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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Screening of cognitive impairment in chronic obstructive pulmonary disease
Raffaele Antonelli-Incalzi1, Andrea Corsonello, Luigi Trojano
1Department of Geriatric Medicine, University Campus Bio-Medico, Rome, Italy.
Abstract:
Cognitive dysfunction is common and clinically important in severe chronic obstructive pulmonary disease (COPD). We investigated the diagnostic accuracy of the Mini Mental State Examination (MMSE) and Instrumental Activities of Daily Living (IADL) scale in screening severe cognitive dysfunction in 149 patients with COPD, mean age 69.3+/-8.5 years, forced expiratory volume in 1 s=36.6+/-17.8% of the predicted. Patients underwent the MMSE and an in-depth neuropsychological assessment based upon the Mental Deterioration Battery (MDB). The 5-item IADL scale was assessed. The sample was randomly divided into a training (n=73) and a testing (n=76) population. The diagnostic accuracy of MMSE, IADL scale or both versus cognitive dysfunction corresponding to abnormal performance in 3 or more MDB tests was assessed in the training population and the model obtained was tested in the testing population. The combination of MMSE<24 and dependence in at least 1 IADL had better diagnostic accuracy than either MMSE or IADL, with sensitivity=52.4, specificity=82.7, positive predictive value=55.0% and negative predictive value=81.1% in the testing population. MMSE and the 5-item IADL scale can be used to exclude, but not to detect cognitive dysfunction in COPD patients. A confirmatory cognitive test should be administered to patients with an MMSE score of <24 and who are dependent in at least 1 IADL.
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