Evidence map›Paper›PMID 42433176›Full record

ArticleAnnals of clinical and translational neurology2026

Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions.

Martina Del Giovane, Valentina Giunchiglia, Michael C B David, Magdalena A Kolanko, William R Trender, Peter J Hellyer, Harmeena Kaur, David J Sharp, Christopher Carswell, Paresh A Malhotra and 1 more

Abstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Martina Del GiovaneDepartment of Brain Sciences, Imperial College London, London, UK.ORCID https://orcid.org/0000-0002-3476-8494
Valentina GiunchigliaDepartment of Brain Sciences, Imperial College London, London, UK.
Michael C B DavidDepartment of Brain Sciences, Imperial College London, London, UK.
Magdalena A KolankoDepartment of Brain Sciences, Imperial College London, London, UK.
William R TrenderDepartment of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Peter J HellyerDepartment of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Harmeena KaurDepartment of Brain Sciences, Imperial College London, London, UK.
David J SharpDepartment of Brain Sciences, Imperial College London, London, UK.
Christopher CarswellDepartment of Brain Sciences, Imperial College London, London, UK.ORCID https://orcid.org/0000-0001-9007-7017
Paresh A MalhotraDepartment of Brain Sciences, Imperial College London, London, UK.ORCID https://orcid.org/0000-0002-1897-0780
Adam HampshireDepartment of Brain Sciences, Imperial College London, London, UK.

Funding

Alzheimer's Society 608 AS-CTF-22-013Imperial College Biomedical Research CentreMedical Research Council MR/W00710X/1Medical Research Council MR/W016095/1Medical Research Council MR/W030098/1UK Dementia Research Institute UKDRI-7201
6 · The paper itself

Abstract

objectiveTo assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment.

methodsPatients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive tasks (Cognitron). We evaluated cognition relative to a large normative dataset (N ≈ 400,000), adjusting for device and demographics which can affect performance. Principal Component Analysis (PCA) was used to derive domain-specific and total composite scores. We compared clinical groups and correlated performance with standard assessments.

resultsUptake was ~70%. PCA identified components across memory, processing speed, language, and executive functions. AD showed memory and language impairments compared with the norms and other groups. iNPH had greater executive and processing speed deficits, consistent with a subcortical impairment profile. TBI showed milder deficits in memory, working memory, and language. Cognitron total composite was associated with standard supervised tests (ADAS-Cog: β = -0.76, p < 0.001 and ACE-III: β = 0.69, p < 0.001). In iNPH, Cognitron composite predicted walking speed (estimate = 1.10, p < 0.001), a core clinical feature of the disease which is difficult to evaluate remotely. We selected five tasks with high completion rates, discriminability between conditions, and broad cognitive coverage. The derived short composite showed very high accuracy in separating AD (AUC = 0.94) and iNPH (AUC = 0.90) from age-matched norms; performance was weaker for TBI (AUC = 0.66).

interpretationOnline assessment in older clinical populations is feasible and sensitive to subtle disease-specific cognitive deficits. A demographically adjusted, 15-min battery offers a scalable adjunct to standard testing, with potential to reduce burden on patients and healthcare systems.

Indexed as

Alzheimer's diseasedementianormal pressure hydrocephalusonline cognitive testingtraumatic brain injury

Identifiers

PMID42433176
PMCPMC13394833

What Socratic holds

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Registered trials

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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 Socratic graph.