Dysphagia in primary progressive aphasia: Clinical predictors and neuroanatomical basis

被引:0
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作者
Mazzeo, Salvatore [1 ,2 ,3 ,4 ]
Mulroy, Eoin [1 ]
Jiang, Jessica [1 ]
Lassi, Michael [5 ,6 ]
Johnson, Jeremy C. S. [1 ]
Hardy, Chris J. D. [1 ]
Rohrer, Jonathan D. [1 ]
Warren, Jason D. [1 ]
Volkmer, Anna [7 ,8 ]
机构
[1] UCL, UCL Queen Sq Inst Neurol, Dementia Res Ctr, Dept Neurodegenerat Dis, London, England
[2] Univ Florence, Res & Innovat Ctr Dementia CRIDEM, Azienda Osped Univ Careggi, Florence, Italy
[3] Univ Vita Salute San Raffaele, Milan, Italy
[4] IRCCS Policlin San Donato, San Donato Milanese, Italy
[5] Scuola Super Sant Anna, BioRobot Inst, Pisa, Italy
[6] Scuola Super Sant Anna, Dept Excellence Robot & AI, Pisa, Italy
[7] UCL, Dept Psychol & Language Sci, London, England
[8] UCL, Chandler House,2 Wakefield St, London WC1N 1PF, England
关键词
Alzheimer dementia; dysphagia; primary progressive aphasia; semantic dementia; swallowing; SUPRANUCLEAR PALSY; DIAGNOSIS; PATHOLOGY; APRAXIA; STROKE; TIME;
D O I
10.1111/ene.16370
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background and purposeDysphagia is an important feature of neurodegenerative diseases and potentially life-threatening in primary progressive aphasia (PPA) but remains poorly characterized in these syndromes. We hypothesized that dysphagia would be more prevalent in nonfluent/agrammatic variant (nfv)PPA than other PPA syndromes, predicted by accompanying motor features, and associated with atrophy affecting regions implicated in swallowing control.MethodsIn a retrospective case-control study at our tertiary referral centre, we recruited 56 patients with PPA (21 nfvPPA, 22 semantic variant [sv]PPA, 13 logopenic variant [lv]PPA). Using a pro forma based on caregiver surveys and clinical records, we documented dysphagia (present/absent) and associated, potentially predictive clinical, cognitive, and behavioural features. These were used to train a machine learning model. Patients' brain magnetic resonance imaging scans were assessed using voxel-based morphometry and region-of-interest analyses comparing differential atrophy profiles associated with dysphagia presence/absence.ResultsDysphagia was significantly more prevalent in nfvPPA (43% vs. 5% svPPA and no lvPPA). The machine learning model revealed a hierarchy of features predicting dysphagia in the nfvPPA group, with excellent classification accuracy (90.5%, 95% confidence interval = 77.9-100); the strongest predictor was orofacial apraxia, followed by older age, parkinsonism, more severe behavioural disturbance, and more severe cognitive impairment. Significant grey matter atrophy correlates of dysphagia in nfvPPA were identified in left middle frontal, right superior frontal, and right supramarginal gyri and right caudate.ConclusionsDysphagia is a common feature of nfvPPA, linked to underlying corticosubcortical network dysfunction. Clinicians should anticipate this symptom particularly in the context of other motor features and more severe disease.
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页数:10
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