Evidence map›Paper›PMID 29911279›Full record

ArticleBrain imaging and behavior2019

Early adolescent brain markers of late adolescent academic functioning.

Alejandro Daniel Meruelo, Joanna Jacobus, Erick Idy, Tam Nguyen-Louie, Gregory Brown, Susan Frances Tapert

Abstract read
In one paragraph

Article in Brain imaging and behavior, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
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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

6 authors.

Alejandro Daniel MerueloDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603V, La Jolla, CA, 92093, USA. ameruelo@ucsd.edu.ORCID http://orcid.org/0000-0001-6087-1818
Joanna JacobusDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603V, La Jolla, CA, 92093, USA.
Erick IdyDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603V, La Jolla, CA, 92093, USA.
Tam Nguyen-LouieSan Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.
Gregory BrownDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603V, La Jolla, CA, 92093, USA.
Susan Frances TapertDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603V, La Jolla, CA, 92093, USA.

Funding

UC San Diego Clinical and Translational Research InstituteKL2TR001444 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DEPP, COLIN A. · 2015 to 2024
$15.4M
fMRI Cognition in Youth at Risk for Alcoholism-Diversity SupplementR01AA013419 · NIAAA · VETERANS MEDICAL RESEARCH FDN/SAN DIEGO · PI TAPERT, SUSAN F · 2002 to 2017
$7.1M
Psychiatry Research Residency Training TrackR25MH101072 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NEAL R SWERDLOW · 2013 to 2026
$2.8M
Adolescent Markers of Depression and the Impact of Alcohol UseK23AA026869 · NIAAA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MERUELO, ALEJANDRO DANIEL · 2019 to 2023
$1.0M
NCATS NIH HHS KL2 TR001444NIAAA NIH HHS AA013419-14S1NIAAA NIH HHS AA13419NIAAA NIH HHS K23 AA026869NIAAA NIH HHS R01 AA013419NIMH NIH HHS MH101072NIMH NIH HHS R25 MH101072
6 · The paper itself

Abstract

Academic performance in adolescence strongly influences adult prospects. Intelligence quotient (IQ) has historically been considered a strong predictor of academic performance. Less objectively explored have been morphometric features. We analyzed brain MRI morphometry metrics in early adolescence (age 12-14 years) as quantitative predictors of academic performance over high school using a naïve Bayesian classifier approach with n = 170 subjects. Based on the mean GPA, subjects were divided into high (GPA ≥3.54; n = 87) and low (GPA <3.54; n = 83) academic performers. Covariance analysis was performed to look at the influence of subject demographics. We examined predictive features from the 343 available regions (surface areas, cortical thickness, and subcortical volumes) and applied 4 algorithms for selection and reduction of attributes using Weka. Cortical thickness measures performed better than surface areas or subcortical volumes as predictors of academic performance. We identified 15 cortical thickness regions most predictive of academic performance, three of which have not been described in the literature predictive of academic performance. These were in the left hemisphere fusiform, bilateral insula, and left hemisphere paracentral regions. Prediction had a sensitivity of 0.65 and specificity of 0.73 with independent validation. Follow-up independent t-test analyses between high and low academic achievers on 10 of 15 regions showed between-group significance at the p < 0.05 level. High achievers demonstrated thicker cortices than low achievers. These newly identified regions may help pinpoint new targets for further study in understanding the developing adolescent brain in the classroom setting.

Indexed as

Academic SuccessAdolescentBayes TheoremBiomarkersBrainBrain MappingCerebral CortexChildCognitionFemaleForecastingHumansIntelligence TestsMagnetic Resonance ImagingMaleSensitivity and SpecificityBiomarkersAcademic performanceAdolescenceCortical thicknessMagnetic resonance imagingnaïve Bayesian classifier

Identifiers

PMID29911279
PMCPMC6298856

What OpenQuestion holds

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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.