837 resultados para population model


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Soil erosion is one of the most pressing issues facing developing countries. The need for soil erosion assessment is paramount as a successful and productive agricultural base is necessary for economic growth and stability. In Ghana, a country with an expanding population and high potential for economic growth, agriculture is an important resource; however, most of the crop production is restricted to low technology shifting cultivation agriculture. The high intensity seasonal rainfall coincides with the early growing period of many of the crops meaning that plots are very susceptible to erosion, especially on steep sided valleys in the region south of Lake Volta. This research investigated the processes of soil erosion by rainfall with the aim of producing a sediment yield model for a small semi-agricultural catchment in rural Ghana. Various types of modelling techniques were considered to discover those most applicable to the sub-tropical environment of Southern Ghana. Once an appropriate model had been developed and calibrated, the aim was to look at how to enable the scaling up of the model using sub-catchments to calculate sedimentation rates of Lake Volta. An experimental catchment was located in Ghana, south west of Lake Volta, where data on rainstorms and the associated streamflow, sediment loads and soil data (moisture content, classification and particle size distribution) was collected to calibrate the model. Additional data was obtained from the Soil Research Institute in Ghana to explore calibration of the Universal Soil Loss Equation (USLE, Wischmeier and Smith, 1978) for Ghanaian soils and environment. It was shown that the USLE could be successfully converted to provide meaningful soil loss estimates in the Ghanaian environment. However, due to experimental difficulties, the proposed theory and methodology of the sediment yield model could only be tested in principle. Future work may include validation of the model and subsequent scaling up to estimate sedimentation rates in Lake Volta.

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Aims - To build a population pharmacokinetic model that describes the apparent clearance of tacrolimus and the potential demographic, clinical and genetically controlled factors that could lead to inter-patient pharmacokinetic variability within children following liver transplantation. Methods - The present study retrospectively examined tacrolimus whole blood pre-dose concentrations (n = 628) of 43 children during their first year post-liver transplantation. Population pharmacokinetic analysis was performed using the non-linear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance and influential covariates. Results - The final model identified time post-transplantation and CYP3A5*1 allele as influential covariates on tacrolimus apparent clearance according to the following equation: TVCL = 12.9 x (Weight/13.2)0.35 x EXP (-0.0058 x TPT) x EXP (0.428 x CYP3A5) where TVCL is the typical value for apparent clearance, TPT is time post-transplantation in days and the CYP3A5 is 1 where *1 allele is present and 0 otherwise. The population estimate and inter-individual variability (%CV) of tacrolimus apparent clearance were found to be 0.977 l h−1 kg−1 (95% CI 0.958, 0.996) and 40.0%, respectively, while the residual variability between the observed and predicted concentrations was 35.4%. Conclusion Tacrolimus apparent clearance was influenced by time post-transplantation and CYP3A5 genotypes. The results of this study, once confirmed by a large scale prospective study, can be used in conjunction with therapeutic drug monitoring to recommend tacrolimus dose adjustments that take into account not only body weight but also genetic and time-related changes in tacrolimus clearance.

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Aims - To characterize the population pharmacokinetics of ranitidine in critically ill children and to determine the influence of various clinical and demographic factors on its disposition. Methods - Data were collected prospectively from 78 paediatric patients (n = 248 plasma samples) who received oral or intravenous ranitidine for prophylaxis against stress ulcers, gastrointestinal bleeding or the treatment of gastro-oesophageal reflux. Plasma samples were analysed using high-performance liquid chromatography, and the data were subjected to population pharmacokinetic analysis using nonlinear mixed-effects modelling. Results - A one-compartment model best described the plasma concentration profile, with an exponential structure for interindividual errors and a proportional structure for intra-individual error. After backward stepwise elimination, the final model showed a significant decrease in objective function value (−12.618; P < 0.001) compared with the weight-corrected base model. Final parameter estimates for the population were 32.1 l h−1 for total clearance and 285 l for volume of distribution, both allometrically modelled for a 70 kg adult. Final estimates for absorption rate constant and bioavailability were 1.31 h−1 and 27.5%, respectively. No significant relationship was found between age and weight-corrected ranitidine pharmacokinetic parameters in the final model, with the covariate for cardiac failure or surgery being shown to reduce clearance significantly by a factor of 0.46. Conclusions - Currently, ranitidine dose recommendations are based on children's weights. However, our findings suggest that a dosing scheme that takes into consideration both weight and cardiac failure/surgery would be more appropriate in order to avoid administration of higher or more frequent doses than necessary.

