13 resultados para volume-time curve

em University of Queensland eSpace - Australia


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This research work analyses techniques for implementing a cell-centred finite-volume time-domain (ccFV-TD) computational methodology for the purpose of studying microwave heating. Various state-of-the-art spatial and temporal discretisation methods employed to solve Maxwell's equations on multidimensional structured grid networks are investigated, and the dispersive and dissipative errors inherent in those techniques examined. Both staggered and unstaggered grid approaches are considered. Upwind schemes using a Riemann solver and intensity vector splitting are studied and evaluated. Staggered and unstaggered Leapfrog and Runge-Kutta time integration methods are analysed in terms of phase and amplitude error to identify which method is the most accurate and efficient for simulating microwave heating processes. The implementation and migration of typical electromagnetic boundary conditions. from staggered in space to cell-centred approaches also is deliberated. In particular, an existing perfectly matched layer absorbing boundary methodology is adapted to formulate a new cell-centred boundary implementation for the ccFV-TD solvers. Finally for microwave heating purposes, a comparison of analytical and numerical results for standard case studies in rectangular waveguides allows the accuracy of the developed methods to be assessed. © 2004 Elsevier Inc. All rights reserved.

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Background: Cyclosporin A (CsA)-treated renal transplant recipients (RTR) exhibit relative hyperhomocystinemia and vascular dysfunction. Folate supplementation lowers homocysteine and has been shown to improve vascular function in healthy subjects and patients with coronary artery disease. The aim of this study was to assess the effects of 3 months of folate supplementation (5 mg/day) on vascular function and structure in RTR. Methods: A double-blind, placebo-controlled crossover study was conducted in 10 CsA-treated RTR. Vascular structure was measured as carotid artery intima media thickness (IMT) and function was assessed as changes in brachial artery diameter during reactive hyperemia (RE) and in response to glyceryl trinitrate (GTN). Function data were analyzed as absolute and percent change from baseline and area under the diameter/time curve. Blood samples were collected before and after supplementation and analyzed for total plasma homocysteine, folate, vitamin B-12 and asymmetric dimethyl arginine (ADMA) in addition to regular measures of hemoglobin, hematocrit, mean corpuscular volume (MCV) and serum creatinine. Results: Folate supplementation significantly increased plasma folate by 687% (p < 0.005) and decreased homocysteine by 37% (p < 0.05) with no changes (p > 0.05) in vitamin B 12 or ADMA. There were no significant (p > 0.05) changes in vascular structure or function during the placebo or the folate supplementation phases; IMT; placebo pre mean +/- SD, 0.52 +/- 0.12, post 0.50 +/- 0.11; folate pre 0.55 +/- 0.17, post 0.49 +/- 10.20 mm 5% change in brachial artery diameter (RH, placebo pre 10 +/- 8, post 6 +/- 5; folate pre 9 +/- 7, post 7 +/- 5; GTN, placebo pre 18 +/- 10, post 17 +/- 9, folate pre 16 +/- 9, post-supplementation 18 +/- 8). Conclusion: Three months of folate supplementation decreases plasma homocysteine but has no effect on endothelial function or carotid artery IMT in RTR.

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Background: This study investigated whether patients suffering from post-stroke depressive disorder had a similar disturbance in central serotonergic function to that described in non-brain injured depressed patients. Methods: Twenty-three depressed patients (nine major, 14 minor) and 38 non-depressed patients were examined 4-8 weeks post-stroke with a structured interview, rating scales and MRI brain scans. Patients were administered 30 mg D-fenfluramine orally and plasma prolactin and D-fenfluramine concentrations were measured for 6 h post-dose. Results: The prolactin response was significantly blunted in major depression compared to minor depression and non-depressed patients as measured by both delta prolactin and area under the prolactin versus time curve. There was no significant relationship between prolactin response and lesion lateralization or any of the measured clinical characteristics. Limitations: The major limitation of the study is the relatively small number in each depressive group. Conclusions: Patients suffering from major depression in the post-stroke period have a blunted prolactin response to D-fenfluramine. This indicates a serotonergic abnormality consistent with that found in major depression where neurological disease is not present. (C) 2003 Elsevier B.V. All rights reserved.

