Acta neurologica Belgica · 2025
Predicting cognitive decline using tongue pressure: a novel, non-invasive screening strategy for dementia in geriatric dentistry.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Srinivas Sowmya, Arjun S, More Veena, Aparna M S, Ramesh K, Doddawad Vidya G
Аннотация
BACKGROUND: Cognitive decline and dementia pose significant public health challenges, especially in aging populations. Oral frailty-characterized by reduced tongue pressure, chewing difficulties, and swallowing impairment-has been linked to cognitive deterioration. However, the potential of tongue pressure as a biomarker for early cognitive decline remains underexplored.
PURPOSE: This study investigates the relationship between tongue pressure, cognitive function, educational background, and dentition status to assess its feasibility as a non-invasive screening tool for early dementia detection.
MATERIALS AND METHODS: A novel, low-cost tongue pressure measurement device was developed to evaluate oral function in older adults. Cognitive status was assessed using the Montreal Cognitive Assessment (MoCA), while machine learning models were employed to predict cognitive decline based on tongue pressure, dentition, and education level. Among the models tested, the Decision Tree classifier was recommended due to its high interpretability and performance, achieving 94% accuracy, 0.94 recall, 0.94 precision, and an AUC of 0.95.
RESULTS: Lower tongue pressure was significantly associated with cognitive decline. Dentition status and education level also showed strong correlations. The Decision Tree model effectively predicted cognitive impairment using these variables.
CONCLUSION: Tongue pressure measurement, supported by machine learning, presents a promising, non-invasive, and accessible method for early cognitive decline screening. The developed tool has strong potential for clinical and community-based application, especially in resource-limited settings.
PURPOSE: This study investigates the relationship between tongue pressure, cognitive function, educational background, and dentition status to assess its feasibility as a non-invasive screening tool for early dementia detection.
MATERIALS AND METHODS: A novel, low-cost tongue pressure measurement device was developed to evaluate oral function in older adults. Cognitive status was assessed using the Montreal Cognitive Assessment (MoCA), while machine learning models were employed to predict cognitive decline based on tongue pressure, dentition, and education level. Among the models tested, the Decision Tree classifier was recommended due to its high interpretability and performance, achieving 94% accuracy, 0.94 recall, 0.94 precision, and an AUC of 0.95.
RESULTS: Lower tongue pressure was significantly associated with cognitive decline. Dentition status and education level also showed strong correlations. The Decision Tree model effectively predicted cognitive impairment using these variables.
CONCLUSION: Tongue pressure measurement, supported by machine learning, presents a promising, non-invasive, and accessible method for early cognitive decline screening. The developed tool has strong potential for clinical and community-based application, especially in resource-limited settings.