Markku D Hämäläinen1, Andreas Zetterström1, Maria Winkvist1, Marcus Söderquist1, Elin Karlberg2, Patrik Öhagen3, Karl Andersson4,5, Fred Nyberg6. 1. Kontigo Care AB, Dragarbrunnsgatan 35, Uppsala, Sweden. 2. Innovation Akademiska, Akademiska Sjukhuset, Uppsala, Sweden. 3. Uppsala Clinical Research Center, Dag Hammarskjöldsväg 14 B, Uppsala Science Park, Uppsala, Sweden. 4. Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden. 5. Ridgeview Instruments AB, Skillsta 4, Vänge, Sweden. 6. Department of Pharmaceutical Biosciences, Uppsala University, Box 591, Uppsala, Sweden.
Abstract
AIM: We introduce a new remote real-time breathalyzer-based method for monitoring and early identification of lapse/relapse patterns for alcohol use disorder (AUD) patients using a composite measure of sobriety, the Addiction Monitoring Index (AMI). METHODS: We constructed AMI from (a) obtained test results and (b) the pattern of ignored tests using data from the first 30 patients starting in the treatment arms of two on-going clinical trials. The patients performed 2-4 scheduled breath alcohol content (BrAC)-tests per day presented as blood alcohol content (BAC) data. In total, 10,973 tests were scheduled, 7743 were performed and 3230 were ignored during 3982 patient days. RESULTS: AMI-time profiles could be used to monitor the daily trends of alcohol consumption and detect early signs of lapse and relapses. The pattern of ignored tests correlates with the onset of drinking. AMI correlated with phosphatidyl ethanol (n = 61, F-ratio = 34.6, P < 0.0001, R = -0.61). The recognition of secret drinking could further be improved using a low alcohol detection threshold (BrAC = 0.025 mg/l, BACSwe = 0.05‰ or US = 0.0053g/dl), in addition to the legal Swedish traffic limit (BrAC = 0.1 mg/l, BACSwe = 0.2‰ or US = 0.021 g/dl). Nine out of 10 patients who dropped out from the study showed early risk signs as reflected in the level and pattern in AMI before the actual dropout. CONCLUSIONS: AMI-time profiles from an eHealth system are useful for monitoring the recovery process and for early identification of lapse/relapse patterns. High-resolution monitoring of sobriety enables new measurement-based treatment methods for proactive personalized long-term relapse prevention and treatment of AUD patients. CLINICAL TRIAL REGISTRATION: The data used for construction of AMI was from two clinical trials approved by the Regional Ethics Committee of Uppsala, Sweden and performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participating subjects. The study was registered at ClinicalTrials.gov (NCT03195894).
AIM: We introduce a new remote real-time breathalyzer-based method for monitoring and early identification of lapse/relapse patterns for alcohol use disorder (AUD) patients using a composite measure of sobriety, the Addiction Monitoring Index (AMI). METHODS: We constructed AMI from (a) obtained test results and (b) the pattern of ignored tests using data from the first 30 patients starting in the treatment arms of two on-going clinical trials. The patients performed 2-4 scheduled breath alcohol content (BrAC)-tests per day presented as blood alcohol content (BAC) data. In total, 10,973 tests were scheduled, 7743 were performed and 3230 were ignored during 3982 patient days. RESULTS: AMI-time profiles could be used to monitor the daily trends of alcohol consumption and detect early signs of lapse and relapses. The pattern of ignored tests correlates with the onset of drinking. AMI correlated with phosphatidyl ethanol (n = 61, F-ratio = 34.6, P < 0.0001, R = -0.61). The recognition of secret drinking could further be improved using a low alcohol detection threshold (BrAC = 0.025 mg/l, BACSwe = 0.05‰ or US = 0.0053g/dl), in addition to the legal Swedish traffic limit (BrAC = 0.1 mg/l, BACSwe = 0.2‰ or US = 0.021 g/dl). Nine out of 10 patients who dropped out from the study showed early risk signs as reflected in the level and pattern in AMI before the actual dropout. CONCLUSIONS: AMI-time profiles from an eHealth system are useful for monitoring the recovery process and for early identification of lapse/relapse patterns. High-resolution monitoring of sobriety enables new measurement-based treatment methods for proactive personalized long-term relapse prevention and treatment of AUD patients. CLINICAL TRIAL REGISTRATION: The data used for construction of AMI was from two clinical trials approved by the Regional Ethics Committee of Uppsala, Sweden and performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participating subjects. The study was registered at ClinicalTrials.gov (NCT03195894).
Authors: Andreas Zetterström; Gunnar Dahlberg; Sara Lundqvist; Markku D Hämäläinen; Maria Winkvist; Fred Nyberg; Karl Andersson Journal: PLoS One Date: 2022-07-14 Impact factor: 3.752
Authors: Oladunni Oluwoye; Hailey Reneau; Jalene Herron; Karl C Alcover; Sterling McPherson; John Roll; Michael G McDonell Journal: J Addict Med Date: 2020 May/Jun Impact factor: 4.647
Authors: Andreas Zetterström; Markku D Hämäläinen; Maria Winkvist; Marcus Söderquist; Patrik Öhagen; Karl Andersson; Fred Nyberg Journal: Front Digit Health Date: 2021-12-07