Evidence map›Paper›PMID 27936363›Full record

ArticleJournal of studies on alcohol and drugs2017

Predictors of Patterns of Alcohol-Related Blackouts Over Time in Youth From the Collaborative Study of the Genetics of Alcoholism: The Roles of Genetics and Cannabis.

Marc A Schuckit, Tom L Smith, Alexandra Shafir, Peyton Clausen, George Danko, Priscila Dib Gonçalves, Robert M Anthenelli, Grace Chan, Samuel Kuperman, Michie Hesselbrock and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in Journal of studies on alcohol and drugs, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 21 citations in OpenAlex.

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  12. Intentions and motives to experience alcohol-induced blackout among young adults in college.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 2 countries.

Marc A SchuckitDepartment of Psychiatry, University of California, San Diego, La Jolla, California.
Tom L SmithDepartment of Psychiatry, University of California, San Diego, La Jolla, California.
Alexandra ShafirDepartment of Psychiatry, University of California, San Diego, La Jolla, California.
Peyton ClausenDepartment of Psychiatry, University of California, San Diego, La Jolla, California.
George DankoDepartment of Psychiatry, University of California, San Diego, La Jolla, California.
Priscila Dib GonçalvesDepartment of Psychiatry, University of California, San Diego, La Jolla, California.
Robert M AnthenelliDepartment of Psychiatry, University of California, San Diego, La Jolla, California.
Grace ChanUniversity of Connecticut Health Center, Farmington, Connecticut.
Samuel KupermanUniversity of Iowa Hospitals, Iowa City, Iowa.
Michie HesselbrockUniversity of Connecticut Health Center, Farmington, Connecticut.
Victor HesselbrockUniversity of Connecticut Health Center, Farmington, Connecticut.
John KramerUniversity of Iowa Hospitals, Iowa City, Iowa.
Kathleen K BucholzWashington University at St. Louis, St. Louis, Missouri.
University of California, San Diego · USUConn Health · USUniversity of Iowa Hospitals and Clinics · USWashington University in St. Louis · US

Funding

Subject CollectionU10AA008401 · NIAAA · SUNY DOWNSTATE MEDICAL CENTER · PI JESSICA E SALVATORE · 1989 to 2026
$162.7M
PREVENTION APPROACH TO COLLEGE HEAVY DRINKING BASED ON A LOW RESPONSE TO ALCOHOLR01AA021162 · NIAAA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SCHUCKIT, MARC A · 2013 to 2014
$945k
NIAAA NIH HHS R01 AA021162NIAAA NIH HHS U10 AA008401
6 · The paper itself

Abstract

objectiveAlcohol-related blackouts (ARBs) are anterograde amnesias related to heavy alcohol intake seen in about 50% of drinkers. Although a major determinant of ARBs relates to blood alcohol concentrations, additional contributions come from genetic vulnerabilities and possible impacts of cannabis use disorders (CUDs). We evaluated relationships of genetics and cannabis use to latent class trajectories of ARBs in 829 subjects from the Collaborative Study of the Genetics of Alcoholism (COGA).

methodThe number of ARBs experienced every 2 years from subjects with average ages of 18 to 25 were entered into a latent class growth analysis in Mplus, and resulting class membership was evaluated in light of baseline characteristics, including CUDs. Correlations of number of ARBs across assessments were also compared for sibling pairs versus unrelated subjects.

resultsLatent class growth analysis identified ARB-based Classes 1 (consistent low = 42.5%), 2 (moderate low = 28.3%), 3 (moderate high = 22.9%), and 4 (consistent high = 6.3%). A multinomial logistic regression analysis within latent class growth analysis revealed that baseline CUDs related most closely to Classes 3 and 4. The number of ARBs across time correlated .23 for sibling pairs and -.10 for unrelated subjects.

conclusionsBaseline CUDs related to the most severe latent ARB course over time, even when considered along with other trajectory predictors, including baseline alcohol use disorders and maximum number of drinks. Data indicated significant roles for genetic factors for alcohol use disorder patterns over time. Future research is needed to improve understanding of how cannabis adds to the ARB risk and to find genes that contribute to risks for ARBs among drinkers.

Indexed as

AdolescentAdultAlcohol DrinkingAmnesiaFemaleHumansMaleMarijuana SmokingRisk FactorsSiblingsSubstance-Related DisordersYoung Adult

Identifiers

PMID27936363
PMCPMC5148748
OpenAlexW2565631158

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.