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The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

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The current approach for therapeutic drug monitoring in renal transplant recipients receiving mycophenolate mofetil (MMF) is measurement of total mycophenolic acid (MPA) concentration. Because MPA is highly bound, during hypoalbuminemia the total concentration no longer reflects the free (pharmacologically active) concentration. The authors investigated what degree of hypoalbuminemia causes a significant change in protein binding and thus percentage free MPA. Forty-two renal transplant recipients were recruited for the study. Free and total concentrations of MPA (predose, and 1, 3, and 6 hours post-MMF dose samples) and plasma albumin concentrations were determined on day 5 posttransplantation. Six-hour area under the concentration-time curve (AUC(0-6)) values were calculated for free and total MPA, and percentage free MPA was determined for each patient. The authors found a significant relationship between low albumin concentrations and increased percentage free MPA (Spearman correlation = -0.54, P < 0.0001). Receiver operating characteristic (ROC) curve analysis was performed on the albumin versus percentage free MPA data. The cutoff value of albumin determined from the ROC analysis that differentiated normal from elevated percentage free MPA (defined as greater than or equal to3%) in this patient population was 31 g/L. At this cutoff value albumin was found to be a good predictor of altered free MPA percentage, with a sensitivity and specificity of 0.75 and 0.80, respectively, and an area under the ROC curve of 0.79. To rationalize MMF dosing regimens in hypoalbuminemic patients (plasma albumin less than or equal to 31 g/L), clinicians should consider monitoring the free MPA concentration.

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Alternative measures to trough concentrations [non-trough concentrations and limited area under the concentration-time curve (AUC)] have been shown to better predict tacrolimus AUC. The aim of this study was to determine if these are also better predictors of adverse outcomes in long term liver transplant recipients. The associations between tacrolimus trough concentrations (C-0), non-trough concentrations (C-1, C-2, C-4, C-6/8), and AUC(0-12) and the occurrence of hypertension, hyperkalaemia, hyperglycaemia and nephrotoxicity were assessed in 34 clinically stable liver transplant patients. The most common adverse outcome was hypertension, prevalence of 36%. Hyperkalaemia and hyperglycaemia had a prevalence of 21% and 13%, respectively. A sequential population pharmacokinetic/pharmacodynamic approach was implemented. No significant association between predicted C-0, C-1, C-2, C-4, C-6/8 or AUC(0-12) and adverse effects could be found. Tacrolimus concentrations and AUC measures were in the same range in patients with and without adverse effects. Measures reported to provide benefit, preventing graft rejection and minimizing acute adverse effects in the early post-transplant period, were not able to predict adverse effects in stable adult liver recipients whose trough concentrations were maintained in the notional target range.

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The aim of this study was to ascertain the most suitable dosing schedule for gentamicin in patients receiving hemodialysis. We developed a model to describe the concentrationtime course of gentamicin in patients receiving hemodialysis. Using the model, an optimal dosing schedule was evaluated. Various dosing regimens were compared in their ability to achieve maximum concentration (C-max, >= 8 mg/L) and area under the concentration time-curve (AUC >= 70 mg(.)h/L and <= 120 mg(.)h/L per 24 hours). The model was evaluated by comparing model predictions against real data collected retrospectively. Simulations from the model confirmed the benefits of predialysis dosing. The mean optimal dose was 230 mg administered immediately before dialysis. The model was found to have good predictive performance when simulated data were compared to data observed in real patients. In summary, a model was developed that describes gentamicin pharmacokinetics in patients receiving hemodialysis. Predialysis dosing provided a superior pharmacokinetic profile than did postdialysis dosing.

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The aim of this study was to evaluate dosing schedules of gentamicin in patients with end-stage renal disease and receiving hemodialysis. Forty-six patients were recruited who received gentamicin while on hemodialysis. Each patient provided approximately 4 blood samples at various times before and after dialysis for analysis of plasma gentamicin concentrations. A population pharmacokinetic model was constructed using NONMEM (version 5). The clearance of gentamicin during dialysis was 4.69 L/h and between dialysis was 0.453 L/h. The clearance between dialysis was best described by residual creatinine clearance (as calculated using the Cockcroft and Gault equation), which probably reflects both lean mass and residual clearance mechanisms. Simulation from the final population model showed that predialysis dosing has a higher probability of achieving target maximum concentration (C-max) concentrations (> 8 mg/L) within acceptable exposure limits (area under the concentration-time curve [AUC] values > 70 and < 120 mg.h/L per 24 hours) than postdialysis dosing.

