Evidence map›Paper›PMID 28279885›Full record

ArticleAdvances in medical sciences2017

Brain morphometric analysis predicts decline of intelligence quotient in children with sickle cell disease: A preliminary study.

Rong Chen, Jaroslaw Krejza, Michal Arkuszewski, Robert A Zimmerman, Edward H Herskovits, Elias R Melhem

Abstract read
In one paragraph

Article in Advances in medical sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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.

Rong ChenDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA. Electronic address: rchen@umm.edu.
Jaroslaw KrejzaDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA. Electronic address: jkrejza@me.com.
Michal ArkuszewskiDepartment of Neurology, Medical University of Silesia, Katowice, Poland.
Robert A ZimmermanDepartment of Radiology, The Children's Hospital of Philadelphia, Philadelphia, USA; Department of Radiology, The Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA.
Edward H HerskovitsDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA.
Elias R MelhemDepartment of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA.

Funding

SPATIALLY ORIENTED DATABASE FOR DIGITAL BRAIN IMAGESR01AG013743 · NIA · UNIVERSITY OF PENNSYLVANIA · PI HERSKOVITS, EDWARD H · 1995 to 2010
$3.7M
Cognitive and Neuroimaging Study in Sickle Cell DiseaseR01NS046717 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI MELHEM, ELIAS R · 2004 to 2007
$2.1M
An open-source software for Bayesian neuroimaging data analysisR03EB009310 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI CHEN, RONG · 2009 to 2009
$158k
NIA NIH HHS R01 AG013743NIBIB NIH HHS R03 EB009310NINDS NIH HHS R01 NS046717
6 · The paper itself

Abstract

purposeFor children with sickle cell disease (SCD) and at low risk category of stroke, we aim to build a predictive model to differentiate those with decline of intelligence-quotient (IQ) from counterparts without decline, based on structural magnetic-resonance (MR) imaging volumetric analysis. MATERIALS AND

methodsThis preliminary prospective cohort study included 25 children with SCD, homozygous for hemoglobin S, with no history of stroke and transcranial Doppler mean velocities below 170cm/s at baseline. We administered the Kaufman Brief Intelligence Test (K-BIT) to each child at yearly intervals for 2-4 years. Each child underwent MR examination within 30 days of the baseline K-BIT evaluation date. We calculated K-BIT change rates, and used rate of change in K-BIT to classify children into two groups: a decline group and a non-decline group. We then generated predictive models to predict K-BIT decline/non-decline based on regional gray-matter (GM) volumes computed from structural MR images.

resultsWe identified six structures (the left median cingulate gyrus, the right middle occipital gyrus, the left inferior occipital gyrus, the right fusiform gyrus, the right middle temporal gyrus, the right inferior temporal gyrus) that, when assessed for volume at baseline, are jointly predictive of whether a child would suffer subsequent K-BIT decline. Based on these six regional GM volumes and the baseline K-BIT, we built a prognostic model using the K

conclusionsGM volumetric analysis predicts subsequent IQ decline for children with SCD.

Indexed as

IntelligenceAnemia, Sickle CellBrainCase-Control StudiesChildFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMalePilot ProjectsPrognosisProspective StudiesSocioeconomic FactorsBiomarkerCognitive declineMagnetic resonancePredictive modelingSickle cell disease

Identifiers

PMID28279885
PMCPMC5420463

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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.