3,346 research outputs found
Beyond Patient Reported Pain: Perfusion Magnetic Resonance Imaging Demonstrates Reproducible Cerebral Representation of Ongoing Post-Surgical Pain
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Discrepancies in autologous bone marrow stem cell trials and enhancement of ejection fraction (DAMASCENE): weighted regression and meta-analysis
Objective To investigate whether discrepancies in trials of use of bone marrow stem cells in patients with heart disease account for the variation in reported effect size in improvement of left ventricular function. Design Identification and counting of factual discrepancies in trial reports, and sample size weighted regression against therapeutic effect size. Meta-analysis of trials that provided sufficient information. Data sources PubMed and Embase from inception to April 2013. Eligibility for selecting studies Randomised controlled trials evaluating the effect of autologous bone marrow stem cells for heart disease on mean left ventricular ejection fraction. Results There were over 600 discrepancies in 133 reports from 49 trials. There was a significant association between the number of discrepancies and the reported increment in EF with bone marrow stem cell therapy (Spearman’s r=0.4, P=0.005). Trials with no discrepancies were a small minority (five trials) and showed a mean EF effect size of −0.4%. The 24 trials with 1-10 discrepancies showed a mean effect size of 2.1%. The 12 with 11-20 discrepancies showed a mean effect of size 3.0%. The three with 21-30 discrepancies showed a mean effect size of 5.7%. The high discrepancy group, comprising five trials with over 30 discrepancies each, showed a mean effect size of 7.7%. Conclusions Avoiding discrepancies is difficult but is important because discrepancy count is related to effect size. The mechanism is unknown but should be explored in the design of future trials because in the five trials without discrepancies the effect of bone marrow stem cell therapy on ejection fraction is zero
Glycoprotein IIb/IIIa Inhibitors Use and Outcome after Percutaneous Coronary Intervention for Non-ST Elevation Myocardial Infarction
Aims. We investigate the effect of glycoprotein IIb/IIIa (GP IIb/IIIa) inhibitors on long-term outcomes following percutaneous coronary intervention (PCI) after non-ST elevation myocardial infarction (NSTEMI). Meta-analyses indicate that these agents are associated with improved short-term outcomes. However, many trials were undertaken before the routine use of P2Y12 inhibitors. Recent studies yield conflicting results and registry data have suggested that GP IIb/IIIa inhibitors may cause more bleeding than what trials indicate. Methods and Results. This retrospective observational study involves 3047 patients receiving dual-antiplatelet therapy who underwent PCI for NSTEMI. Primary outcome was all-cause mortality. Major adverse cardiac events (MACE) were a secondary outcome. Mean follow-up was 4.6 years. Patients treated with GP IIb/IIIa inhibitors were younger with fewer comorbidities. Although the unadjusted Kaplan-Meier analysis suggested that GP IIb/IIIa inhibitor use was associated with improved outcomes, multivariate analysis (including propensity scoring) showed no benefit for either survival (P=0.136) or MACE (P=0.614). GP IIb/IIIa inhibitor use was associated with an increased risk of major bleeding (P=0.021). Conclusion. Although GP IIb/IIIa inhibitor use appeared to improve outcomes after PCI for NSTEMI, patients who received GP IIb/IIIa inhibitors tended to be at lower risk. After multivariate adjustment we observed no improvement in MACE or survival and an increased risk of major bleeding
Disrupted reward processing in Parkinson's disease and its relationship with dopamine state and neuropsychiatric syndromes: a systematic review and meta-analysis
Background: Neuropsychiatric symptoms are common in Parkinson’s disease (PD) and predict poorer outcomes. Reward processing dysfunction is a candidate mechanism for the development of psychiatric symptoms including depression and impulse control disorders (ICDs). We aimed to determine whether reward processing is impaired in PD and its relationship with neuropsychiatric syndromes and dopamine replacement therapy. // Methods: The Ovid MEDLINE/PubMed, Embase and PsycInfo databases were searched for articles published up to 5 November 2020. Studies reporting reward processing task performance by patients with PD and healthy controls were included. Summary statistics comparing reward processing between groups were converted to standardised mean difference (SMD) scores and meta-analysed using a random effects model. // Results: We identified 55 studies containing 2578 participants (1638 PD and 940 healthy controls). Studies assessing three subcomponent categories of reward processing tasks were included: option valuation (n=12), reinforcement learning (n=37) and reward response vigour (n=6). Across all studies, patients with PD on medication exhibited a small-to-medium impairment versus healthy controls (SMD=0.34; 95% CI 0.14 to 0.53), with greater impairments observed off dopaminergic medication in within-subjects designs (SMD=0.43, 95% CI 0.29 to 0.57). Within-subjects subcomponent analysis revealed impaired processing off medication on option valuation (SMD=0.57, 95% CI 0.39 to 0.75) and reward response vigour (SMD=0.36, 95% CI 0.13 to 0.59) tasks. However, the opposite applied for reinforcement learning, which relative to healthy controls was impaired on-medication (SMD=0.45, 95% CI 0.25 to 0.65) but not off-medication (SMD=0.28, 95% CI −0.03 to 0.59). ICD was the only neuropsychiatric syndrome with sufficient studies (n=13) for meta-analysis, but no significant impairment was identified compared tonon-ICD patients (SMD=−0.02, 95% CI −0.43 to 0.39). // Conclusion: Reward processing disruption in PD differs according to subcomponent and dopamine medication state, and warrants further study as a potential treatment target and mechanism underlying associated neuropsychiatric syndromes
Fracture Propagation Driven by Fluid Outflow from a Low-permeability Aquifer
Deep saline aquifers are promising geological reservoirs for CO2
sequestration if they do not leak. The absence of leakage is provided by the
caprock integrity. However, CO2 injection operations may change the
geomechanical stresses and cause fracturing of the caprock. We present a model
for the propagation of a fracture in the caprock driven by the outflow of fluid
