4.6 Article

Diagnostic Accuracy of the Chinese Version of the Trail-Making Test for Screening Cognitive Impairment

期刊

出版社

WILEY
DOI: 10.1111/jgs.15135

关键词

Trail-Making Test; clinical norms; vascular dementia; Alzheimer's disease

资金

  1. 111 Project [B08006]
  2. National Natural Science Foundation of China [81473518, 81573824]
  3. Capital Health Research and Development of Special [SF2014-1-4191, SF2016-4-4193]
  4. Beijing Municipal Science and Technology Commission Foundation, China [Z141107002515019, Z151100003815021]

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Background/ObjectivesThe Trail-Making Test (TMT), which is commonly used to measure executive function, consists of two components (TMT-A and TMTB). There is a lack of normative TMT data for Chinese elderly adults. This study aimed to evaluate the validity of the TMT in screening for cognitive impairment. Design2,294 Chinese-speaking adults aged 50 to 85: 1,026 with normal cognition (NC), 462 with mild cognitive impairment (MCI), 108 with Alzheimer's disease (AD), 113 with vascular mild cognitive impairment (VaMCI), 121 with vascular dementia (VaD), 282 with uncertain types of dementia, and 15 with mixed dementia. Receiver operating characteristic curve analysis was performed to test the ability of TMT scores to differentiate between NC and cognitive impairment. ResultsAge, education, and sex were significantly associated with TMT completion time. The TMT-A exhibited sensitivity of 77.8% and specificity of 92.0% with cut-off value of 98.5seconds for discriminating AD from NC. The TMT-B had sensitivity of 83.3% and specificity of 91.8% with a cut-off value of 188.5seconds for discriminating AD from NC. The TMT-A had sensitivity of 85.7% and specificity of 81.6% for discriminating NC from VaD with a cut-off value of 77.5seconds, and the TMT-s had sensitivity of 81.6% and specificity of 83.9% with a cut-off value of 147.5seconds. The TMT had less sensitivity distinguishing MCI from NC. ConclusionThe Chinese version of the TMT is reliable for detecting AD or VaD but poor at distinguishing MCI from NC.

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