Evidence map›Paper›PMID 34434163›Full record

ArticleFrontiers in neurology2021

Neuropsychological Assessments of Patients With Acquired Brain Injury: A Cluster Analysis Approach to Address Heterogeneity in Web-Based Cognitive Rehabilitation.

Alejandro García-Rudolph, Alberto García-Molina, Eloy Opisso, Josep María Tormos, Vince I Madai, Dietmar Frey, Montserrat Bernabeu

Abstract read
In one paragraph

Article in Frontiers in neurology, 2021. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Alejandro García-RudolphUniversitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.
Alberto García-MolinaUniversitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.
Eloy OpissoUniversitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.
Josep María TormosUniversitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.
Vince I MadaiCLAIM Charité Lab for AI in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.
Dietmar FreyCLAIM Charité Lab for AI in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.
Montserrat BernabeuUniversitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to (1) apply cluster analysis techniques to mixed-type data (numerical and categorical) from baseline neuropsychological standard and widely used assessments of patients with acquired brain injury (ABI) (2) apply state-of-the-art cluster validity indexes (CVI) to assess their internal validity (3) study their external validity considering relevant aspects of ABI rehabilitation such as functional independence measure (FIM) in activities of daily life assessment (4) characterize the identified profiles by using demographic and clinically relevant variables and (5) extend the external validation of the obtained clusters to all cognitive rehabilitation tasks executed by the participants in a web-based cognitive rehabilitation platform (GNPT). We analyzed 1,107 patients with ABI, 58.1% traumatic brain injury (TBI), 21.8% stroke and 20.1% other ABIs (e.g., brain tumors, anoxia, infections) that have undergone inpatient GNPT cognitive rehabilitation from September 2008 to January 2021. We applied the k-prototypes algorithm from the clustMixType R package. We optimized seven CVIs and applied bootstrap resampling to assess clusters stability (fpc R package). Clusters'

Indexed as

acquired brain injurycluster analysiscognitive rehabilitationfunctional independencemixed-type dataneuropsychological assessmentweb-based platform

Identifiers

PMID34434163
PMCPMC8380987

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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.