Evidence map›Paper›PMID 33282611›Full record

ReviewAlcohol research : current reviews2020

Brain Structure and Function in Recovery.

Sara Jo Nixon, Ben Lewis

Abstract readReview
In one paragraph

Review in Alcohol research : current reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. From the Editors.Alcohol research : current reviews · 2021
    Article
  8. 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

2 authors.

Sara Jo NixonDepartment of Psychiatry, University of Florida, Gainesville, Florida.
Ben LewisDepartment of Psychiatry, University of Florida, Gainesville, Florida.

Funding

ABCD-USA Consortium: Research ProjectU01DA041106 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mary M Heitzeg, Chandra Sekhar Sripada · 2015 to 2026
$24.9M
Enhancing Recovery Outcomes in Alcohol Use Disorder: Cognitive Training as an Adjunct to TreatmentK01AA026893 · NIAAA · UNIVERSITY OF FLORIDA · PI LEWIS, BEN · 2018 to 2022
$729k
Sex Differences, Cognitive Training & Emotion Processing: A pilot study of Treatment-Seeking Men and Women with Alcohol Use DisorderR03AA025430 · NIAAA · UNIVERSITY OF FLORIDA · PI NIXON, SARA JO · 2017 to 2018
$153k
NIAAA NIH HHS K01 AA026893NIAAA NIH HHS R03 AA025430NIDA NIH HHS U01 DA041106
6 · The paper itself

Abstract

Alcohol use disorder (AUD) commonly is associated with compromise in neurobiological and/or neurobehavioral processes. The severity of this compromise varies across individuals and outcomes, as does the degree to which recovery of function is achieved. This narrative review first summarizes neurobehavioral, neurophysiological, structural, and neurochemical aberrations/deficits that are frequently observed in people with AUD after detoxification. Subsequent sections review improvements across these domains during recovery, taking into account modulators of recovery to the extent permitted. Where appropriate, the discussion includes work integrating outcomes across domains, leveraging the strengths of diverse experimental methods. Interventions to ameliorate neurobiological or neurobehavioral deficits do not constitute a primary objective of this review. However, their consideration is a logical inclusion. Therefore, a limited introduction to existing methods is also presented.

Indexed as

AlcoholismBrainHumansalcoholalcohol use disorderbrain structureneural networksneurobehavioral deficitsneurochemistryneurophysiologyrecovery

Identifiers

PMID33282611
PMCPMC7703868

What OpenQuestion holds

Textmetadata
LicenceCC0
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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.