Browsing by Author "Takada, Leonel T."

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    Classification of Alzheimer’s disease and frontotemporal dementia using routine clinical and cognitive measures across multicentric underrepresented samples: a cross sectional observational study
    (2023) Maito, Marcelo Adrián; Santamaría-García, Hernando; Moguilner, Sebastián; Possin, Katherine L.; Godoy, María E.; Avila-Funes, José Alberto; Behrens, Maria Isabel; Brusco, Ignacio L. Maira Okada de Oliveira,b,r,s,ae Stefanie D. Pina-Escuder; Bruno, Martín A.; Cardona, Juan F.; Custodio, Nilton; García, Adolfo M.; Javandel, Shireen; Lopera, Francisco; Matallana, Diana L.; Miller, Bruce; Okada de Oliveira, Maira; Pina Escudero, Stefanie; Slachevsky Chonchol, Andrea; Ana L Sosa Ortiz; Takada, Leonel T.; Tagliazuchi, Enzo; Valcour, Victor; Yokoyama, Jennifer S.; Ibañez, Agustín
    Background Global brain health initiatives call for improving methods for the diagnosis of Alzheimer’s disease (AD) and frontotemporal dementia (FTD) in underrepresented populations. However, diagnostic procedures in upper middle-income countries (UMICs) and lower-middle income countries (LMICs), such as Latin American countries (LAC), face multiple challenges. These include the heterogeneity in diagnostic methods, lack of clinical harmonisation, and limited access to biomarkers. Methods This cross-sectional observational study aimed to identify the best combination of predictors to discriminate between AD and FTD using demographic, clinical and cognitive data among 1794 participants [904 diagnosed with AD, 282 diagnosed with FTD, and 606 healthy controls (HCs)] collected in 11 clinical centres across five LAC (ReDLat cohort). Findings A fully automated computational approach included classical statistical methods, support vector machine procedures, and machine learning techniques (random forest and sequential feature selection procedures). Results demonstrated an accurate classification of patients with AD and FTD and HCs. A machine learning model produced the best values to differentiate AD from FTD patients with an accuracy = 0.91. The top features included social cognition, neuropsychiatric symptoms, executive functioning performance, and cognitive screening; with secondary contributions from age, educational attainment, and sex. Interpretation Results demonstrate that data-driven techniques applied in archival clinical datasets could enhance diagnostic procedures in regions with limited resources. These results also suggest specific fine-grained cognitive and behavioural measures may aid in the diagnosis of AD and FTD in LAC. Moreover, our results highlight an opportunity for harmonisation of clinical tools for dementia diagnosis in the region.
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    The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science
    (2021) Ibáñez, Agustín; Yokoyama, Jennifer S.; Possin, Katherine L.; Matallana, Diana; Lopera, Francisco; Nitrini, Ricardo; Takada, Leonel T.; Custodio, Nilton; Sosa Ortiz, Ana Luisa; Avila-Funes, José Alberto; Behrens, María Isabel; Slachevsky, Andrea; Myers, Richard M.; Cochran, J. Nicholas; Brusco, Luis Ignacio; Bruno, Martin A.; Brucki, Sonia M. D.; Pina-Escudero, Stefanie Danielle; Oliveira, Maira Okada de; Donnelly Kehoe, Patricio; Santamaria-Garcia, Hernando; Moguilner, Sebastián; Tagliazucchi, Enzo; Maito, Marcelo; Longoria Ibarrola, Erika Mariana; Pintado-Caipa, Maritza; Godoy, Maria Eugenia; Bakman, Vera; Javandel, Shireen; Kosik, Kenneth S.; Valcour, Victor; Miller, Bruce L.; The Latin America the Caribbean Consortium on Dementia (LAC-CD)
    Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat’s regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer’s disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems’ infrastructure, and increase translational research collaborations across the continent.

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