Methods We performed prospective observations and retrospective interviews and surveys of family (n = 70) and professionals (n = 103) of LTC decedents with dementia in the Netherlands.
Results Instruments within the constructs QOC and QOD were highly correlated, and showed moderate to high correlation with overall assessments of QOC and QOD. Prospective and retrospective ratings using the same instruments differed
little. Concordance between family and professional scores was low. Cronbach’s selleck kinase inhibitor alpha was mostly adequate. The EOLD-CAD showed good fit with pre-assumed factor structures. The EOLD-SWC and FPCS appear most valid and reliable for measuring QOC, and the EOLD-CAD and MSSE for measuring QOD. The POS performed worst in this population.
Conclusions Our comparative study of psychometric properties of instruments allows for informed selection of QOC and QOD measures for LTC residents with dementia.”
“Background: Characterization of anti-malarial drug concentration
profiles is necessary to optimize dosing, and thereby optimize cure rates and reduce both MGCD0103 molecular weight toxicity and the emergence of resistance. Population pharmacokinetic studies determine the drug concentration time profiles in the target patient populations, including children who have limited sampling options. Currently, population pharmacokinetic studies of anti-malarial drugs are designed based on logistical, financial and ethical constraints, and prior knowledge of the drug concentration time profile. Although these factors are important, the proposed design may be unable to determine the desired pharmacokinetic profile because there was no formal consideration of the complex statistical models used to analyse the drug concentration data.
Methods: Optimal design methods incorporate prior knowledge of the pharmacokinetic profile of the drug, the statistical methods used to analyse data from population PF-00299804 solubility dmso pharmacokinetic
studies, and also the practical constraints of sampling the patient population. The methods determine the statistical efficiency of the design by evaluating the information of the candidate study design prior to the pharmacokinetic study being conducted.
Results: In a hypothetical population pharmacokinetic study of intravenous artesunate, where the number of patients and blood samples to be assayed was constrained to be 50 and 200 respectively, an evaluation of varying elementary designs using optimal design methods found that the designs with more patients and less samples per patient improved the precision of the pharmacokinetic parameters and inter-patient variability, and the overall statistical efficiency by at least 50%.
Conclusion: Optimal design methods ensure that the proposed study designs for population pharmacokinetic studies are robust and efficient.