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dc.contributor.authorPatel, Nikil
dc.contributor.authorPeterson, Katie A
dc.contributor.authorIngram, Ruth U
dc.contributor.authorStorey, Ian
dc.contributor.authorCappa, Stefano F
dc.contributor.authorCatricala, Eleonora
dc.contributor.authorHalai, Ajay
dc.contributor.authorPatterson, Karalyn E
dc.contributor.authorLambon Ralph, Matthew A
dc.contributor.authorRowe, James B
dc.contributor.authorGarrard, Peter
dc.date.accessioned2022-04-14T01:02:20Z
dc.date.available2022-04-14T01:02:20Z
dc.date.issued2022
dc.identifier.issn2632-1297
dc.identifier.other35282164
dc.identifier.otherPMC8914496
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/336090
dc.description.abstractThere are few available methods for qualitatively evaluating patients with primary progressive aphasia. Commonly adopted approaches are time-consuming, of limited accuracy or designed to assess different patient populations. This paper introduces a new clinical test-the Mini Linguistic State Examination-which was designed uniquely to enable a clinician to assess and subclassify both classical and mixed presentations of primary progressive aphasia. The adoption of a novel assessment method (error classification) greatly amplifies the clinical information that can be derived from a set of standard linguistic tasks and allows a five-dimensional profile to be defined. Fifty-four patients and 30 matched controls were recruited. Five domains of language competence (motor speech, phonology, semantics, syntax and working memory) were assessed using a sequence of 11 distinct linguistic assays. A random forest classification was used to assess the diagnostic accuracy for predicting primary progressive aphasia subtypes and create a decision tree as a guide to clinical classification. The random forest prediction model was 96% accurate overall (92% for the logopenic variant, 93% for the semantic variant and 98% for the non-fluent variant). The derived decision tree produced a correct classification of 91% of participants whose data were not included in the training set. The Mini Linguistic State Examination is a new cognitive test incorporating a novel and powerful, yet straightforward, approach to scoring. Rigorous assessment of its diagnostic accuracy confirmed excellent matching of primary progressive aphasia syndromes to clinical gold standard diagnoses. Adoption of the Mini Linguistic State Examination by clinicians will have a decisive impact on the consistency and uniformity with which patients can be described clinically. It will also facilitate screening for cohort-based research, including future therapeutic trials, and is suitable for describing, quantifying and monitoring language deficits in other brain disorders.
dc.languageeng
dc.publisherOxford University Press (OUP)
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceessn: 2632-1297
dc.sourcenlmid: 101755125
dc.subjectFrontotemporal Dementia
dc.subjectPrimary Progressive Aphasia
dc.subjectRandom Forest Classifier
dc.titleA 'Mini Linguistic State Examination' to classify primary progressive aphasia.
dc.typeArticle
dc.date.updated2022-04-14T01:02:19Z
prism.issueIdentifier2
prism.publicationNameBrain Commun
prism.volume4
dc.identifier.doi10.17863/CAM.83519
dcterms.dateAccepted2021-12-17
rioxxterms.versionofrecord10.1093/braincomms/fcab299
rioxxterms.versionVoR
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidPatel, Nikil [0000-0003-2888-9668]
dc.contributor.orcidStorey, Ian [0000-0002-0952-0673]
dc.contributor.orcidHalai, Ajay [0000-0003-1725-7948]
dc.contributor.orcidPatterson, Karalyn E [0000-0003-1927-7424]
dc.contributor.orcidLambon Ralph, Matthew A [0000-0001-5907-2488]
dc.contributor.orcidGarrard, Peter [0000-0001-8268-9718]
dc.identifier.eissn2632-1297
pubs.funder-project-idWellcome Trust (103838/Z/14/Z)
pubs.funder-project-idEuropean Research Council (670428)
pubs.funder-project-idMedical Research Council (MC_UU_00005/12)
pubs.funder-project-idCambridge University Hospitals NHS Foundation Trust (CUH) (146281)
cam.issuedOnline2021-12-21


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International