27 resultados para Cranial mesenteric artery

em Queensland University of Technology - ePrints Archive


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Background The accurate measurement of Cardiac output (CO) is vital in guiding the treatment of critically ill patients. Invasive or minimally invasive measurement of CO is not without inherent risks to the patient. Skilled Intensive Care Unit (ICU) nursing staff are in an ideal position to assess changes in CO following therapeutic measures. The USCOM (Ultrasonic Cardiac Output Monitor) device is a non-invasive CO monitor whose clinical utility and ease of use requires testing. Objectives To compare cardiac output measurement using a non-invasive ultrasonic device (USCOM) operated by a non-echocardiograhically trained ICU Registered Nurse (RN), with the conventional pulmonary artery catheter (PAC) using both thermodilution and Fick methods. Design Prospective observational study. Setting and participants Between April 2006 and March 2007, we evaluated 30 spontaneously breathing patients requiring PAC for assessment of heart failure and/or pulmonary hypertension at a tertiary level cardiothoracic hospital. Methods SCOM CO was compared with thermodilution measurements via PAC and CO estimated using a modified Fick equation. This catheter was inserted by a medical officer, and all USCOM measurements by a senior ICU nurse. Mean values, bias and precision, and mean percentage difference between measures were determined to compare methods. The Intra-Class Correlation statistic was also used to assess agreement. The USCOM time to measure was recorded to assess the learning curve for USCOM use performed by an ICU RN and a line of best fit demonstrated to describe the operator learning curve. Results In 24 of 30 (80%) patients studied, CO measures were obtained. In 6 of 30 (20%) patients, an adequate USCOM signal was not achieved. The mean difference (±standard deviation) between USCOM and PAC, USCOM and Fick, and Fick and PAC CO were small, −0.34 ± 0.52 L/min, −0.33 ± 0.90 L/min and −0.25 ± 0.63 L/min respectively across a range of outputs from 2.6 L/min to 7.2 L/min. The percent limits of agreement (LOA) for all measures were −34.6% to 17.8% for USCOM and PAC, −49.8% to 34.1% for USCOM and Fick and −36.4% to 23.7% for PAC and Fick. Signal acquisition time reduced on average by 0.6 min per measure to less than 10 min at the end of the study. Conclusions In 80% of our cohort, USCOM, PAC and Fick measures of CO all showed clinically acceptable agreement and the learning curve for operation of the non-invasive USCOM device by an ICU RN was found to be satisfactorily short. Further work is required in patients receiving positive pressure ventilation.

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This paper explores the potential therapeutic role of the naturally occurring sugar heparan sulfate (HS) for the augmentation of bone repair. Scaffolds comprising fibrin glue loaded with 5 lg of embryonically derived HS were assessed, firstly as a release-reservoir, and secondly as a scaffold to stimulate bone regeneration in a critical size rat cranial defect. We show HS-loaded scaffolds have a uniform distribution of HS, which was readily released with a typical burst phase, quickly followed by a prolonged delivery lasting several days. Importantly, the released HS contributed to improved wound healing over a 3-month period as determined by microcomputed tomography (lCT) scanning, histology, histomorphometry, and PCR for osteogenic markers. In all cases, only minimal healing was observed after 1 and 3 months in the absence of HS. In contrast, marked healing was observed by 3 months following HS treatment, with nearly full closure of the defect site. PCR analysis showed significant increases in the gene expression of the osteogenic markers Runx2, alkaline phosphatase, and osteopontin in the heparin sulfate group compared with controls. These results further emphasize the important role HS plays in augmenting wound healing, and its successful delivery in a hydrogel provides a novel alternative to autologous bone graft and growth factorbased therapies.

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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

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Background: Acute coronary syndromes are a major cause of mortality and morbidity. Objectives/Methods: The objective of this evaluation is to review the clinical trials of two new drugs being developed for the treatment of acute coronary syndromes. The first drug is the anti-coagulant otamixaban, and the trial compared otamixaban with unfractionated heparin and eptifibatide in acute coronary syndromes. The second drug is the anti-platelet ticagrelor, and the trial compared ticagrelor with clopidogrel in acute coronary syndromes. Results: In the SEPIA-ACS1 TIMI 42 trial, the primary efficacy endpoint occurred in 6.2% of subjects treated with unfractionated heparin and eptifibatide, and to a significantly lesser extent with otamixaban. In the PLATO trial, the primary efficacy endpoint had occurred less in the ticagrelor group (9.8%) than in the clopidogrel group (11.7%) at 12 months. Conclusions: Two new drugs for acute coronary syndromes, otamixaban and ticagrelor, have recently been shown to have benefits in subjects undergoing percutaneous interventions compared to the present standard regimens for this condition.

