Evidence map›Paper›PMID 36938527›Full record

ArticleBrain communications2023

A new approach to digitized cognitive monitoring: validity of the SelfCog in Huntington's disease.

Marine Lunven, Karen Hernandez Dominguez, Katia Youssov, Jennifer Hamet Bagnou, Rafika Fliss, Henri Vandendriessche, Blanche Bapst, Graça Morgado, Philippe Remy, Robin Schubert and 6 more

Open access · goldFull text read
In one paragraph

Article in Brain communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 39% of its field
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

16 authors at 6 institutions in 3 countries.

Marine LunvenDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Karen Hernandez DominguezDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Katia YoussovDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Jennifer Hamet BagnouDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Rafika FlissDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Henri VandendriesscheDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Blanche BapstDepartment of Neuroradiology, AP-HP, Henri Mondor University Hospital, 94010 Créteil, France.
Graça MorgadoInserm, Centre d'Investigation Clinique 1430, APHP, Hôpital Henri Mondor, 94010 Créteil, France.
Philippe RemyDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Robin SchubertGeorge Huntington Institute, Technology-Park, 48149 Muenster, Germany.
Ralf ReilmannGeorge Huntington Institute, Technology-Park, 48149 Muenster, Germany.
Monica BusseCentre for Trials Research, Cardiff University, Cardiff CF14 4EP, UK.
David CraufurdManchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9PL, UK.
Renaud MassartDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Anne RosserWales Brain Research And Intracranial Neurotherapeutics (BRAIN) Biomedical Research Unit, College of Biomedical and Life Sciences, Cardiff University, Cardiff CF14 4EP, UK.ORCID https://orcid.org/0000-0002-4716-4753
Anne-Catherine Bachoud-LéviDépartement d'Etudes Cognitives, École normale supérieure, PSL University, 75005 Paris, France.
Inserm · FRCardiff University · GBHertie Institute for Clinical Brain Research · DEManchester Academic Health Science Centre · GBUniversité Paris-Est Créteil · FRUniversity of Münster · DE

Funding

HCRW_ RFPPB-16A-1298Medical Research Council MR/L010305/1
6 · The paper itself

Abstract

Cognitive deficits represent a hallmark of neurodegenerative diseases, but evaluating their progression is complex. Most current evaluations involve lengthy paper-and-pencil tasks which are subject to learning effects dependent on the mode of response (motor or verbal), the countries' language or the examiners. To address these limitations, we hypothesized that applying neuroscience principles may offer a fruitful alternative. We thus developed the SelfCog, a digitized battery that tests motor, executive, visuospatial, language and memory functions in 15 min. All cognitive functions are tested according to the same paradigm, and a randomization algorithm provides a new test at each assessment with a constant level of difficulty. Here, we assessed its validity, reliability and sensitivity to detect decline in early-stage Huntington's disease in a prospective and international multilingual study (France, the UK and Germany). Fifty-one out of 85 participants with Huntington's disease and 40 of 52 healthy controls included at baseline were followed up for 1 year. Assessments included a comprehensive clinical assessment battery including currently standard cognitive assessments alongside the SelfCog. We estimated associations between each of the clinical assessments and SelfCog using Spearman's correlation and proneness to retest effects and sensitivity to decline through linear mixed models. Longitudinal effect sizes were estimated for each cognitive score. Voxel-based morphometry and tract-based spatial statistics analyses were conducted to assess the consistency between performance on the SelfCog and MRI 3D-T1 and diffusion-weighted imaging in a subgroup that underwent MRI at baseline and after 12 months. The SelfCog detected the decline of patients with Huntington's disease in a 1-year follow-up period with satisfactory psychometric properties. Huntington's disease patients are correctly differentiated from controls. The SelfCog showed larger effect sizes than the classical cognitive assessments. Its scores were associated with grey and white matter damage at baseline and over 1 year. Given its good performance in longitudinal analyses of the Huntington's disease cohort, it should likely become a very useful tool for measuring cognition in Huntington's disease in the future. It highlights the value of moving the field along the neuroscience principles and eventually applying them to the evaluation of all neurodegenerative diseases.

Indexed as

clinical trialdigitized cognitive assessmentHuntington’s diseaselongitudinal follow-upneurodegenerative disease

Identifiers

PMID36938527
PMCPMC10018460
OpenAlexW4323363322

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read13
identifiers read1
Read underepoch 390

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.