TY - JOUR
T1 - Cognitive Impairment and Dementia in Primary Care
T2 - Current Knowledge and Future Directions Based on Findings From a Large Cross-Sectional Study in Crete, Greece
AU - Bertsias, Antonios
AU - Symvoulakis, Emmanouil
AU - Tziraki, Chariklia
AU - Panagiotakis, Symeon
AU - Mathioudakis, Lambros
AU - Zaganas, Ioannis
AU - Basta, Maria
AU - Boumpas, Dimitrios
AU - Simos, Panagiotis
AU - Vgontzas, Alexandros
AU - Lionis, Christos
N1 - Funding Information:
This project was supported by a grant from the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program Education and Lifelong Learning of the National Strategic Reference Framework (NSRF)-Research
Funding Information:
We would like to thank Myron Galenianos and Cynthia Manasaki for their valuable contribution to the coordination of the project. We would also like to thank Dr. Nikolaos Scarmeas for the overall assistance in the design and evaluation of the project. We would like to thank the following study nurses who played an important role in recruitment of participants and conducted the interviews and tests: Sofia Marinaki, Marina Lyroni, Maria Maniou, Georgia Fragkiadaki, Maria Titaki, and Katerina Almpantaki. Finally, we would like to thank the following GPs and physicians for their contribution to the project: Drs. Ioanna Tsiligianni and Theodoros Vasilopoulos from the Health Center of Agia Varvara; Dr. Eva Ladoukaki from the Health Center of Charakas; Drs. Nikolaos Tsakountakis, Rodanthi Pateli, Eirini Kalogridaki, Kornilia Makri, and Aggeliki Vasilaki from the Health Center of Kastelli; Drs. Ioanna Stefanaki and Emmanouil Papamastorakis from the Health Center of Ano Viannos; Drs. Dimitroula Prokopiadou and Polyvios Papadokostakis from the Health Center of Arkalochori and the private primary care practitioner Dr. Eleni Klouva. Finally we would like to thank Drs. George Duijker, Stefania Kapetanaki, Irini Koutentaki, Nikolaos Fountoulakis, and Simeon Panagiotakis for their overall contribution to the project. Funding. This project was supported by a grant from the European Union (European Social Fund ? ESF) and Greek national funds through the Operational Program Education and Lifelong Learning of the National Strategic Reference Framework (NSRF)-Research Funding Program: THALES entitled UOC-Multidisciplinary network for the study of Alzheimer's Disease (Grant Code: MIS 377299).
Publisher Copyright:
© Copyright © 2020 Bertsias, Symvoulakis, Tziraki, Panagiotakis, Mathioudakis, Zaganas, Basta, Boumpas, Simos, Vgontzas and Lionis.
PY - 2020/11/23
Y1 - 2020/11/23
N2 - Introduction: Dementia severely affects the quality of life of patients and their caregivers; however, it is often not adequately addressed in the context of a primary care consultation, especially in patients with multi-morbidity. Study Population and Methods: A cross-sectional study was conducted between March-2013 and December-2014 among 3,140 consecutive patients aged >60 years visiting 14 primary health care practices in Crete, Greece. The Mini-Mental-State-Examination [MMSE] was used to measure cognitive status using the conventional 24-point cut-off. Participants who scored low on MMSE were matched with a group of elders scoring >24 points, according to age and education; both groups underwent comprehensive neuropsychiatric and neuropsychological assessment. For the diagnosis of dementia and Mild-Cognitive-Impairment (MCI), the Diagnostic and Statistical Manual-of-Mental-Disorders (DSM-IV) criteria and the International-Working-Group (IWG) criteria were used. Chronic conditions were categorized according to ICD-10 categories. Logistic regression was used to provide associations between chronic illnesses and cognitive impairment according to MMSE scores. Generalized Linear Model Lasso Regularization was used for feature selection in MMSE items. A two-layer artificial neural network model was used to classify participants as impaired (dementia/MCI) vs. non-impaired. Results: In the total sample of 3,140 participants (42.1% men; mean age 73.7 SD = 7.8 years), low MMSE scores were identified in 645 (20.5%) participants. Among participants with low MMSE scores 344 (54.1%) underwent comprehensive neuropsychiatric evaluation and 185 (53.8%) were diagnosed with Mild-Cognitive-Impairment (MCI) and 118 (34.3%) with dementia. Mental and behavioral disorders (F00-F99) and diseases of the nervous system (G00-G99) increased the odds of low MMSE scores in both genders. Generalized linear model lasso regularization indicated that 7/30 MMSE questions contributed the most to the classification of patients as impaired (dementia/MCI) vs. non-impaired with a combined accuracy of 82.0%. These MMSE items were questions 5, 13, 19, 20, 22, 23, and 26 of the Greek version of MMSE assessing orientation in time, repetition, calculation, registration, and visuo-constructive ability. Conclusions: Our study identified certain chronic illness-complexes that were associated with low MMSE scores within the context of primary care consultation. Also, our analysis indicated that seven MMSE items provide strong evidence for the presence of dementia or MCI.
