BLOOD CANNABINOIDS .2. MODELS FOR THE PREDICTION OF TIME OF MARIJUANA EXPOSURE FROM PLASMA-CONCENTRATIONS OF DELTA-9-TETRAHYDROCANNABINOL (THC) AND 11-NOR-9-CARBOXY-DELTA-9-TETRAHYDROCANNABINOL (THCCOOH)
BLOOD CANNABINOIDS .2. MODELS FOR THE PREDICTION OF TIME OF MARIJUANA EXPOSURE FROM PLASMA-CONCENTRATIONS OF DELTA-9-TETRAHYDROCANNABINOL (THC) AND 11-NOR-9-CARBOXY-DELTA-9-TETRAHYDROCANNABINOL (THCCOOH)
复制标题
DOI：
10.1093/jat/16.5.283
复制
发表时间：
1992-09-01
影响因子：
2.5
通讯作者：
CONE, EJ
中科院分区：
文献类型：
--
作者：
HUESTIS, MA;HENNINGFIELD, JE;CONE, EJ
描述了两个数学模型，用于从大麻素的单个血浆样品的分析预测大麻使用的时间。这些模型来自于从急性大麻吸烟的对照临床研究中获得的大麻素数据。模型I基于血浆Δ 9-四氢大麻酚（THC）浓度，模型II基于血浆中11-去甲-9-羧基-Δ 9-四氢大麻酚（THCCOOH）与THC的比率。这两个模型用来自9项已发表和未发表的临床研究的大麻素数据进行了验证。这些数据包括从不经常和经常吸食大麻的人以及口服大麻后获得的血浆样本。大麻素血浆浓度已通过各种分析方法测定。通过比较既往药物使用的预测时间与实际暴露时间，评价模型预测的准确性。暴露时间的预测一般是准确的，但往往高估吸烟后立即的时间，往往低估以后的时间。通过确定实际使用时间是否在95%置信区间内，对模型的有效性进行了第二次评估。模型I在95%置信区间内正确预测了261个样本中的235个样本（90.0%）的暴露时间，模型II在260个样本中的232个样本（89.2%）中正确。这些预测模型可能有助于法医科学家解释大麻素血浆水平。
Two mathematical models are described for the prediction of time of marijuana use from the analysis of a single plasma sample for cannabinoids. The models were derived from cannabinoid data obtained from a controlled clinical study of acute marijuana smoking. Model I was based on plasma Δ9-tetrahydrocannabinol (THC) concentrations and Model II was based on the ratio of 11-nor-9-carboxy-Δ9-tetra-hydrocannabinol (THCCOOH) to THC in plasma. The two models were validated with cannabinoid data from nine published and unpublished clinical studies. The data included plasma samples obtained from infrequent and frequent marijuana smokers and after oral marijuana administration. Cannabinoid plasma concentrations had been determined by a variety of analytical methods. The accuracy of model prediction was evaluated by comparison of the predicted time of prior drug use to the actual time of exposure. Predictions of time of exposure were generally accurate but tended to overestimate time immediately after smoking and tended to underestimate later times. A second assessment of the validity of the models was made by determining if actual time of use was within the 95% confidence interval. Model I correctly predicted the time of exposure within the 95% confidence interval for 235 of 261 samples (90.0%), and Model II was correct in 232 of 260 samples (89.2%). These prediction models may be beneficial to forensic scientists in the interpretation of cannabinoid plasma levels.