971 resultados para 730199 Clinical health not specific to particular organs, diseases and conditions


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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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Objective: To develop a standard weight descriptor that can be used for estimation of patient size for obese patients. Patients and methods: Data were available from 3849 patients: 2839 from oncology patients (index data set) and 1010 from general medical patients (validation data set). The patients had a wide range of age (16-100 years), weight (25-165kg) and body mass index (BMI) [12-52 kg/m(2)] in both data sets. From the normal-weight patients in the oncology data set, an equation for male and female patients was developed to predict their normal weight as the sum of the lean body mass and normal fat body mass. The equations were evaluated by predicting the weight of patients in the general medical data set who had a normal BMI (30 kg/m(2)).

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A simple method for the measurement of the active leflunomide metabolite A77 1726 in human plasma by HPLC is presented. The sample workup was simple, using acetonitrile for protein precipitation. Chromatographic separation of A77 1726 and the internal standard, alpha-phenylcinnamic acid, was achieved using a C-18 column with UV detection at 305 nm. The assay displayed reproducible linearity for A77 1726 with determination coefficients (r(2)) > 0.997 over the concentration range 0.5-60.0 mug/ml. The reproducibility (%CV) for intra- and inter-day assays of spiked controls was

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Objective. To determine the population incidence and outcome of severe sepsis occurring in adult patients treated in Australian and New Zealand intensive care units (ICUs), and compare with recent retrospective estimates from the USA and UK. Design. Inception cohort study. Setting. Twenty-three closed multi-disciplinary ICUs of 21 hospitals (16 tertiary and 5 university affiliated) in Australia and New Zealand. Patients. A total of 5878 consecutive ICU admission episodes. Measurements and results. Main outcome measures were population-based incidence of severe sepsis, mortality at ICU discharge, mortality at 28 days after onset of severe sepsis, and mortality at hospital discharge. A total of 691 patients, 11.8 (95% confidence intervals 10.9-12.6) per 100 ICU admissions, were diagnosed with 752 episodes of severe sepsis. Site of infection was pulmonary in 50.3% of episodes and abdominal in 19.3% of episodes. The calculated incidence of severe sepsis in adults treated in Australian and New Zealand ICUs is 0.77 (0.76-0.79) per 1000 of population. 26.5% of patients with severe sepsis died in ICU, 32.4% died within 28 days of the diagnosis of severe sepsis and 37.5% died in hospital. Conclusion. In this prospective study, 11.8 patients per 100 ICU admissions were diagnosed with severe sepsis and the calculated annual incidence of severe sepsis in adult patients treated in Australian and New Zealand ICUs is 0.77 per 1000 of population. This figure for the population incidence falls in the lower range of recent estimates from retrospective studies in the U.S. and the U.K.

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We studied an in vitro model of continuous venous-venous haemofiltration (CVVH), into which levofloxacin 100 mg was infused, to determine levofloxacin adsorption and to determine the effect of filter material and point of dilution (pre- or post-filter) on sieving coefficient. Mean (standard deviation; S.D.) adsorption was 18.7 (5.3) mg for the polyamide filter and 40.2 (2.0) mg for the polyacrylonitrile (PAN) filter (P < 0.001). Post-dilution resulted in a minor, but statistically significant, decrease in sieving coefficient (pre-dilution 0.96 (S.D. 0.10), post-dilution 0.88 (S.D. 0.11) with the PAN filter. These data indicate that the variability in published values for levofloxacin sieving coefficient are not due to variation in point of dilution or membrane type (PAN or polyamide). Significant adsorption of levofloxacin onto PAN filters occurs. (C) 2004 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

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