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Objective: Radiation safety principles dictate that imaging procedures should minimise the radiation risks involved, without compromising diagnostic performance. This study aims to define a core set of views that maximises clinical information yield for minimum radiation risk. Angiographers would supplement these views as clinically indicated. Methods: An algorithm was developed to combine published data detailing the quality of information derived for the major coronary artery segments through the use of a common set of views in angiography with data relating to the dose–area product and scatter radiation associated with these views. Results: The optimum view set for the left coronary system comprised four views: left anterior oblique (LAO) with cranial (Cr) tilt, shallow right anterior oblique (AP-RAO) with caudal (Ca) tilt, RAO with Ca tilt and AP-RAO with Cr tilt. For the right coronary system three views were identified: LAO with Cr tilt, RAO and AP-RAO with Cr tilt. An alternative left coronary view set including a left lateral achieved minimally superior efficiency (,5%), but with an ,8% higher radiation dose to the patient and 40% higher cardiologist dose. Conclusion: This algorithm identifies a core set of angiographic views that optimises the information yield and minimises radiation risk. This basic data set would be supplemented by additional clinically determined views selected by the angiographer for each case. The decision to use additional views for diagnostic angiography and interventions would be assisted by referencing a table of relative radiation doses for the views being considered.

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Scaffolds for bone tissue engineering should be designed to optimize cell migration, enhance new bone formation and give mechanical support. In the present study, we used polycaprolactone-tricalciumphosphate (PCL/TCP) scaffolds with two different fibre lay down patterns which were coated with hydroxyapatite and gelatine as an approach for optimizing bone regeneration in a critical sized calvarial defect. After 12 weeks bone regeneration was quantified using microCT analysis, biomechanical testing and histological evaluation. Notably, the experimental groups containing coated scaffolds showed lower bone formation and lower biomechanical properties within the defect compared to the uncoated scaffolds. Surprisingly, the different lay down pattern of the fibres resulted in different bone formation and biomechanical properties; namely 0/60/120° scaffolds revealed lower bone formation and biomechanical properties compared to the 0/90° scaffolds in all the experimental groups. The different architecture of the scaffold fibres may have an effect on nutrition supply as well as the attachment of the newly formed matrix to the scaffold. Therefore, future bone regeneration strategies utilising scaffolds should consider scaffold architecture as an important factor during the scaffold optimisation stages in order to move closer to a clinical application.

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I read with interest the article in Angiology that determined the role of anxiety level on radial artery spasm during transradial coronary angiography.1 As the importance of conducting more randomised controlled trials using anxiolytics to define the relation between anxiety and vasospasm was noted by the authors, I offer the following insights for investigators to consider when conducting such research. While previous research has already identified that moderate procedural sedation and opioid analgesia reduces the incidence of vasospasm,2 the identification of risk factors in the present study is hypothesis generating as to how outcomes might be even further improved. It is possible that selectively applying either even more intensive sedation and analgesia or complementary non-pharmacological stress-reducing therapies, such as music therapy or visualisation and attentive behaviour, to patients ‘at-risk’ of vasospasm (women and those with high levels of anxiety prior to the procedure) might lead to even better patient outcomes...

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There is debate as to whether percutaneous coronary intervention (PCI) with drug-eluting stents or coronary artery bypass surgery (CABG) is the best procedure for subjects with type 2 diabetes and coronary artery disease requiring revascularization. There is some evidence that following these procedures there is less further revascularization with CABG than PCI in subjects with diabetes. Two recent studies; the FREEDOM (Future Revascularization Evaluation in patients with Diabetes mellitus: Optimal Management of Multivessel Disease) trial, and a trial using a real world diabetic population from a Registry, have shown that the benefits of CABG over PCI in subjects with type 2 diabetes extends to lower rates of death and myocardial infarct, in addition to lower rates of revascularization. However, the rates of stroke may be higher with CABG than PCI with drug-eluting stents in this population. Thus, if CABG is going to be preferred to PCI in subjects with type 2 diabetes and multivessel coronary disease, consideration should be given to how to reduce the rates of stroke with CABG.