315 resultados para Kirkpatrick


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Some volumes have title: The Cambridge Bible for schools.

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Drugs and metabolites are eliminated from the body by metabolism and excretion. The kidney makes the major contribution to excretion of unchanged drug and also to excretion of metabolites. Net renal excretion is a combination of three processes - glomerular filtration, tubular secretion and tubular reabsorption. Renal function has traditionally been determined by measuring plasma creatinine and estimating creatinine clearance. However, estimated creatinine clearance measures only glomerular filtration with a small contribution from active secretion. There is accumulating evidence of poor correlation between estimated creatinine clearance and renal drug clearance in different clinical settings, challenging the 'intact nephron hypothesis' and suggesting that renal drug handling pathways may not decline in parallel. Furthermore, it is evident that renal drug handling is altered to a clinically significant extent in a number of disease states, necessitating dosage adjustment not just based on filtration. These observations suggest that a re-evaluation of markers of renal function is required. Methods that measure all renal handling pathways would allow informed dosage individualisation using an understanding of renal excretion pathways and patient characteristics. Methodologies have been described to determine individually each of the renal elimination pathways. However, their simultaneous assessment has only recently been investigated. A cocktail of markers to measure simultaneously the individual renal handling pathways have now been developed, and evaluated in healthy volunteers. This review outlines the different renal elimination pathways and the possible markers that can be used for their measurement. Diseases and other physiological conditions causing altered renal drug elimination are presented, and the potential application of a cocktail of markers for the simultaneous measurement of drug handling is evaluated. Further investigation of the effects of disease processes on renal drug handling should include people with HIV infection, transplant recipients (renal and liver) and people with rheumatoid arthritis. Furthermore, changes in renal function in the elderly, the effect of sex on renal function, assessment of living kidney donors prior to transplantation and the investigation of renal drug interactions would also be potential applications. Once renal drug handling pathways are characterised in a patient population, the implications for accurate dosage individualisation can be assessed. The simultaneous measurement of renal function elimination pathways of drugs and metabolites has the potential to assist in understanding how renal function changes with different disease states or physiological conditions. In addition, it will further our understanding of fundamental aspects of the renal elimination of drugs.

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A retrospective review was undertaken in 744 patients who were dose-individualized with gentamicin once daily to evaluate a change in gentamicin clearance as a potential predictor of nephrotoxicity. The definition of nephrotoxicity was chosen to be a change in creatinine clearance greater than 20%. Similarly, a change in gentamicin clearance of greater than 20% was also considered a possible index of nephrotoxicity. Four criteria were developed to assess the usefulness of gentamicin clearance as a predictor of nephrotoxicity. Following the application of the inclusion/exclusion criteria, 132 patients were available for the analysis. The sensitivity, specificity, positive predictive value, and negative predictive value were assessed for each of the criteria. Receiver operating characteristic (ROC) curves were produced to determine if an optimum value in the change of gentamicin clearance could be found to maximize sensitivity and specificity. The overall incidence of nephrotoxicity based on a decrease in creatinine clearance by 20% or more was 3.8%. Women were overrepresented in the nephrotoxic group [71.4% versus 40.1% (P = 0.0025)]. Patients with nephrotoxicity had statistically longer treatment periods, increased cumulative dose, and more dosing predictions (P < 0.05 in each case). The sensitivity of the criteria ranged from 43 to 46%, and specificity ranged from 93 to 99%. The positive and negative predictive values ranged from 63 to 94% and 86 to 89%, respectively. In those patients in whom nephrotoxicity was predicted from a change in gentamicin clearance, this change occurred on average 3 days before the change in creatinine clearance (P < 0.05). A change in gentamicin clearance to predict nephrotoxicity may be a useful addition to current monitoring methods, although it is not the complete answer.

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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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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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Aims [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. Methods Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (>=20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. Results A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V-1), 19.5 l 70 kg(-1); volume of peripheral compartment (V-2) 11.2 l 70 kg(-1). Conclusions Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.

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Background: It is essential for health-care professionals to calculate drug doses accurately. Previous studies have demonstrated that many hospital doctors were unable to accurately convert dilutions (e.g. 1:1000) or percentages (e.g. percentage w/v) of drug concentrations into mass concentrations (e.g. mg/mL). Aims: The aims of the present study were to evaluate the ability of health-care professionals to perform drug dose calculations accurately and to determine their preferred concentration convention when calculating drug doses. Methods: A selection of nurses, medical students, house surgeons, registrars and pharmacists undertook a written survey to assess their ability to perform five drug dose calculations. Participants were also asked which concentration convention they preferred when calculating drug doses. The surveys were marked then analysed for health-care professionals as a whole and then by subgroup analysis to assess the performance of each health-care-professional group. Results: Overall, less than 14% of the surveyed health-care professionals could answer all five questions correctly. Subgroup analysis revealed that health-care pro-fessionals' ability to calculate drug doses were ranked in the following order: registrars approximate to pharmacists > house surgeons > medical students >> nurses. Ninety per cent of health-care professionals preferred to calculate drug doses using the mass concentration convention. Conclusions: Overall, drug dose calculations were performed poorly. Mass concentration was clearly indicated as the preferred convention for calculating drug doses.

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