Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
Itel MMSE: a short phone screening test for cognitive decline. Italian Validation study by the SINdem Neuropsychology Working Group.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Quaranta Davide, L'Abbate Federica, Pelosi Annalisa, Arighi Andrea, Asoni Gesuina, Bagattini Chiara, Bessi Valentina, Bonanni Laura, Bortoletto Marta, Bruni Amalia Cecilia, Cagnin Annachiara, Cappa Stefano F, Giubilei Franco, Guarino Maria, Iavarone Alessandro, Isella Valeria, Luca Antonina, Monastero Roberto, Pellegrini Francesca Ferrari, Perini Marta, Piccoli Tommaso, Rainero Innocenzo, Tedeschi Gioacchino, Marra Camillo, Caffarra Paolo
Аннотация
INTRODUCTION: The Italian telephone-based Mini-Mental State Examination (Itel-MMSE) is considered a very easy tool for screening individuals with dementia, gained importance during COVID-19, but lacks validation and faces a ceiling effect.
AIM: In the present study, we conducted a study standardizing and validating it, establishing cut-off values for two versions.
METHODS: Across 24 Italian sites, 707 healthy individuals (50-89 years, men: 268, women: 439) with diverse educational levels (3-24 years) were recruited. Subjects met criteria for normal conditions investigated through a semi-structured interview covering neurological, psychiatric, general medical, and psychopharmacological history. Two test versions were created to assess test-retest reliability at 45-day intervals. We also enrolled 187 subjects with Mild Cognitive Impairment (MCI) and 181 with Alzheimer's Disease (AD) for validation. The raw scores obtained on both versions of Itel-MMSE were set as dependent variables in linear regression models that included age, education, and gender as independent variables. RESULTS : Mean raw Itel-MMSE1 score was 20.82 (range: 13-22). Multiple linear regression demonstrated significant effects of sociodemographic variables for age and education, establishing a new cut-off ≥ 18.49. Mean raw Itel-MMSE2 score was 20.97 (range: 10-22), with a new cut-off ≥ 18.45. Validation showed high informative values, with areas under the curve (AUCs) for MCI and AD conditions and both versions (Itel-MMSE1: MCI AUC = 0.801, AD AUC = 0.907; Itel-MMSE2: MCI AUC = 0.827, AD AUC = 0.977).
CONCLUSION: The Itel-MMSE proves valuable as a screening method for detecting and monitoring dementia in remote phone screenings, with different cut-offs aiding MCI patient identification in clinical settings.
AIM: In the present study, we conducted a study standardizing and validating it, establishing cut-off values for two versions.
METHODS: Across 24 Italian sites, 707 healthy individuals (50-89 years, men: 268, women: 439) with diverse educational levels (3-24 years) were recruited. Subjects met criteria for normal conditions investigated through a semi-structured interview covering neurological, psychiatric, general medical, and psychopharmacological history. Two test versions were created to assess test-retest reliability at 45-day intervals. We also enrolled 187 subjects with Mild Cognitive Impairment (MCI) and 181 with Alzheimer's Disease (AD) for validation. The raw scores obtained on both versions of Itel-MMSE were set as dependent variables in linear regression models that included age, education, and gender as independent variables. RESULTS : Mean raw Itel-MMSE1 score was 20.82 (range: 13-22). Multiple linear regression demonstrated significant effects of sociodemographic variables for age and education, establishing a new cut-off ≥ 18.49. Mean raw Itel-MMSE2 score was 20.97 (range: 10-22), with a new cut-off ≥ 18.45. Validation showed high informative values, with areas under the curve (AUCs) for MCI and AD conditions and both versions (Itel-MMSE1: MCI AUC = 0.801, AD AUC = 0.907; Itel-MMSE2: MCI AUC = 0.827, AD AUC = 0.977).
CONCLUSION: The Itel-MMSE proves valuable as a screening method for detecting and monitoring dementia in remote phone screenings, with different cut-offs aiding MCI patient identification in clinical settings.