The Clinical Course of Alcohol Use Disorder Depicted by Digital Biomarkers

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Fältnamn	Indikatorer	Metadata
000		04363naa a2200481 4500
001		oai:DiVA.org:uu-510959
003		SwePub
008		230907s2021 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5109592 URI
024	7	a https://doi.org/10.3389/fdgth.2021.7320492 DOI
040		a (SwePub)uu
041		a engb eng
042		9 SwePub
072	7	a ref2 swepub-contenttype
072	7	a art2 swepub-publicationtype
100	1	a Zetterström, Andreasu Kontigo Care AB, Uppsala, Sweden4 aut
245	1 0	a The Clinical Course of Alcohol Use Disorder Depicted by Digital Biomarkers
264		c 2021-12-07
264	1	b Frontiers Media S.A.c 2021
338		a electronic2 rdacarrier
520		a Aims: This study introduces new digital biomarkers to be used as precise, objective tools to measure and describe the clinical course of patients with alcohol use disorder (AUD).Methods: An algorithm is outlined for the calculation of a new digital biomarker, the recovery and exacerbation index (REI), which describes the current trend in a patient's clinical course of AUD. A threshold applied to the REI identifies the starting point and the length of an exacerbation event (EE). The disease patterns and periodicity are described by the number, length, and distance between EEs. The algorithms were tested on data from patients from previous clinical trials (n = 51) and clinical practice (n = 1,717).Results: Our study indicates that the digital biomarker-based description of the clinical course of AUD might be superior to the traditional self-reported relapse/remission concept and conventional biomarkers due to higher data quality (alcohol measured) and time resolution. We found that EEs and the REI introduce distinct tools to identify qualitative and quantitative differences in drinking patterns (drinks per drinking day, phosphatidyl ethanol levels, weekday and holiday patterns) and effect of treatment time.Conclusions: This study indicates that the disease state-level, trend and periodicity-can be mathematically described and visualized with digital biomarkers, thereby improving knowledge about the clinical course of AUD and enabling clinical decision-making and adaptive care. The algorithms provide a basis for machine-learning-driven research that might also be applied for other disorders where daily data are available from digital health systems.
650	7	a MEDICIN OCH HÄLSOVETENSKAPx Hälsovetenskapx Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi0 (SwePub)303022 hsv//swe
650	7	a MEDICAL AND HEALTH SCIENCESx Health Sciencesx Public Health, Global Health, Social Medicine and Epidemiology0 (SwePub)303022 hsv//eng
650	7	a MEDICIN OCH HÄLSOVETENSKAPx Hälsovetenskapx Beroendelära0 (SwePub)303092 hsv//swe
650	7	a MEDICAL AND HEALTH SCIENCESx Health Sciencesx Substance Abuse0 (SwePub)303092 hsv//eng
653		a digital biomarker
653		a recovery and exacerbation index
653		a addiction monitoring index
653		a maximum time between tests
653		a identification of a relapse
700	1	a Hämäläinen, Markku D.u Kontigo Care AB, Uppsala, Sweden4 aut
700	1	a Winkvist, Mariau Kontigo Care AB, Uppsala, Sweden4 aut
700	1	a Söderquist, Marcusu Kontigo Care AB, Uppsala, Sweden4 aut
700	1	a Öhagen, Patriku Uppsala universitet,Uppsala kliniska forskningscentrum (UCR)4 aut0 (Swepub:uu)patoh117
700	1	a Andersson, Karl,d 1972-u Uppsala universitet,Cancerprecisionsmedicin,Ridgeview Instruments AB, Vange, Sweden4 aut0 (Swepub:uu)kaand227
700	1	a Nyberg, Fred,d 1945-u Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Institutionen för läkemedelskemi4 aut0 (Swepub:uu)frednybe
710	2	a Kontigo Care AB, Uppsala, Swedenb Uppsala kliniska forskningscentrum (UCR)4 org
773	0	t Frontiers in Digital Healthd : Frontiers Media S.A.g 3q 3x 2673-253X
856	4	u https://doi.org/10.3389/fdgth.2021.732049y Fulltext
856	4	u https://uu.diva-portal.org/smash/get/diva2:1794975/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
856	4	u https://www.frontiersin.org/articles/10.3389/fdgth.2021.732049/pdf
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-510959
856	4 8	u https://doi.org/10.3389/fdgth.2021.732049

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