Evidence map›Paper›PMID 39287680›Full record

ArticleJournal of neurology2024

How to detect affect recognition alterations in amyotrophic lateral sclerosis.

Veronica Castelnovo, Elisa Canu, Edoardo Nicolò Aiello, Beatrice Curti, Elisa Sibilla, Silvia Torre, Fabiola Freri, Chiara Tripodi, Laura Lumaca, Edoardo Gioele Spinelli and 12 more

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. The spectrum of behavioral disorders in amyotrophic lateral sclerosis: current view.Journal of neural transmission (Vienna, Austria : 1996) · 2025
    Review
  3. 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

22 authors.

Veronica CastelnovoNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Elisa CanuNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Edoardo Nicolò AielloDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Beatrice CurtiDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Elisa SibillaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Silvia TorreDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Fabiola FreriNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Chiara TripodiNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Laura LumacaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Edoardo Gioele SpinelliNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Paride SchitoNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Tommaso RussoNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Yuri FalzoneNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Federico VerdeDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Vincenzo SilaniDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Nicola TicozziDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Virginia E SturmMemory and Aging Center, University of California, San Francisco, CA, USA.
Katherine P RankinMemory and Aging Center, University of California, San Francisco, CA, USA.
Maria Luisa Gorno-TempiniMemory and Aging Center, University of California, San Francisco, CA, USA.
Barbara PolettiDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Massimo FilippiNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Federica AgostaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. agosta.federica@hsr.it.ORCID http://orcid.org/0000-0003-3121-4979

Funding

FP7 Ideas: European Research Council StG-2016_714388_NeuroTRACK
6 · The paper itself

Abstract

objectiveTo define the clinical usability of an affect recognition (AR) battery-the Comprehensive Affect Testing System (CATS)-in an Italian sample of patients with amyotrophic lateral sclerosis (ALS).

methods96 ALS patients and 116 healthy controls underwent a neuropsychological assessment including the AR subtests of the abbreviated version of the CATS (CATS-A). CATS-A AR subtests and their global score (CATS-A AR Quotient, ARQ) were assessed for their factorial, convergent, and divergent validity. The diagnostic accuracy of each CATS-A AR measure in discriminating ALS patients with cognitive impairment from cognitively normal controls and patients was tested via receiver-operating characteristics analyses. Optimal cut-offs were identified for CATS-A AR measures yielding an acceptable AUC value (≥ .70). The ability of CATS-A ARQ to discriminate between different ALS cognitive phenotypes was also tested. Gray-matter (GM) volumes of controls, ALS with normal (ALS-nARQ), and impaired ARQ score (ALS-iARQ) were compared using ANCOVA models.

resultsCATS-A AR subtests and ARQ proved to have moderate-to-strong convergent and divergent validity. Almost all considered CATS-A measures reached acceptable accuracy and diagnostic power (AUC range = .79-.83). ARQ showed to be the best diagnostic measure (sensitivity = .80; specificity = .75) and discriminated between different ALS cognitive phenotypes. Compared to ALS-nARQ, ALS-iARQ patients showed reduced GM volumes in the right anterior cingulate, right middle frontal, left inferior temporal, and superior occipital regions.

conclusionsThe AR subtests of the CATS-A, and in particular the CATS-A ARQ, are sound measures of AR in ALS. AR deficits may be a valid marker of frontotemporal involvement in these patients.

Indexed as

Amyotrophic Lateral SclerosisNeuropsychological TestsAgedCognitive DysfunctionFemaleHumansMaleMiddle AgedRecognition, PsychologyReproducibility of ResultsAmyotrophic lateral sclerosisComprehensive Affect Testing SystemEmotion recognitionGray matter volumesSocial cognition

Identifiers

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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.