Yale School of Medicine, New Haven, Connecticut, USA.
Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA.
Alcohol Clin Exp Res. 2022 May;46(5):783-796. doi: 10.1111/acer.14804. Epub 2022 May 14.
There is a need for novel alcohol biosensors that are accurate, able to detect alcohol concentration close in time to consumption, and feasible and acceptable for many clinical and research applications. We evaluated the field accuracy and tolerability of novel (BACTrack Skyn) and established (Alcohol Monitoring Systems SCRAM CAM) alcohol biosensors.
The sensor and diary data were collected in a larger study of a biofeedback intervention and compared observationally in the present sub-study. Participants (high-risk drinkers, 40% female; median age 21) wore both Skyn and SCRAM CAM sensors for 1-6 days and were instructed to drink as usual. Data from the first cohort of participants (N = 27; 101 person-days) were used to find threshold values of transdermal alcohol that classified each day as meeting or not meeting defined levels of drinking (heavy, above-moderate, any). These values were used to develop scoring metrics that were subsequently tested using the second cohort (N = 20; 57 person-days). Data from both biosensors were compared to mobile diary self-report to evaluate sensitivity and specificity in relation to a priori standards established in the literature.
Skyn classification rules for Cohort #1 within 3 months of device shipment showed excellent sensitivity for heavy drinking (94%) and exceeded expectations for above-moderate and any drinking (78% and 69%, respectively), while specificity met expectations (91%). However, classification worsened when Cohort #1 devices ≥3 months from shipment were tested (area under curve for receiver operator characteristic 0.87 vs. 0.79) and the derived classification threshold when applied to Cohort #2 was inadequately specific (70%). Skyn tolerability metrics were excellent and exceeded the SCRAM CAM (p ≤ 0.001).
Skyn tolerability was favorable and accuracy rules were internally derivable but did not yield useful scoring metrics going forward across device lots and months of usage.
需要开发新型酒精生物传感器，这种传感器应当具有准确度高、能及时检测到饮酒后血液中的酒精浓度、并适用于许多临床和研究应用场景的特点。本研究评估了新型（BACTrack Skyn）和传统（Alcohol Monitoring Systems SCRAM CAM）酒精生物传感器的现场准确性和耐受性。
在一项生物反馈干预的大型研究中收集了传感器和日记数据，并在本子研究中进行了观察性比较。参与者（高风险饮酒者，40%为女性；中位年龄 21 岁）佩戴 Skyn 和 SCRAM CAM 传感器 1-6 天，并按照平时的习惯饮酒。使用第一组参与者（N=27；101 人日）的数据来找到经皮酒精的阈值，将每天的饮酒量分为符合或不符合既定饮酒水平（重度、高于中度、任何程度）。这些值用于开发评分指标，然后使用第二组（N=20；57 人日）进行测试。将两种生物传感器的数据与移动日记自我报告进行比较，以评估与文献中预先确定的标准相关的敏感性和特异性。
在设备发货后 3 个月内，Skyn 分类规则对重度饮酒的敏感性很高（94%），超过了中度以上和任何程度饮酒的预期（分别为 78%和 69%），而特异性符合预期（91%）。然而，当测试发货后 3 个月以上的 Cohort #1 设备时，分类效果恶化（接受者操作特征曲线下面积为 0.87 与 0.79），应用于 Cohort #2 的分类阈值特异性不足（70%）。Skyn 的耐受性指标非常好，超过了 SCRAM CAM（p≤0.001）。
Skyn 的耐受性良好，准确性规则可内部推导，但在未来的设备批次和数月使用中，并未产生有用的评分指标。
