Performance characteristics and diagnostic efficacy of the digital clock drawing test in patients with amnestic mild cognitive impairment
10.3760/cma.j.cn371468-20210607-00313
- VernacularTitle:遗忘型轻度认知障碍患者数字化画钟测验的表现特征及诊断效能研究
- Author:
Xiaonan ZHANG
1
;
Yarong ZHAO
;
Liangliang LYU
;
Guowen MIN
;
Qiuyan WANG
;
Yang LI
Author Information
1. 山西医科大学第一临床医学院，太原 030001
- Keywords:
Mild cognitive impairment;
Clock drawing test;
Neuropsychological test;
Diagnostic effectiveness;
Digital evaluation
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2021;30(9):794-799
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the performance characteristics of the digital clock-drawing test(dCDT) for amnestic mild cognitive impairment(aMCI), and its diagnostic value for aMCI patients compared with the traditional clock-drawing test (tCDT).Methods:Total 81 middle-aged and elderly outpatients in Affiliated Hospital to Shanxi Medical University from November 2020 to May 2021 were selected, including 42 cognitively normal people (control group) and 39 aMCI patients (aMCI group). The dCDT developed by our team was used to collect drawing process parameters (such as stroke length, time and speed). The Cognitive Domain Indexs of Montreal Cognitive Assessment (MoCA) were calculated using the CDIS scoring method, and the correlation between dCDT parameters and MoCA indexs were analyzed.Logistic regression analysis was used to construct the predictive model, and the sensitivity and specificity of different methods for the diagnosis of aMCI patients were compared by the area under the ROC curve.Results:(1) The total time(51.25(38.80, 63.75)s vs 42.42(33.64, 51.91)s) and time in air(36.34(26.81, 47.25)s vs 28.47(22.37, 33.98)s) of the aMCI group were significantly higher than those of the control group, and the minute hand/hour hand ratio(1.23±0.35 vs 1.39±0.34), strokes per minute((31.31±10.44) vs (41.05±9.48))and tCDT score(3.0(3.0, 4.0), 4.0(3.0, 4.0))were significantly lower than those of the control group, and the differences were statistically significant (all P<0.05). Other dCDT parameters were not statistically significant between the two groups ( Z=-1.835--0.440, P>0.05). (2) Correlation analysis showed that the total time was negatively correlated with MoCA MIS( r=-0.224, P=0.049), LIS( r=-0.237, P=0.037)and AIS( r=-0.236, P=0.038); time in air was negatively correlated with MoCA MIS( r=-0.268, P=0.018), LIS( r=-0.271, P=0.016), AIS( r=-0.259, P=0.022)and OISA( r=-0.267, P=0.018); the minute hand/hour hand ratio was positively correlated with MoCA EIS( r=0.259, P=0.022)and VIS( r=0.309, P=0.006); the strokes per minute was positively correlated with MoCA MIS( r=0.376, P=0.001), EIS( r=0.290, P=0.010), VIS( r=0.294, P=0.009), AIS( r=0.238, P=0.036)and OISA( r=0.301, P=0.007). (3)dCDT model composed of the pre-second hand latency, the ratio of minute hand/hour hand, and the strokes per minute can correctly classify 77.8% of aMCI, with a sensitivity of 74.36% and a specificity of 80.95%.Its diagnostic power for aMCI was significantly higher than the tCDT scoring( Z=2.335, P=0.02). Conclusion:The cognitive impairment in aMCI can be detected by dCDT, and different dCDT parameters can reflect the impairment of different cognitive domains.Compared with tCDT scoring, dCDT can improve the diagnostic efficacy of aMCI patients.
