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- Hesseberg, K, et al.
(författare)
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Physical Fitness in Older People Recently Diagnosed with Cognitive Impairment Compared to Older People Recently Discharged from Hospital
- 2016
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Ingår i: Dementia and geriatric cognitive disorders extra. - : S. Karger AG. - 1664-5464. ; 6:3, s. 396-406
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Tidskriftsartikel (refereegranskat)abstract
- <b><i>Background/Aims:</i></b> There is evidence of an association between cognitive function and physical fitness. The aim of this study was to compare physical fitness in patients with cognitive impairment with a group of older people recently discharged from hospital. <b><i>Methods:</i></b> A cross-sectional study with 98 patients recently diagnosed with cognitive impairment and 115 patients recently discharged from hospital. Associations between the study group variable and different components in the Senior fitness test were examined, controlling for demographic factors and comorbidity. <b><i>Results:</i></b> The group recently diagnosed with cognitive impairment indicated poorer results on three of six physical fitness components (p < 0.05). <b><i>Conclusion:</i></b> Older adults with cognitive impairment are in need of individually tailored physical activity programs to increase the level of physical fitness.
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| 2. |
- Munoz-Ruiz, Miguel Angel, et al.
(författare)
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Using the Disease State Fingerprint Tool for Differential Diagnosis of Frontotemporal Dementia and Alzheimer's Disease
- 2016
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Ingår i: Dementia and Geriatric Cognitive Disorders Extra. - : S. Karger AG. - 1664-5464. ; 6:2, s. 313-329
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Tidskriftsartikel (refereegranskat)abstract
- Background: Disease State Index (DSI) and its visualization, Disease State Fingerprint (DSF), form a computer-assisted clinical decision making tool that combines patient data and compares them with cases with known outcomes. Aims: To investigate the ability of the DSI to diagnose frontotemporal dementia (FTD) and Alzheimer's disease (AD). Methods: The study cohort consisted of 38 patients with FTD, 57 with AD and 22 controls. Autopsy verification of FTD with TDP-43 positive pathology was available for 14 and AD pathology for 12 cases. We utilized data from neuropsychological tests, volumetric magnetic resonance imaging, single-photon emission tomography, cerebrospinal fluid biomarkers and the APOE genotype. The DSI classification results were calculated with a combination of leave-one-out cross-validation and bootstrapping. A DSF visualization of a FTD patient is presented as an example. Results: The DSI distinguishes controls from FTD (area under the receiver-operator curve, AUC = 0.99) and AD (AUC = 1.00) very well and achieves a good differential diagnosis between AD and FTD (AUC = 0.89). In subsamples of autopsy-confirmed cases (AUC = 0.97) and clinically diagnosed cases (AUC = 0.94), differential diagnosis of AD and FTD performs very well. Conclusions: DSI is a promising computer-assisted biomarker approach for aiding in the diagnostic process of dementing diseases. Here, DSI separates controls from dementia and differentiates between AD and FTD.
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