1. Evaluation of a multimodal diagnostic algorithm for prediction of cognitive impairment in elderly patients with dizziness.
- Author
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Felfela, K., Jooshani, N., Möhwald, K., Huppert, D., Becker-Bense, S., Schöberl, F., Schniepp, R., Filippopulos, F., Dieterich, M., Wuehr, M., and Zwergal, A.
- Subjects
OLDER patients ,COGNITION disorders ,DIZZINESS ,CEREBRAL atrophy ,NEUROPSYCHOLOGICAL tests - Abstract
Background: The current diagnostic workup for chronic dizziness in elderly patients often neglects neuropsychological assessment, thus missing a relevant proportion of patients, who perceive dizziness as a subjective chief complaint of a concomitant cognitive impairment. This study aimed to establish risk prediction models for cognitive impairment in chronic dizzy patients based on data sources routinely collected in a dizziness center. Methods: One hundred patients (age: 74.7 ± 7.1 years, 41.0% women) with chronic dizziness were prospectively characterized by (1) neuro-otological testing, (2) quantitative gait assessment, (3) graduation of focal brain atrophy and white matter lesion load, and (4) cognitive screening (MoCA). A linear regression model was trained to predict patients' total MoCA score based on 16 clinical features derived from demographics, vestibular testing, gait analysis, and imaging scales. Additionally, we trained a binary logistic regression model on the same data sources to identify those patients with a cognitive impairment (i.e., MoCA < 25). Results: The linear regression model explained almost half of the variance of patients' total MoCA score (R
2 = 0.49; mean absolute error: 1.7). The most important risk-predictors of cognitive impairment were age (β = − 0.75), pathological Romberg's sign (β = − 1.05), normal caloric test results (β = − 0.8), slower timed-up-and-go test (β = − 0.67), frontal (β = − 0.6) and temporal (β = − 0.54) brain atrophy. The binary classification yielded an area under the curve of 0.84 (95% CI 0.70–0.98) in distinguishing between cognitively normal and impaired patients. Conclusions: The need for cognitive testing in patients with chronic dizziness can be efficiently approximated by available data sources from routine diagnostic workup in a dizziness center. [ABSTRACT FROM AUTHOR]- Published
- 2024
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