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Maniaci A, Lechien JR, La Mantia I, Iannella G, Ferlito S, Albanese G, Magliulo G, Pace A, Cammaroto G, Di Mauro P, Vicini C, Cocuzza S. Cognitive Impairment and Mild to Moderate Dysphagia in Elderly Patients: A Retrospective Controlled Study. EAR, NOSE & THROAT JOURNAL 2024; 103:NP671-NP678. [PMID: 35255725 DOI: 10.1177/01455613211054631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background: To investigate whether cognitive impairment in elderly patients could correlate with the severity of swallowing disorders detectable through the endoscopic fiber optic evaluation. Methods: Elderly patients (≥65 years) performing a swallowing evaluation were included and divided according to the Dysphagia outcome and severity scale (DOSS). Neurological evaluation and Mini-Mental test examination (MMET) were administered to detect cognitive impairment. Results: Significantly worse swallowing function was reported in the cognitive impairment group than the control one (40% vs 19%; P = .001). A different significant distribution of swallowing performance was detected according to the patient's MMET score (P < .001; P < .001; P = .01). At the ANOVA test among dependent variables assessed, only age>65 and MMET<10 were significantly correlated with swallowing function (F = 3.862, P = .028; F = 17.49, P = .000). Conclusions: The elderly patient has an increased risk for unrecognized swallowing disorders, with a prevalence of mild to moderate forms. Assessment of cognitive performance could facilitate the identification of swallowing disorders by providing a higher level of suspicion for silent aspiration in subjects with poor MMET scores.
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Affiliation(s)
- Antonino Maniaci
- Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia, " ENT Section, University of Catania, Catania, Italy
| | - Jérome R Lechien
- Department of Human Anatomy and Experimental Oncology, Faculty of Medicine, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, Belgium
| | - Ignazio La Mantia
- Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia, " ENT Section, University of Catania, Catania, Italy
| | - Giannicola Iannella
- Department of Head-Neck Surgery, Otolaryngology, Head-Neck and Oral Surgery Unit, Morgagni Pierantoni Hospital, Forlì, Italy
- Department of Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Salvatore Ferlito
- Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia, " ENT Section, University of Catania, Catania, Italy
| | - Gianluca Albanese
- Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia, " ENT Section, University of Catania, Catania, Italy
| | - Giuseppe Magliulo
- Department of Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Annalisa Pace
- Department of Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Giovanni Cammaroto
- Department of Head-Neck Surgery, Otolaryngology, Head-Neck and Oral Surgery Unit, Morgagni Pierantoni Hospital, Forlì, Italy
| | - Paola Di Mauro
- Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia, " ENT Section, University of Catania, Catania, Italy
| | - Claudio Vicini
- Department of Head-Neck Surgery, Otolaryngology, Head-Neck and Oral Surgery Unit, Morgagni Pierantoni Hospital, Forlì, Italy
- Department ENT and Audiology, University of Ferrara, Ferrara, Italy
| | - Salvatore Cocuzza
- Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia, " ENT Section, University of Catania, Catania, Italy
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Feng HY, Zhang PP, Wang XW. Presbyphagia: Dysphagia in the elderly. World J Clin Cases 2023; 11:2363-2373. [PMID: 37123321 PMCID: PMC10131003 DOI: 10.12998/wjcc.v11.i11.2363] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/08/2023] [Accepted: 03/22/2023] [Indexed: 04/06/2023] Open
Abstract
Dysphagia has been classified as a “geriatric syndrome” and can lead to serious complications that result in a tremendous burden on population health and healthcare resources worldwide. A characteristic age-related change in swallowing is defined as “presbyphagia.” Medical imaging has shown some changes that seriously affect the safety and efficacy of swallowing. However, there is a general lack of awareness of the effects of aging on swallowing function and a belief that these changes are part of normal aging. Our review provides an overview of presbyphagia, which has been a neglected health problem for a long time. Attention and awareness of dysphagia in the elderly population should be strengthened, and targeted intervention measures should be actively implemented.
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Affiliation(s)
- Hai-Yang Feng
- School of Rehabilitation Medicine, Weifang Medical University, Weifang 261021, Shandong Province, China
| | - Ping-Ping Zhang
- School of Rehabilitation Medicine, Weifang Medical University, Weifang 261021, Shandong Province, China
| | - Xiao-Wen Wang
- School of Rehabilitation Medicine, Weifang Medical University, Weifang 261021, Shandong Province, China
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Hsieh SW, Chuang HY, Hung CH, Chen CH. Cognitive Deficits Associated With Dysphagia in Patients With Dementia. J Neurogastroenterol Motil 2021; 27:650-652. [PMID: 34642286 PMCID: PMC8521476 DOI: 10.5056/jnm21027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- Sun-Wung Hsieh
- Department of Neurology, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Neurology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Neuroscience Research Center, Kaohsiung Medical University, Kaohsiung, Taiwan.,Dysphagia Functional Reconstructive Center, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Hui-Yu Chuang
- Department of Neurology, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chih-Hsing Hung
- Dysphagia Functional Reconstructive Center, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.,Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Pediatrics, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chun-Hung Chen
- Department of Neurology, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Neurology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Neuroscience Research Center, Kaohsiung Medical University, Kaohsiung, Taiwan.,Dysphagia Functional Reconstructive Center, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
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Laguarta J, Subirana B. Longitudinal Speech Biomarkers for Automated Alzheimer's Detection. FRONTIERS IN COMPUTER SCIENCE 2021. [DOI: 10.3389/fcomp.2021.624694] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
We introduce a novel audio processing architecture, the Open Voice Brain Model (OVBM), improving detection accuracy for Alzheimer's (AD) longitudinal discrimination from spontaneous speech. We also outline the OVBM design methodology leading us to such architecture, which in general can incorporate multimodal biomarkers and target simultaneously several diseases and other AI tasks. Key in our methodology is the use of multiple biomarkers complementing each other, and when two of them uniquely identify different subjects in a target disease we say they are orthogonal. We illustrate the OBVM design methodology by introducing sixteen biomarkers, three of which are orthogonal, demonstrating simultaneous above state-of-the-art discrimination for two apparently unrelated diseases such as AD and COVID-19. Depending on the context, throughout the paper we use OVBM indistinctly to refer to the specific architecture or to the broader design methodology. Inspired by research conducted at the MIT Center for Brain Minds and Machines (CBMM), OVBM combines biomarker implementations of the four modules of intelligence: The brain OS chunks and overlaps audio samples and aggregates biomarker features from the sensory stream and cognitive core creating a multi-modal graph neural network of symbolic compositional models for the target task. In this paper we apply the OVBM design methodology to the automated diagnostic of Alzheimer's Dementia (AD) patients, achieving above state-of-the-art accuracy of 93.8% using only raw audio, while extracting a personalized subject saliency map designed to longitudinally track relative disease progression using multiple biomarkers, 16 in the reported AD task. The ultimate aim is to help medical practice by detecting onset and treatment impact so that intervention options can be longitudinally tested. Using the OBVM design methodology, we introduce a novel lung and respiratory tract biomarker created using 200,000+ cough samples to pre-train a model discriminating cough cultural origin. Transfer Learning is subsequently used to incorporate features from this model into various other biomarker-based OVBM architectures. This biomarker yields consistent improvements in AD detection in all the starting OBVM biomarker architecture combinations we tried. This cough dataset sets a new benchmark as the largest audio health dataset with 30,000+ subjects participating in April 2020, demonstrating for the first time cough cultural bias.
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