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WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • The cytotoxic effects of 6-mercaptopurine (6-MP) were found to be due to drug-derived intracellular metabolites (mainly 6-thioguanine nucleotides and to some extent 6-methylmercaptopurine nucleotides) rather than the drug itself. • Current empirical dosing methods for oral 6-MP result in highly variable drug and metabolite concentrations and hence variability in treatment outcome. WHAT THIS STUDY ADDS • The first population pharmacokinetic model has been developed for 6-MP active metabolites in paediatric patients with acute lymphoblastic leukaemia and the potential demographic and genetically controlled factors that could lead to interpatient pharmacokinetic variability among this population have been assessed. • The model shows a large reduction in interindividual variability of pharmacokinetic parameters when body surface area and thiopurine methyltransferase polymorphism are incorporated into the model as covariates. • The developed model offers a more rational dosing approach for 6-MP than the traditional empirical method (based on body surface area) through combining it with pharmacogenetically guided dosing based on thiopurine methyltransferase genotype. AIMS - To investigate the population pharmacokinetics of 6-mercaptopurine (6-MP) active metabolites in paediatric patients with acute lymphoblastic leukaemia (ALL) and examine the effects of various genetic polymorphisms on the disposition of these metabolites. METHODS - Data were collected prospectively from 19 paediatric patients with ALL (n = 75 samples, 150 concentrations) who received 6-MP maintenance chemotherapy (titrated to a target dose of 75 mg m−2 day−1). All patients were genotyped for polymorphisms in three enzymes involved in 6-MP metabolism. Population pharmacokinetic analysis was performed with the nonlinear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance for the active metabolites. RESULTS - The developed model revealed considerable interindividual variability (IIV) in the clearance of 6-MP active metabolites [6-thioguanine nucleotides (6-TGNs) and 6-methylmercaptopurine nucleotides (6-mMPNs)]. Body surface area explained a significant part of 6-TGNs clearance IIV when incorporated in the model (IIV reduced from 69.9 to 29.3%). The most influential covariate examined, however, was thiopurine methyltransferase (TPMT) genotype, which resulted in the greatest reduction in the model's objective function (P < 0.005) when incorporated as a covariate affecting the fractional metabolic transformation of 6-MP into 6-TGNs. The other genetic covariates tested were not statistically significant and therefore were not included in the final model. CONCLUSIONS - The developed pharmacokinetic model (if successful at external validation) would offer a more rational dosing approach for 6-MP than the traditional empirical method since it combines the current practice of using body surface area in 6-MP dosing with a pharmacogenetically guided dosing based on TPMT genotype.

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Objective: To characterize the population pharmacokinetics of canrenone following administration of potassium canrenoate (K-canrenoate) in paediatric patients. Methods: Data were collected prospectively from 37 paediatric patients (median weight 2.9 kg, age range 2 days–0.85 years) who received intravenous K-canrenoate for management of retained fluids, for example in heart failure and chronic lung disease. Dried blood spot (DBS) samples (n = 213) from these were analysed for canrenone content and the data subjected to pharmacokinetic analysis using nonlinear mixed-effects modelling. Another group of patients (n = 16) who had 71 matching plasma and DBS samples was analysed separately to compare canrenone pharmacokinetic parameters obtained using the two different matrices. Results: A one-compartment model best described the DBS data. Significant covariates were weight, postmenstrual age (PMA) and gestational age. The final population models for canrenone clearance (CL/F) and volume of distribution (V/F) in DBS were CL/F (l/h) = 12.86 ×  (WT/70.0)0.75 × e [0.066 ×  (PMA - 40]) and V/F (l) = 603.30 ×  (WT/70) × (GA/40)1.89 where weight is in kilograms. The corresponding values of CL/F and V/F in a patient with a median weight of 2.9 kg are 1.11 l/h and 20.48 l, respectively. Estimated half-life of canrenone based on DBS concentrations was similar to that based on matched plasma concentrations (19.99 and 19.37 h, respectively, in 70 kg patient). Conclusion: The range of estimated CL/F in DBS for the study population was 0.12–9.62 l/h; hence, bodyweight-based dosage adjustment of K-canrenoate appears necessary. However, a dosing scheme that takes into consideration both weight and age (PMA/gestational age) of paediatric patients seems more appropriate.

