ORCID: https://orcid.org/0000-0003-1981-7435; Sakka, Paraskevi; Georgiou, Eleni-Zacharoula; Charalampopoulou, Μarina; Felemegkas, Panagiotis; Leroi, Iracema; Batsidis, Apostolos; Perna, Laura; Politis, Antonios; Scarmeas, Nikolaos und Economou, Polychronis
(2025):
The potential of depressive symptoms to identify cognitive impairment in ageing.
In: European Journal of Ageing, Bd. 22, 7
[PDF, 691kB]

Abstract
Depressive symptoms are common in mild cognitive impairment (MCI), dementia caused by Alzheimer’s disease (AD dementia) and in cognitively unimpaired older adults. However, it is unclear whether they could contribute to the identification of cognitive impairment in ageing. To assess the potential utility of depressive symptoms to distinguish between healthy cognitive ageing and MCI and AD dementia. The diagnostic workup of the cognitive function of 1737 older cognitively unimpaired individuals, 334 people with MCI and 142 individuals with AD dementia relied on a comprehensive neuropsychiatric assessment, including the Mini Mental State Examination (MMSE). Depressive symptoms were tapped with the 15-item Geriatric Depression Scale (GDS). Proportional odds logistic regression (POLR) models and the machine learning technique Adaptive Boosting algorithm (AdaBoost) were employed. Stratified repeated random subsampling (stratified bootstrap resampling) was used to recursive partitioning to training- and validation set (70/30 ratio). The average accuracy of the POLR models for the GDS total score in distinguishing between cognitive impairment and healthy cognitive ageing exceeded 78% and was inferior to that of MMSE. Of note, the sensitivity of GDS total score was very low. By employing the AdaBoost algorithm and considering GDS items separately, the average accuracy was higher than 0.72 and comparable to that of the MMSE, while sensitivity- and specificity values were more balanced. The findings of the study provide initial evidence that depressive symptoms may contribute to distinguishing between cognitive impairment and cognitively healthy ageing.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Munich Cluster for Systems Neurology (SyNergy)
Medizin > Klinikum der LMU München > Klinik und Poliklink für Psychiatrie und Psychotherapie |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-124789-0 |
ISSN: | 1613-9372 |
Sprache: | Englisch |
Dokumenten ID: | 124789 |
Datum der Veröffentlichung auf Open Access LMU: | 26. Mrz. 2025 14:20 |
Letzte Änderungen: | 26. Mrz. 2025 14:20 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198 |