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首页> 外文期刊>The New England journal of medicine >Pinching the poor? Medicaid cost sharing under the ACA
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Pinching the poor? Medicaid cost sharing under the ACA

机译:捏穷人? ACA下的医疗补助费用分摊

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Assessment of total uncertainty of analytical methods for the measurements of drugs in human hair has mainly been derived from the analytical variation. However, in hair analysis several other sources of uncertainty will contribute to the total uncertainty. Particularly, in segmental hair analysis pre-analytical variations associated with the sampling and segmentation may be significant factors in the assessment of the total uncertainty budget. The aim of this study was to develop and validate a method for the analysis of 31 common drugs in hair using ultra-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) with focus on the assessment of both the analytical and pre-analytical sampling variations. The validated method was specific, accurate (80-120%), and precise (CV≤20%) across a wide linear concentration range from 0.025-25ng/mg for most compounds. The analytical variation was estimated to be less than 15% for almost all compounds. The method was successfully applied to 25 segmented hair specimens from deceased drug addicts showing a broad pattern of poly-drug use. The pre-analytical sampling variation was estimated from the genuine duplicate measurements of two bundles of hair collected from each subject after subtraction of the analytical component. For the most frequently detected analytes, the pre-analytical variation was estimated to be 26-69%. Thus, the pre-analytical variation was 3-7 folds larger than the analytical variation (7-13%) and hence the dominant component in the total variation (29-70%). The present study demonstrated the importance of including the pre-analytical variation in the assessment of the total uncertainty budget and in the setting of the 95%-uncertainty interval (±2CVT). Excluding the pre-analytical sampling variation could significantly affect the interpretation of results from segmental hair analysis.
机译:用于测量人发中药物的分析方法的总不确定度的评估主要来自分析变异。但是,在头发分析中,其他几种不确定性来源也将导致总体不确定性。特别地,在分段毛发分析中,与采样和分段相关的分析前变化可能是评估总不确定性预算的重要因素。这项研究的目的是开发和验证一种使用超高效液相色谱-串联质谱(UHPLC-MS / MS)分析头发中31种常见药物的方法,重点是分析和前处理的评估。分析抽样变化。对于大多数化合物,在0.025-25ng / mg的宽线性浓度范围内,经过验证的方法是特异,准确的(80-120%)和精确的(CV≤20%)。几乎所有化合物的分析偏差估计都小于15%。该方法已成功应用于已故吸毒者的25个分段头发标本中,显示出广泛使用多种药物。通过减去分析成分后从每个受试者收集的两束头发的真实重复测量值来估计分析前的采样变化。对于最常检测到的分析物,分析前的变化估计为26-69%。因此,分析前的变化是分析变化(7-13%)的3-7倍,因此是总变化的主要成分(29-70%)。本研究证明了在总不确定性预算的评估和95%不确定性区间(±2CVT)的设置中包括分析前变化的重要性。排除分析前的采样变化可能会严重影响分段头发分析结果的解释。

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