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Background To determine the pharmacokinetics (PK) of a new i.v. formulation of paracetamol (Perfalgan) in children ≤15 yr of age. Methods After obtaining written informed consent, children under 16 yr of age were recruited to this study. Blood samples were obtained at 0, 15, 30 min, 1, 2, 4, 6, and 8 h after administration of a weight-dependent dose of i.v. paracetamol. Paracetamol concentration was measured using a validated high-performance liquid chromatographic assay with ultraviolet detection method, with a lower limit of quantification (LLOQ) of 900 pg on column and an intra-day coefficient of variation of 14.3% at the LLOQ. Population PK analysis was performed by non-linear mixed-effect modelling using NONMEM. Results One hundred and fifty-nine blood samples from 33 children aged 1.8–15 yr, weight 13.7–56 kg, were analysed. Data were best described by a two-compartment model. Only body weight as a covariate significantly improved the goodness of fit of the model. The final population models for paracetamol clearance (CL), V1 (central volume of distribution), Q (inter-compartmental clearance), and V2 (peripheral volume of distribution) were: 16.51×(WT/70)0.75, 28.4×(WT/70), 11.32×(WT/70)0.75, and 13.26×(WT/70), respectively (CL, Q in litres per hour, WT in kilograms, and V1 and V2 in litres). Conclusions In children aged 1.8–15 yr, the PK parameters for i.v. paracetamol were not influenced directly by age but were by total body weight and, using allometric size scaling, significantly affected the clearances (CL, Q) and volumes of distribution (V1, V2).

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Early detection of glaucoma relies on a detailed knowledge of how the normal optic nerve (ONH) varies within the population. The purpose of this study focused on two main areas; 1. To explore the optic nerve head appearance in the normal optometric population and compare the south Asian (principally Pakistani) with the European white population, correcting for possible ocular and non-ocular influences in a multiple regression model. The main findings were: • The optic discs of the South Asian (SA) and White European (WE) populations were not statistically different in size. The SA group possessed discs with increased cupping and thinner neuro-retinal rims (NRR) compared with the WE group. The SA group also demonstrated a more vertically oval shape than the WE population. These differences were significant at the p<0.01 level. • The upper limits of inter-eye asymmetry were: ≤0.2 for cup to disc area ratio, and 3mmHg for intra-ocular pressure (IOP) for both ethnic groups and this did not increase with age. IOP asymmetry did not vary with gender, ethnicity or a family history of glaucoma and was independent of ONH asymmetry. ONH and IOP asymmetry are therefore independent risk factors when screening for glaucoma for both ethnic groups. 2. To investigate the validity of the ISNT rule: inferior> superior> nasal> temporal NRR thickness in the optometric population. The main findings were: • As disc size increased the disc become rounder and less vertically oval in shape. Vertically oval discs had thicker superior and inferior NRRs and thinner nasal and temporal NRRs compared with rounder disc shapes due to cup shape being independent of disc shape. Vertically oval discs were therefore more likely to obey the ISNT rule than larger rounder discs. • The ISNT rule has a low adherence in our sample of normal eyes (5.7%). However, by removing the nasal sector to become the IST rule, 74.5% of normal eyes obeyed. SA eyes and female gender were more likely to obey the ISNT rule due to increased disc ovality. The IST rule is independent of disc shape and therefore more suitable for assessing discs from both ethnic backgrounds. Obeying the ISNT rule or IST rule was not related to disc or cup size.

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Background: Coronary heart disease (CHD) is a public health priority in the UK. The National Service Framework (NSF) has set standards for the prevention, diagnosis and treatment of CHD, which include the use of cholesterol-lowering agents aimed at achieving targets of blood total cholesterol (TC) < 5.0 mmol/L and low density lipoprotein-cholesterol (LDL-C) < 3.0 mmol/L. In order to achieve these targets cost effectively, prescribers need to make an informed choice from the range of statins available. Aim: To estimate the average and relative cost effectiveness of atorvastatin, fluvastatin, pravastatin and simvastatin in achieving the NSF LDL-C and TC targets. Design: Model-based economic evaluation. Methods: An economic model was constructed to estimate the number of patients achieving the NSF targets for LDL-C and TC at each dose of statin, and to calculate the average drug cost and incremental drug cost per patient achieving the target levels. The population baseline LDL-C and TC, and drug efficacy and drug costs were taken from previously published data. Estimates of the distribution of patients receiving each dose of statin were derived from the UK national DIN-LINK database. Results: The estimated annual drug cost per 1000 patients treated with atorvastatin was £289 000, with simvastatin £315 000, with pravastatin £333 000 and with fluvastatin £167 000. The percentages of patients achieving target are 74.4%, 46.4%, 28.4% and 13.2% for atorvastatin, simvastatin, pravastatin and fluvastatin, respectively. Incremental drug cost per extra patient treated to LDL-C and TC targets compared with fluvastafin were £198 and £226 for atorvastatin, £443 and £567 for simvastatin and £1089 and £2298 for pravastatin, using 2002 drug costs. Conclusions: As a result of its superior efficacy, atorvastatin generates a favourable cost-effectiveness profile as measured by drug cost per patient treated to LDL-C and TC targets. For a given drug budget, more patients would achieve NSF LDL-C and TC targets with atorvastatin than with any of the other statins examined.