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Background: Qualitative interpretation of myocardial contrast echocardiography (MCE) improves the accuracy of wall-motion analysis for assessment of coronary artery disease (CAD). We examined the feasibility and accuracy of quantitative MCE for diagnosis of CAD. Methods: Dipyridamole/exercise stress MCE (destruction-replenishment protocol with real-time imaging) was performed in 90 patients undergoing quantitative coronary angiography, 48 of whom had significant (> 50%) stenoses. MCE was repeated with exercise alone in 18 patients. Myocardial blood flow (A*beta) was obtained from blood volume (A) and time to refill (beta). Results: Quantification of flow reserve was feasible in 88%. The mean A*beta reserve in the anterior wall was significantly impaired for patients with left anterior descending coronary artery disease (n = 28) compared with those with no disease (1.6 +/- 1.2 vs; 4.0 +/- 2.5, P <=.001). This reflected impaired beta reserve, with no difference in the A reserve. Applying a receiver operating characteristic curve derived cutoff of 2.0 for A*beta reserve, quantitative MCE was 76% sensitive and 71% specific for the diagnosis of significant left anterior descending coronary artery stenosis. Posterior circulation results were similar, with 78% sensitivity and 59% specificity for detection of posterior CAD. Overall, quantitative MCE was similarly sensitive to qualitative approach for diagnosis of CAD (88% vs 93%), but with lower specificity (52% vs 65%, P =.07). In 18 patients restudied with pure exercise stress, the mean myocardial blood flow reserve was less than after combined stress (2.1 +/- 1.6 vs 3.7 +/- 1.9, P =.01). Conclusion: Quantitative MCE is feasible for the diagnosis of CAD with dipyridamole/exercise stress. Dipyridamole prolongs postexercise hyperemia, augmenting the degree of hyperemia at the time of imaging.

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Objectives: Left atrial (LA) volume (LAV) is a prognostically important biomarker for diastolic dysfunction, but its reproducibility on repeated testing is not well defined. LA assessment with 3-dimensional. (3D) echocardiography (3DE) has been validated against magnetic resonance imaging, and we sought to assess whether this was superior to existing measurements for sequential echocardiographic follow-up. Methods: Patients (n = 100; 81 men; age 56 +/- 14 years) presenting for LA evaluation were studied with M-mode (MM) echocardiography, 2-dimensional (2D) echocardiography, and 3DE. Test-retest variation was performed by a complete restudy by a separate sonographer within 1 hour without alteration of hemodynamics or therapy. In all, 20 patients were studied for interobserver and intraobserver variation. LAVs were calculated by using M-mode diameter and planimetered atrial area in the apical. 4-chamber view to calculate an assumed sphere, as were prolate ellipsoid, Simpson's biplane, and biplane area-length methods. All were compared with 3DE. Results: The average LAV was 72 +/- 27 mL by 3DE. There was significant underestimation of LAV by M-mode (35 +/- 20 mL, r = 0.66, P < .01). The 3DE and various 2D echocardiographic techniques were well correlated: LA planimetry (85 +/- 38 mL, r = 0.77, P < .01), prolate ellipsoid (73 +/- 36 mL, r = 0.73, P = .04), area-length (64 +/- 30 mL, r = 0.74, P < .01), and Simpson's biplane (69 +/- 31 mL, r = 0.78, P = .06). Test-retest variation for 3DE was most favorable (r = 0.98, P < .01), with the prolate ellipsoid method showing most variation. Interobserver agreement between measurements was best for 3DE (r = 0.99, P < .01), with M-mode the worst (r = 0.89, P < .01). Intraobserver results were similar to interobserver, the best correlation for 3DE (r = 0.99, P < .01), with LA planimetry the worst (r = 0.91, P < .01). Conclusions. The 2D measurements correlate closely with 3DE. Follow-up assessment in daily practice appears feasible and reliable with both 2D and 3D approaches.

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The purpose of this study was to examine the effects of different methods of measuring training volume, controlled in different ways, on selected variables that reflect acute neuromuscular responses. Eighteen resistance-trained males performed three fatiguing protocols of dynamic constant external resistance exercise, involving elbow flexors, that manipulated either time-under-tension (TUT) or volume load (VL), defined as the product of training load and repetitions. Protocol A provided a standard for TUT and VL. Protocol B involved the same VL as Protocol A but only 40% concentric TUT; Protocol C was equated to Protocol A for TUT but only involved 50% VL. Fatigue was assessed by changes in maximum voluntary isometric contraction (MVIC), interpolated doublet (ID), muscle twitch characteristics (peak twitch, time to peak twitch, 0.5 relaxation time, and mean rates of force development and twitch relaxation). All protocols produced significant changes (P

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The purpose of this study was to investigate the effects of three different weight training protocols, that varied in the way training volume was measured, on acute muscular fatigue. Ten resistance-trained males performed all three protocols which involved dynamic constant resistance exercise of the elbow flexors. Protocol A provided a standard for the time the muscle group was under tension (TUT) and volume load (VL), expressed as the product of the total number of repetitions and the load that was lifted. Protocol B involved 40% of the TUT but the same VL compared to protocol A; protocol C was equated with protocol A for TUT but only involved 50% of the VL. Fatigue was assessed by changes in maximum voluntary isometric force and integrated electromyography (iEMG) between the pre- and post-training protocols. The results of the study showed that, when equated for VL, greater TUT produced greater overall muscular fatigue ( p