Background Diagnostics of Alzheimer’s Disease (AD) require a multimodal approach. Neuropsychologists examine the degree and etiology of dementia syndromes and results are combined with those of cerebrospinal fluid markers and imaging data. In the diagnostic process, neuropsychologists often rely on anamnestic and clinical information, as well as cognitive tests, prior to the availability of exhaustive etiological information. The congruency of this phenomenological approach with results from FDG-PET/CT examinations remains to be explored. The latter yield highly accurate diagnostic information. Method A mixed sample of N = 127 hospitalized neurological patients suspected of displaying a dementia syndrome underwent extensive neuropsychological and FDG-PET/CT examinations. Neuropsychological examinations included an anamnestic and clinical interview, and the CERAD cognitive test battery. Two decisional approaches were considered: First, routine diagnostic results were obtained, i.e. the final clinical decision of the examining neuropsychologist (ADClinical vs. non-ADClinical). Secondly, a logistic regression model was implemented, relying on CERAD profiles alone. CERAD subscales that best predicted AD based on FDG-PET/CT were identified and a nominal categorization obtained (ADTest vs. non-ADTest). Congruency of results from both approaches with those of the FDG-PET/CT (ADPET vs. non-ADPET) were estimated with Cohen’s Kappa (κ) and Yule’s Y coefficient of colligation. Descriptive estimates of accuracy, sensitivity and specificity of CERAD relative to FDG-PET/CT diagnostics were derived. Results ADPET patients constituted N = 33/127 (26%) of the sample. The clinical decision approach (ADClinical vs. non-ADClinical) showed substantial agreement with the FDG-PET/CT classification (κ = .69, Y = .72) involving good accuracy (84.2%), moderate sensitivity (75.8%) and excellent specificity (92.6%). In contrast, the decisional approach that relied on CERAD data alone (ADTest vs. non-ADTest) involved only moderate agreement with the FDG-PET/CT (κ = .54, Y = .62) with lower accuracy (74.8%), attributable to decreased sensitivity (56.3%) and comparable specificity (93.3%). Conclusions It is feasible to identify AD through a comprehensive neuropsychological examination in a mixed sample of neurological patients. However, within the boundaries of methods applied here, decisions based on cognitive test results alone appear limited. One may conclude that the clinical impression based on anamnestic and clinical information obtained by the neuropsychological examiner plays a crucial role in the identification of AD patients in routine clinical practice.
Background:Clinical diagnostics of Alzheimer’s Disease (AD) require a multimodal approach. Neuropsychological assessments are commonly implemented to obtain information about the degree of cognitive impairment, while cerebrospinal fluid markers and imaging data provide etiological information. In routine clinical practice, neuropsychologists often have to rely on relatively limited anamnestic information, as well as cognitive test results and are required to infer whether patients actually suffer from AD, prior to the availability of exhaustive etiological information. To date, it remains to be explored how congruent the results of such a phenomenological approach may be with results from neuroimaging techniques such as FDG-PET/CT examinations. The latter are known to yield highly accurate diagnostic information. Methods:A mixed sample of N=127 hospitalized neurological patients suspected of displaying a syndrome of dementia underwent routine differential diagnostics including an extensive neuropsychological and an FDG-PET/CT examination. The neuropsychological examination included an interview in which anamnestic information was obtained, as well as the administration of the standardized CERAD cognitive test battery. Two separate decisional approaches were considered: First, routine diagnostic results were obtained, as reflected by the final clinical decision of the examining neuropsychologist (ADClinical vs. non-ADClinical) for the routine clinical report. Secondly, a logistic regression model was implemented, that relied on data from the CERAD test profiles alone. Based on the logistic regression, the CERAD test subscales that best predicted the presence of AD according to the FDG-PET/CT results were identified and a nominal categorization was obtained (ADTest vs. non-ADTest). Results from both decisional approaches were matched against the FDG-PET/CT results (ADPET vs. non-ADPET) in cross-tables and estimates of accuracy, sensitivity and specificity were derived.Results:Based on the FDG-PET/CT examination, N=33/127 (26%) of the patients were diagnosed as ADPET patients. When matched against these results, the clinical decision approach of the neuropsychological examination (ADClinical vs. non-ADClinical) yielded a good accuracy (84.2%), involving moderate sensitivity (75.8%) and excellent specificity (92.6%). The decisional approach that relied on the neuropsychological test data alone (ADTest vs. non-ADTest) involved a lower estimate of accuracy (74.8%), that was attributable to considerably decreased sensitivity (56.3%) while specificity was comparable (93.3%) to the clinical decision model.Conclusions:These results indicate that it is feasible to identify AD in context of a comprehensive routine neuropsychological examination in a mixed sample of neurological patients, relative to an FDG-PET/CT classification. However, decisions based on cognitive test results alone appear limited in this respect. It may be assumed that anamnestic information in combination with the clinical impression obtained by the neuropsychological examiner play a crucial role in the identification of AD patients in routine clinical practice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.