Development and validation of a model to predict blood alcohol concentrations: Updating the NHTSA equation

A physiologically-based digital twin for alcohol consumption-predicting real-life drinking responses and long-term plasma PEth

Alcohol consumption is associated with a wide variety of preventable health complications and is a major risk factor for all-cause mortality in the age group 15-47 years. To reduce dangerous drinking behavior, eHealth applications have shown promise. A particularly interesting potential lies in the combination of eHealth apps with mathematical models. However, existing mathematical models do not consider real-life situations, such as combined intake of meals and beverages, and do not connect drinking to clinical markers, such as phosphatidylethanol (PEth). Herein, we present such a model which can simulate real-life situations and connect drinking to long-term markers. The new model can accurately describe both estimation data according to a χ2 -test (187.0 < Tχ2 = 226.4) and independent validation data (70.8 < Tχ2 = 93.5). The model can also be personalized using anthropometric data from a specific individual and can thus be used as a physiologically-based digital twin. This twin is also able to connect short-term consumption of alcohol to the long-term dynamics of PEth levels in the blood, a clinical biomarker of alcohol consumption. Here we illustrate how connecting short-term consumption to long-term markers allows for a new way to determine patient alcohol consumption from measured PEth levels. An additional use case of the twin could include the combined evaluation of patient-reported AUDIT forms and measured PEth levels. Finally, we integrated the new model into an eHealth application, which could help guide individual users or clinicians to help reduce dangerous drinking.

Feasibility and reliability of continuously monitoring alcohol use among female adolescents and young adults

INTRODUCTION AND AIMS

Transdermal alcohol sensors allow objective, continuous monitoring and have potential to expand current research on adolescent and young adult alcohol use. The purpose of this manuscript is to evaluate the feasibility and reliability of transdermal alcohol sensor use among female adolescents as compared to female young adults.

DESIGN AND METHODS

This trial included 59 female adolescents and young adults aged 14-24 years who reported drinking during the previous month. All participants were asked to wear a Giner Wrist Transdermal Alcohol Sensor (WrisTAS)-7 over a 1 month prospective study. Participants came to the research lab weekly to complete a detailed self-report of behaviours, including day of drinking events, amounts and types of alcohol use and length of drinking events. Estimates of blood alcohol concentration (eBAC) were computed from self-report data using the Matthew and Miller, NHTSA and Zhang equations. Daily transdermal alcohol concentration (TAC) peaks and calculated eBAC peak data were analysed with paired-samples t-tests and repeated measures correlations for validity comparisons.

RESULTS

All participants (100%, n = 59) completed the trial, however, two participants were removed due to greater than 50% of missing transdermal alcohol sensor data. Of the 57 participants, the data included 1,722 days of continuous alcohol monitoring. Missing data was recorded more frequently among female adolescents at about (11.78%) as compared to female young adults (8.59%; χ²  = -18.40, P < 0.001). Participant self-report of drinking occurred with greater frequency (374 events) than detected by the WrisTAS transdermal alcohol sensors (243 events). On days when self-report and sensor data indicated a drinking event, participants' eBAC was moderately correlated with TAC, after accounting for repeated measures.

DISCUSSION AND CONCLUSIONS

This study finds that transdermal alcohol sensors are moderately reliable when sensor data is paired with self-report. This objective data collection method may improve the ability to collect alcohol curves among adolescents.