Evidence map›Paper›PMID 29265385›Full record

ArticleAlcoholism, clinical and experimental research2018

Predictors of Longitudinal Trajectories of Alcohol Consumption in People with HIV.

Usama Bilal, Mary E McCaul, Heidi M Crane, W Christopher Mathews, Kenneth H Mayer, Elvin Geng, Sonia Napravnik, Karen L Cropsey, Michael J Mugavero, Michael S Saag and 3 more

Open access · greenAbstract read
In one paragraph

Article in Alcoholism, clinical and experimental research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

20 citing papers in PubMed, 25 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

13 authors at 7 institutions in 1 country.

Usama BilalDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.ORCID 0000-0002-9868-7773
Mary E McCaulDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-2009-4115
Heidi M CraneDepartment of Medicine, UW School of Medicine, University of Washington, Seattle, Washington.ORCID 0000-0002-3308-7005
W Christopher MathewsDepartment of Medicine, University of California San Diego, San Diego, California.
Kenneth H MayerSchool of Medicine, Harvard University, Boston, Massachusetts.ORCID 0000-0001-7460-733X
Elvin GengSchool of Medicine, University of California San Francisco, San Francisco, California.ORCID 0000-0002-0825-1424
Sonia NapravnikDepartment of Medicine, University of North Carolina Chapel Hill, Chapel Hill, North Carolina.
Karen L CropseyDepartment of Medicine, University of Alabama, Birmingham, Alabama.
Michael J MugaveroDepartment of Medicine, University of Alabama, Birmingham, Alabama.ORCID 0000-0001-6916-6701
Michael S SaagDepartment of Medicine, University of Alabama, Birmingham, Alabama.ORCID 0000-0002-8866-1043
Heidi HuttonDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Bryan LauDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.ORCID 0000-0002-2355-612X
Geetanjali ChanderDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.ORCID 0000-0002-2216-6330
Johns Hopkins University · USUniversity of Alabama at Birmingham · USHarvard University · USUniversity of California San Diego · USUniversity of California, San Francisco · USUniversity of North Carolina at Chapel Hill · USUniversity of Washington · US

Funding

University of Washington/Fred Hutch Center for AIDS ResearchP30AI027757 · NIAID · UNIVERSITY OF WASHINGTON · PI EDWIN ROBERTO ORELLANA · 1988 to 2026
$104.9M
Unsolicited R24 for the CFAR-Network of Integrated Clinical Sciences, CNICSR24AI067039 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Michael S. Saag · 2006 to 2026
$99.4M
Virology CoreP30AI027767 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Latesha Ellen Elopre · 1988 to 2026
$84.1M
Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Richard E. Chaisson · 2012 to 2026
$67.0M
3/4 Alcohol Research Consortium in HIV - Epidemiological Research Arm (ARCH-ERA)U01AA020793 · NIAAA · UNIVERSITY OF WASHINGTON · PI CRANE, HEIDI M., LAU, BRYAN · 2011 to 2020
$5.8M
Integration of Evidence-based Alcohol Interventions into HIV CareU01AA020802 · NIAAA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CROPSEY, KAREN L, MUGAVERO, MICHAEL J · 2011 to 2020
$4.2M
1/4 Alcohol Research Consortium in HIV-Administrative Core (ARCH-AC)U24AA020801 · NIAAA · JOHNS HOPKINS UNIVERSITY · PI CHANDER, GEETANJALI, MCCAUL, MARY E · 2011 to 2021
$3.5M
NIAAA NIH HHS U01 AA020793NIAAA NIH HHS U01 AA020802NIAAA NIH HHS U24 AA020801NIAID NIH HHS P30 AI027757NIAID NIH HHS P30 AI027767NIAID NIH HHS P30 AI050410NIAID NIH HHS P30 AI094189NIAID NIH HHS R24 AI067039
6 · The paper itself

Abstract

backgroundOur aim was to describe alcohol consumption trajectories in a cohort of people living with HIV and determine clinical and sociodemographic predictors of each trajectory.

methodsThis is a prospective cohort study of 7,906 patients in the 7 Centers for AIDS Research Network of Integrated Clinical Systems sites. Alcohol consumption was categorized as none, moderate, and alcohol misuse. Predictors included age, race/ethnicity, depressive or anxiety symptoms, illicit drug use (opioids, methamphetamines, cocaine/crack), marijuana use, hepatitis C virus (HCV) infection, HIV transmission risk factor, and HIV disease progression. We estimated sex-stratified alcohol consumption trajectories and their predictors.

resultsWe found 7 trajectories of alcohol consumption in men: stable nondrinking and increased drinking (71% and 29% of initial nondrinking); stable moderate, reduced drinking, and increased alcohol misuse (59%, 21%, and 21% of initial moderate alcohol use); and stable alcohol misuse and reduced alcohol misuse (75% and 25% of initial alcohol misuse). Categories were similar in women, except lack of an increase to alcohol misuse trajectory among women that begin with moderate use. Older men and women were more likely to have stable nondrinking, while younger men were more likely to increase to or remain in alcohol misuse. Minorities, people with depressive or anxiety symptoms, HCV-infected individuals, and people who injected drugs were more likely to reduce use. Illicit drug use was associated with a reduction in overall drinking, while marijuana use was associated with stable moderate drinking or misuse.

conclusionsLongitudinal trajectories of increasing alcohol use and stable misuse highlight the need to integrate routine screening and alcohol misuse interventions into HIV primary care.

Indexed as

AdultAge FactorsAlcohol AbstinenceAlcohol DrinkingAlcoholismAnxietyDepressionDisease ProgressionFemaleHepatitis C, ChronicHIV InfectionsHumansLogistic ModelsLongitudinal StudiesMaleMarijuana UseAlcoholic BeveragesBehaviorHIVStatistical ModelsUnited States

Identifiers

PMID29265385
PMCPMC5832592
OpenAlexW2779154912

What OpenQuestion holds

Textmetadata
LicenceTDM
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.