Evidence map›Paper›PMID 30592535›Full record

ArticleAlcoholism, clinical and experimental research2019

Longitudinal Drinking Patterns and Their Clinical Correlates in Million Veteran Program Participants.

Rachel Vickers Smith, Henry R Kranzler, Amy C Justice, Janet P Tate, VA Million Veteran Program

Abstract read
In one paragraph

Article in Alcoholism, clinical and experimental research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Covid-19 and alcohol associated liver disease.Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver · 2022
    Review
  5. Article
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

5 authors at 3 institutions in 1 country.

Rachel Vickers SmithUniversity of Louisville School of Nursing , Louisville, Kentucky.ORCID 0000-0002-7224-8916
Henry R KranzlerMental Illness Research, Education and Clinical Center , Crescenz VAMC, Philadelphia, Pennsylvania.
Amy C JusticeVA Connecticut Healthcare System , West Haven, Connecticut.ORCID 0000-0003-0139-5502
Janet P TateVA Connecticut Healthcare System , West Haven, Connecticut.
VA Million Veteran Program
Yale University · USPhiladelphia VA Medical Center · USUniversity of Louisville · US

Funding

Genetic Vulnerability for Sustained Multi-Substance Use in MVPI01BX003341 · VA · VA CONNECTICUT HEALTHCARE SYSTEM · PI FEDERMAN, DANIEL, JUSTICE, AMY CAROLINE · 2017 to 2017
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BLRD VA I01 BX003341Department of Veterans Affairs or the U.S. GovernmentOffice of Research and Development VHA-ORD i01 BX003341Veterans Health Administration
6 · The paper itself

Abstract

backgroundA variety of measures have been developed to screen for hazardous or harmful drinking. The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) is one of the screening measures recommended by the U.S. Preventive Services Task Force. Annual administration of the AUDIT-C to all primary care patients is required by the U.S. Veterans Affairs Health System. The availability of data from the repeated administration of this instrument over time in a large patient population provides an opportunity to evaluate the utility of the AUDIT-C for identifying distinct drinking groups.

methodsUsing data from the Million Veteran Program cohort, we modeled group-based drinking trajectories using 2,833,189 AUDIT-C scores from 495,178 Veterans across an average 6-year time period. We also calculated patients' age-adjusted mean AUDIT-C scores to compare to the drinking trajectories. Finally, we extracted data on selected clinical diagnoses from the electronic health record and assessed their associations with the drinking trajectories.

resultsOf the trajectory models, the 4-group model demonstrated the best fit to the data. AUDIT-C trajectories were highly correlated with the age-adjusted mean AUDIT-C scores (rs = 0.94). Those with an alcohol use disorder diagnosis had 10 times the odds of being in the highest trajectory group (consistently hazardous/harmful) compared to the lowest drinking trajectory group (infrequent). Those with hepatitis C, posttraumatic stress disorder, liver cirrhosis, and delirium had 10, 7, 21, and 34%, respectively, higher odds of being classified in the highest drinking trajectory group versus the lowest drinking trajectory group.

conclusionsTrajectories and age-adjusted mean scores are potentially useful approaches to optimize the information provided by the AUDIT-C. In contrast to trajectories, age-adjusted mean AUDIT-C scores also have clinical relevance for real-time identification of individuals for whom an intervention may be warranted.

Indexed as

Alcohol DrinkingFemaleHumansMaleMiddle AgedModels, PsychologicalPsychiatric Status Rating ScalesUnited StatesVeteransAlcohol Use DisorderElectronic Health Record DataGroup-Based Trajectory ModelingHazardous Drinking

Identifiers

PMID30592535
PMCPMC6691890
OpenAlexW2907159368

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.