Diagnostic accuracy of digital clock drawing test for Alzheimer disease and mild cognitive impairment

Alzheimer’s disease (AD) and mild cognitive impairment (MCI) are major public health concerns, requiring accurate and scalable diagnostic tools. The digital clock drawing test (dCDT) captures drawing data and enables extraction of process-related features that may improve diagnostic performance. However, existing evidence remains inconsistent, highlighting the need for a systematic synthesis to support its clinical translation. We searched Web of Science, Embase, PubMed, PsycINFO, IEEE Xplore, CNKI, and Wanfang from inception to January 8, 2026. A bivariate mixed-effects model was used to pool sensitivity and specificity. A total of 13 studies comprising 17 diagnostic tests were included, and risk of bias was notable across studies. For MCI, the standalone dCDT showed pooled sensitivity of 0.765 (95% CI: 0.683–0.832), specificity of 0.752 (95% CI: 0.673–0.817), and pooled area under the summary receiver operating characteristic curve (AUC) of 0.825 (95% CI: 0.790–0.856). When both standalone and augmented dCDT tests were considered for MCI, the pooled sensitivity and specificity were 0.760 and 0.800, respectively, and the pooled AUC increased to 0.845. For AD, the pooled sensitivity, specificity, and AUC of dCDT were 0.820 (95% CI: 0.721–0.889), 0.897 (95% CI: 0.860–0.923), and 0.928 (95% CI: 0.902–0.948), respectively. Exploratory subgroup analyses of standalone dCDT for MCI suggested diagnostic performance appeared higher in studies employing algorithm-based approaches than in those using traditional-scoring approaches. Overall, the available evidence supports dCDT as a promising digital screening tool for cognitive impairment. Further multicenter studies and standardized protocols are needed to enhance its role in early diagnostic and clinical practice.