from a low-permeability aquifer. We show that to describe the fracture
propagation, it is necessary to solve the pressure diffusion problem in the
aquifer. We solve the problem numerically for the two-dimensional domain and
show that, after a relatively short time, the solution is close to that of
one-dimensional problem, which can be solved analytically. We use the relations
derived in the hydraulic fracture literature to relate the the width of the
fracture to its length and the flux into it, which allows us to obtain an
analytical expression for the fracture length as a function of time. Using
these results we predict the propagation of a hypothetical fracture at the In
Salah CO2 injection site to be as fast as a typical hydraulic fracture. We also
show that the hydrostatic and geostatic effects cause the increase of the
driving force for the fracture propagation and, therefore, our solution serves
as an estimate from below. Numerical estimates show that if a fracture appears,
it is likely that it will become a pathway for CO2 leakage.Comment: 21 page
Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level classification in cardiac MRI
BACKGROUND: Getting the most value from expert clinicians' limited labelling time is a major challenge for artificial intelligence (AI) development in clinical imaging. We present a novel method for ground-truth labelling of cardiac magnetic resonance imaging (CMR) image data by leveraging multiple clinician experts ranking multiple images on a single ordinal axis, rather than manual labelling of one image at a time. We apply this strategy to train a deep learning (DL) model to classify the anatomical position of CMR images. This allows the automated removal of slices that do not contain the left ventricular (LV) myocardium. METHODS: Anonymised LV short-axis slices from 300 random scans (3,552 individual images) were extracted. Each image's anatomical position relative to the LV was labelled using two different strategies performed for 5 hours each: (I) 'one-image-at-a-time': each image labelled according to its position: 'too basal', 'LV', or 'too apical' individually by one of three experts; and (II) 'multiple-image-ranking': three independent experts ordered slices according to their relative position from 'most-basal' to 'most apical' in batches of eight until each image had been viewed at least 3 times. Two convolutional neural networks were trained for a three-way classification task (each model using data from one labelling strategy). The models' performance was evaluated by accuracy, F1-score, and area under the receiver operating characteristics curve (ROC AUC). RESULTS: After excluding images with artefact, 3,323 images were labelled by both strategies. The model trained using labels from the 'multiple-image-ranking strategy' performed better than the model using the 'one-image-at-a-time' labelling strategy (accuracy 86% vs. 72%, P=0.02; F1-score 0.86 vs. 0.75; ROC AUC 0.95 vs. 0.86). For expert clinicians performing this task manually the intra-observer variability was low (Cohen's κ=0.90), but the inter-observer variability was higher (Cohen's κ=0.77). CONCLUSIONS: We present proof of concept that, given the same clinician labelling effort, comparing multiple images side-by-side using a 'multiple-image-ranking' strategy achieves ground truth labels for DL more accurately than by classifying images individually. We demonstrate a potential clinical application: the automatic removal of unrequired CMR images. This leads to increased efficiency by focussing human and machine attention on images which are needed to answer clinical questions
Association between exposure to environmental tobacco smoke and biomarkers of oxidative stress among patients hospitalised with acute myocardial infarction
Objective
To determine whether exposure to environmental tobacco smoke was associated with oxidative stress among patients hospitalised for acute myocardial infarction.<p></p>
Design
An existing cohort study of 1,261 patients hospitalised for acute myocardial infarction.<p></p>
Setting
Nine acute hospitals in Scotland.<p></p>
Participants
Sixty never smokers who had been exposed to environmental tobacco smoke (admission serum cotinine ≥3.0 ng/mL) were compared with 60 never smokers who had not (admission serum cotinine ≤0.1 ng/mL).<p></p>
Intervention
None.<p></p>
Main outcome measures
Three biomarkers of oxidative stress (protein carbonyl, malondialdehyde (MDA) and oxidised low-density lipoprotein (ox-LDL)) were measured on admission blood samples and adjusted for potential confounders.<p></p>
Results
After adjusting for baseline differences in age, sex and socioeconomic status, exposure to environmental tobacco smoke was associated with serum concentrations of both protein carbonyl (beta coefficient 7.96, 95% CI 0.76, 15.17, p = 0.031) and MDA (beta coefficient 10.57, 95% CI 4.32, 16.81, p = 0.001) but not ox-LDL (beta coefficient 2.14, 95% CI −8.94, 13.21, p = 0.703).<p></p>
Conclusions
Exposure to environmental tobacco smoke was associated with increased oxidative stress. Further studies are requires to explore the role of oxidative stress in the association between environmental tobacco smoke and myocardial infarction.<p></p>
Propagation of an Earth-directed coronal mass ejection in three dimensions
Solar coronal mass ejections (CMEs) are the most significant drivers of
adverse space weather at Earth, but the physics governing their propagation
through the heliosphere is not well understood. While stereoscopic imaging of
CMEs with the Solar Terrestrial Relations Observatory (STEREO) has provided
some insight into their three-dimensional (3D) propagation, the mechanisms
governing their evolution remain unclear due to difficulties in reconstructing
their true 3D structure. Here we use a new elliptical tie-pointing technique to
reconstruct a full CME front in 3D, enabling us to quantify its deflected
trajectory from high latitudes along the ecliptic, and measure its increasing
angular width and propagation from 2-46 solar radii (approximately 0.2 AU).
Beyond 7 solar radii, we show that its motion is determined by an aerodynamic
drag in the solar wind and, using our reconstruction as input for a 3D
magnetohydrodynamic simulation, we determine an accurate arrival time at the
Lagrangian L1 point near Earth.Comment: 5 figures, 2 supplementary movie
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