AB - Introduction: Dementia severely affects the quality of life of patients and their caregivers; however, it is often not adequately addressed in the context of a primary care consultation, especially in patients with multi-morbidity. Study Population and Methods: A cross-sectional study was conducted between March-2013 and December-2014 among 3,140 consecutive patients aged >60 years visiting 14 primary health care practices in Crete, Greece. The Mini-Mental-State-Examination [MMSE] was used to measure cognitive status using the conventional 24-point cut-off. Participants who scored low on MMSE were matched with a group of elders scoring >24 points, according to age and education; both groups underwent comprehensive neuropsychiatric and neuropsychological assessment. For the diagnosis of dementia and Mild-Cognitive-Impairment (MCI), the Diagnostic and Statistical Manual-of-Mental-Disorders (DSM-IV) criteria and the International-Working-Group (IWG) criteria were used. Chronic conditions were categorized according to ICD-10 categories. Logistic regression was used to provide associations between chronic illnesses and cognitive impairment according to MMSE scores. Generalized Linear Model Lasso Regularization was used for feature selection in MMSE items. A two-layer artificial neural network model was used to classify participants as impaired (dementia/MCI) vs. non-impaired. Results: In the total sample of 3,140 participants (42.1% men; mean age 73.7 SD = 7.8 years), low MMSE scores were identified in 645 (20.5%) participants. Among participants with low MMSE scores 344 (54.1%) underwent comprehensive neuropsychiatric evaluation and 185 (53.8%) were diagnosed with Mild-Cognitive-Impairment (MCI) and 118 (34.3%) with dementia. Mental and behavioral disorders (F00-F99) and diseases of the nervous system (G00-G99) increased the odds of low MMSE scores in both genders. Generalized linear model lasso regularization indicated that 7/30 MMSE questions contributed the most to the classification of patients as impaired (dementia/MCI) vs. non-impaired with a combined accuracy of 82.0%. These MMSE items were questions 5, 13, 19, 20, 22, 23, and 26 of the Greek version of MMSE assessing orientation in time, repetition, calculation, registration, and visuo-constructive ability. Conclusions: Our study identified certain chronic illness-complexes that were associated with low MMSE scores within the context of primary care consultation. Also, our analysis indicated that seven MMSE items provide strong evidence for the presence of dementia or MCI.
UR - http://www.scopus.com/inward/record.url?scp=85097415813&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097415813&partnerID=8YFLogxK
U2 - 10.3389/fmed.2020.592924
DO - 10.3389/fmed.2020.592924
M3 - Article
C2 - 33330553
AN - SCOPUS:85097415813
SN - 2296-858X
VL - 7
JO - Frontiers in Medicine
JF - Frontiers in Medicine
M1 - 592924
ER -