Evidence map›Paper›PMID 38873169›Full record

ArticleAdvances in Alzheimer's disease2023

A Novel Computerized Cognitive Test for the Detection of Mild Cognitive Impairment and Its Association with Neurodegeneration in Alzheimer's Disease Prone Brain Regions.

Rosie E Curiel Cid, D Diane Zheng, Marcela Kitaigorodsky, Malek Adjouadi, Elizabeth A Crocco, Mike Georgiou, Christian Gonzalez-Jimenez, Alexandra Ortega, Mohammed Goryawala, Natalya Nagornaya and 4 more

Abstract read
In one paragraph

Article in Advances in Alzheimer's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Rosie E Curiel CidCenter for Cognitive Neuroscience and Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.
D Diane ZhengCenter for Cognitive Neuroscience and Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Marcela KitaigorodskyCenter for Cognitive Neuroscience and Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Malek AdjouadiCenter for Advanced Technology and Education, Department of Electrical and Computer Engineering, College of Engineering and Computing, Florida International University, Miami, Florida, USA.
Elizabeth A CroccoCenter for Cognitive Neuroscience and Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Mike GeorgiouDepartment of Radiology and Nuclear Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Christian Gonzalez-JimenezCenter for Cognitive Neuroscience and Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Alexandra OrtegaCenter for Cognitive Neuroscience and Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Mohammed GoryawalaDepartment of Radiology and Nuclear Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Natalya NagornayaDepartment of Radiology and Nuclear Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Pradip PattanyDepartment of Radiology and Nuclear Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Efrosyni SfakianakiDepartment of Radiology and Nuclear Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA.
Ubbo VisserDepartment of Computer Science, University of Miami, Miami, Florida, USA.
David A LoewensteinCenter for Cognitive Neuroscience and Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.

Funding

Precision-based Assessment for the Detection of Mild Cognitive Impairment in Older AdultsR01AG055638 · NIA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CURIEL CID, ROSIE E · 2018 to 2022
$2.9M
Novel Detection of Early Cognitive and Functional Impairment in the ElderlyR01AG047649 · NIA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI LOEWENSTEIN, DAVID · 2015 to 2019
$2.7M
NIA NIH HHS L30 AG060558NIA NIH HHS R01 AG047649NIA NIH HHS R01 AG055638
6 · The paper itself

Abstract

During the prodromal stage of Alzheimer's disease (AD), neurodegenerative changes can be identified by measuring volumetric loss in AD-prone brain regions on MRI. Cognitive assessments that are sensitive enough to measure the early brain-behavior manifestations of AD and that correlate with biomarkers of neurodegeneration are needed to identify and monitor individuals at risk for dementia. Weak sensitivity to early cognitive change has been a major limitation of traditional cognitive assessments. In this study, we focused on expanding our previous work by determining whether a digitized cognitive stress test, the Loewenstein-Acevedo Scales for Semantic Interference and Learning, Brief Computerized Version (LASSI-BC) could differentiate between Cognitively Unimpaired (CU) and amnestic Mild Cognitive Impairment (aMCI) groups. A second focus was to correlate LASSI-BC performance to volumetric reductions in AD-prone brain regions. Data was gathered from 111 older adults who were comprehensively evaluated and administered the LASSI-BC. Eighty-seven of these participants (51 CU; 36 aMCI) underwent MR imaging. The volumes of 12 AD-prone brain regions were related to LASSI-BC and other memory tests correcting for False Discovery Rate (FDR). Results indicated that, even after adjusting for initial learning ability, the failure to recover from proactive semantic interference (frPSI) on the LASSI-BC differentiated between CU and aMCI groups. An optimal combination of frPSI and initial learning strength on the LASSI-BC yielded an area under the ROC curve of 0.876 (76.1% sensitivity, 82.7% specificity). Further, frPSI on the LASSI-BC was associated with volumetric reductions in the hippocampus, amygdala, inferior temporal lobes, precuneus, and posterior cingulate.

Indexed as

Cortical ThicknessLASSI-LMild Cognitive ImpairmentMRI VolumeProactive Semantic Interference

Identifiers

PMID38873169
PMCPMC11170665

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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.