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Updated: Feb 13, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Development of neuropsychological evaluation screening tool: An education-free cognitive screening instrument
Sakshi Chopra1, Harsimarpreet Kaur1, Ravindra M Pandey1
1Department of Clinical Neuropsychology, All India Institute of Medical Sciences, New Delhi, India.
Background:
Due to the paucity of quick, cognitive screening tools available in India that are independent of cultural and educational influences, a 6-item paper and pencil test, covering areas of memory, executive functioning, attention, and visuospatial ability domains - the Neuropsychological Evaluation Screening Tool (NEST) was developed.
Aim And Method:
NEST was administered to 84 healthy controls to analyze, revise, and review items. In the second phase, 408 patients, above 16 years of age, with their educational level ranging from being illiterate to having greater than 25 years of education, with various neurological and psychiatric conditions were independently administered NEST, Hindi Mental State Examination (HMSE), and a detailed cognitive evaluation using PGI Memory Scale (PGIMS).
Results:
Using receiver operating characteristics analysis for 341 patients, ≥3 was identified as the optimum cut-off for NEST. NEST could correctly classify 87.9% of the patients with an impaired vs. an intact cognition. The diagnostic characteristics of NEST with PGIMS were sensitivity (95% CI): 94.78% (91.1, 97.3); specificity (95% CI): 60.31% (51.3, 68.7); positive predictive value (95% CI): 80.74% (78.1, 93.0); and negative predictive value (95% CI): 86.81% (75.6, 85.3). NEST had an 82.5% agreement (95% CI: 78.1, 86.2) with PGIMS. On the other hand, the diagnostic characteristics of HMSE with PGIMS were sensitivity (95% CI): 73.79% (67.5, 79.3); specificity (95% CI): 82.44% (74.8, 88.5); positive predictive value (95% CI): 88.02% (82.5, 92.2); and negative predictive value (95% CI): 64.3% (56.5, 71.5). HMSE had a 76.95% (95% CI: 72.2, 81.1) agreement with PGIMS.
Conclusions:
NEST has better sensitivity compared to HMSE for detecting cognitive impairment when compared to a detailed evaluation at all educational levels.
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