KGK Science Inc., 255 Queens Ave, London, ON, N6A 5R8, Canada.
Zentrela Inc., Suite B21, 175 Longwood Rd S, Hamilton, ON, L8P 0A1, Canada.
Adv Ther. 2021 May;38(5):2513-2531. doi: 10.1007/s12325-021-01718-6. Epub 2021 Apr 7.
Current standards for identifying recent cannabis use are based on body fluid testing. The Cognalyzer is a novel electroencephalography (EEG) measurement device and algorithm designed to objectively characterize brainwave alterations associated with cannabis. The objective of this study was to assess the accuracy, sensitivity and specificity levels of the Cognalyzer to characterize brainwave alterations following cannabis inhalation.
Seventy-five participants, aged 19-55 years, were enrolled, and oral fluid samples were collected pre-cannabis inhalation. EEG and subjective drug effects questionnaire (DEQ) were administered pre- and post-ad libitum cannabis inhalation. Fifty participants remained in the clinic for 4 h post-inhalation. Blinded analyses of the EEG files were conducted by Zentrela Inc. using two versions (V1 and V2) of the Cognalyzer algorithm. Pre- vs. post-inhalation comparison status was characterized by the Cognalyzer and summarized for: sensitivity, specificity, accuracy, percent false positive, percent false negative and positive and negative predictive value. The null hypothesis was tested using McNemar's test. Cognalyzer results pre- and post-inhalation were combined with the oral fluid tetrahydrocannabinol (THC) concentration to evaluate potential to improve current drug testing.
The two versions of the Cognalyzer algorithm had similar diagnostic results. Diagnostic outcomes were improved when participants with missing EEG recordings or electrode placement errors were removed. The Cognalyzer accuracy was 85.5% and 83.9%, sensitivity was 87.1% and 88.7%, and specificity was 83.9% and 79.0% for algorithm V1 and V2, respectively. Combining Cognalyzer results with oral fluid concentrations reduced false-positive oral fluid test results by up to 49%.
The Cognalyzer characterized brainwave alterations associated with cannabis inhalation with high levels of accuracy in a population of participants with varied cannabis inhalation histories, relative to the comparison standard of pre- vs. post-inhalation status. The Cognalyzer allows the results to be generalized to the larger population addressing a limitation in currently accepted standards.
目前识别近期大麻使用的标准基于体液检测。Cognalyzer 是一种新型脑电图（EEG）测量设备和算法，旨在客观描述与大麻相关的脑波改变。本研究的目的是评估 Cognalyzer 识别大麻吸入后脑波改变的准确性、灵敏度和特异性水平。
招募了 75 名年龄在 19-55 岁之间的参与者，并在大麻吸入前采集了口腔液样本。在吸入大麻前和吸食大麻后，进行了脑电图（EEG）和主观药物效应问卷（DEQ）的检测。50 名参与者在吸入大麻后 4 小时留在诊所。Zentrela Inc. 对 EEG 文件进行了盲法分析，使用了 Cognalyzer 算法的两个版本（V1 和 V2）。使用 Cognalyzer 对吸入大麻前后的脑电图（EEG）文件进行了比较，并总结了灵敏度、特异性、准确性、假阳性率、假阴性率以及阳性和阴性预测值。采用 McNemar 检验对零假设进行检验。将吸入大麻前后的 Cognalyzer 结果与口腔液中四氢大麻酚（THC）浓度相结合，以评估改进当前药物检测的潜力。
两个版本的 Cognalyzer 算法具有相似的诊断结果。当去除缺失脑电图（EEG）记录或电极放置错误的参与者后，诊断结果得到了改善。算法 V1 和 V2 的 Cognalyzer 准确性分别为 85.5%和 83.9%，灵敏度分别为 87.1%和 88.7%，特异性分别为 83.9%和 79.0%。将 Cognalyzer 结果与口腔液浓度相结合，可将假阳性口腔液检测结果降低多达 49%。
Cognalyzer 能够在具有不同大麻吸入史的参与者中，以较高的准确性来描述与大麻吸入相关的脑波改变，与吸入前后的比较标准相比具有较高的准确性。Cognalyzer 使得结果能够推广到更大的人群中，解决了目前接受的标准中的一个局限性。
