for patients with traumatic brain injury in European intensive care units
Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur
Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe
Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme
Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury
Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations
Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.
INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches
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Use and impact of high intensity treatments in patients with traumatic brain injury across Europe: a CENTER-TBI analysis
Abstract: Purpose: To study variation in, and clinical impact of high Therapy Intensity Level (TIL) treatments for elevated intracranial pressure (ICP) in patients with traumatic brain injury (TBI) across European Intensive Care Units (ICUs). Methods: We studied high TIL treatments (metabolic suppression, hypothermia (< 35 °C), intensive hyperventilation (PaCO2 < 4 kPa), and secondary decompressive craniectomy) in patients receiving ICP monitoring in the ICU stratum of the CENTER-TBI study. A random effect logistic regression model was used to determine between-centre variation in their use. A propensity score-matched model was used to study the impact on outcome (6-months Glasgow Outcome Score-extended (GOSE)), whilst adjusting for case-mix severity, signs of brain herniation on imaging, and ICP. Results: 313 of 758 patients from 52 European centres (41%) received at least one high TIL treatment with significant variation between centres (median odds ratio = 2.26). Patients often transiently received high TIL therapies without escalation from lower tier treatments. 38% of patients with high TIL treatment had favourable outcomes (GOSE ≥ 5). The use of high TIL treatment was not significantly associated with worse outcome (285 matched pairs, OR 1.4, 95% CI [1.0–2.0]). However, a sensitivity analysis excluding high TIL treatments at day 1 or use of metabolic suppression at any day did reveal a statistically significant association with worse outcome. Conclusion: Substantial between-centre variation in use of high TIL treatments for TBI was found and treatment escalation to higher TIL treatments were often not preceded by more conventional lower TIL treatments. The significant association between high TIL treatments after day 1 and worse outcomes may reflect aggressive use or unmeasured confounders or inappropriate escalation strategies. Take home message: Substantial variation was found in the use of highly intensive ICP-lowering treatments across European ICUs and a stepwise escalation strategy from lower to higher intensity level therapy is often lacking. Further research is necessary to study the impact of high therapy intensity treatments. Trial registration: The core study was registered with ClinicalTrials.gov, number NCT02210221, registered 08/06/2014, https://clinicaltrials.gov/ct2/show/NCT02210221?id=NCT02210221&draw=1&rank=1 and with Resource Identification Portal (RRID: SCR_015582)
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Quality indicators for patients with traumatic brain injury in European intensive care units: a CENTER-TBI study
Abstract: Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measurement and improvement. Methods: Our analysis was based on 2006 adult patients admitted to 54 ICUs between 2014 and 2018, enrolled in the CENTER-TBI study. Indicator scores were calculated as percentage adherence for structure and process indicators and as event rates or median scores for outcome indicators. Feasibility was quantified by the completeness of the variables. Discriminability was determined by the between-centre variation, estimated with a random effect regression model adjusted for case-mix severity and quantified by the median odds ratio (MOR). Statistical uncertainty of outcome indicators was determined by the median number of events per centre, using a cut-off of 10. Results: A total of 26/42 indicators could be calculated from the CENTER-TBI database. Most quality indicators proved feasible to obtain with more than 70% completeness. Sub-optimal adherence was found for most quality indicators, ranging from 26 to 93% and 20 to 99% for structure and process indicators. Significant (p < 0.001) between-centre variation was found in seven process and five outcome indicators with MORs ranging from 1.51 to 4.14. Statistical uncertainty of outcome indicators was generally high; five out of seven had less than 10 events per centre. Conclusions: Overall, nine structures, five processes, but none of the outcome indicators showed potential for quality improvement purposes for TBI patients in the ICU. Future research should focus on implementation efforts and continuous reevaluation of quality indicators. Trial registration: The core study was registered with ClinicalTrials.gov, number NCT02210221, registered on August 06, 2014, with Resource Identification Portal (RRID: SCR_015582)
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