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OBJECTIVE: To explore the association between use of sedative drugs and frailty. DESIGN: Cross-sectional study. SETTING: First wave of The Irish Longitudinal Study on Ageing (TILDA), a nationally representative cohort of the community-dwelling population aged 50 years or older in Ireland. PARTICIPANTS: Participants were 1642 men and 1804 women aged 65 years or older. MEASUREMENTS: Regular use of sedative drugs determined according to the sedative load (SL) model, frailty phenotype status, and frailty deficit index (FI) score assessed using validated, established protocols. RESULTS: Overall, 19% of the participants took sedative drugs, most frequently hypnotics and antidepressants. Sedative drug use was at 46% for frail, 23% for prefrail, and 9% for nonfrail participants. After adjustment for covariates, SL was positively associated with being prefrail (odds ratio [OR] 1.27; 95% confidence interval [CI] 1.11-1.46) and frail (OR 1.30; 95% CI 1.02-1.64). Advancing age but not sex remained significant (P < .001). After adjustment for covariates, the association between SL and the FI was also significant at P ≤ .001 (β = 1.77; 95% CI 1.13-2.42). CONCLUSION: Higher SL was positively associated with phenotype frailty and the FI. This suggests that careful consideration must be given when prescribing sedatives to frail older adults, who are most vulnerable to adverse drug reactions and adverse health outcomes.

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The natural selection of anticoagulant resistant rats has resulted in a need for an alternative to anticoagulant rodenticides which differs in both active ingredient and in the method of dosing. Cholecalciferol toxicity to rodents using the dermal route is demonstrated using a variety of penetration enhancing formulations in two in-vitro models and finally in-vivo. A 1 ml dose of 50/50 (v/v) DMSO/ethanol containing 15% (v/v) PEG 200 and 20% (w/v) cholecalciferol was judged as 'sufficiently effective' in line with the European Union's Biocidal Products Regulation (No. 528/2012) during in-vivo studies. This dose was found to cause 100% mortality in a rat population in 64.4 h (±22 h).

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In this paper we propose an optimized algorithm, which is faster compared to previously described finite difference acceleration scheme, namely the Modified Super-Time-Stepping (Modified STS) scheme for age- structured population models with diffusion.

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Objective: To describe the effect of age and body size on enantiomer selective pharmacokinetic (PK) of intravenous ketorolac in children using a microanalytical assay. Methods: Blood samples were obtained at 0, 15 and 30 min and at 1, 2, 4, 6, 8 and 12 h after a weight-dependent dose of ketorolac. Enantiomer concentration was measured using a liquid chromatography tandem mass spectrometry method. Non-linear mixed-effect modelling was used to assess PK parameters. Key findings: Data from 11 children (1.7–15.6 years, weight 10.7–67.4 kg) were best described by a two-compartment model for R(+), S(−) and racemic ketorolac. Only weight (WT) significantly improved the goodness of fit. The final population models were CL = 1.5 × (WT/46)0.75, V1 = 8.2 × (WT/46), Q = 3.4 × (WT/46)0.75, V2 = 7.9 × (WT/46), CL = 2.98 × (WT/46), V1 = 13.2 × (WT/46), Q = 2.8 × (WT/46)0.75, V2 = 51.5 × (WT/46), and CL = 1.1 × (WT/46)0.75, V1 = 4.9 × (WT/46), Q = 1.7 × (WT/46)0.75 and V2 = 6.3 × (WT/46)for R(+), S(−) and racemic ketorolac. Conclusions: Only body weight influenced the PK parameters for R(+) and S(−) ketorolac. Using allometric size scaling significantly affected the clearances (CL, Q) and volumes of distribution (V1, V2).

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Дойчин Бояджиев, Галена Пеловска - В статията се предлага оптимизиран алгоритъм, който е по-бърз в сравнение с по- рано описаната ускорена (модифицирана STS) диференчна схема за възрастово структуриран популационен модел с дифузия. Запазвайки апроксимацията на модифицирания STS алгоритъм, изчислителното времето се намаля почти два пъти. Това прави оптимизирания метод по-предпочитан за задачи с нелинейност или с по-висока размерност.

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2000 Mathematics Subject Classification: 62P10, 62J12.

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2000 Mathematics Subject Classification: primary 60J80; secondary 60J85, 92C37.