The Diabetic Cognitive Impairment Score for Early Screening of Cognitive Impairment in Type 2 Diabetes Patients

TL;DR

This study develops a score to screen for cognitive impairment in Type 2 diabetes patients using a biomarker and clinical factors.

Contribution

The study introduces a new score (DCIS) combining P-tau181 levels and clinical factors for early detection of cognitive impairment in T2D.

Findings

Higher P-tau181 levels are independently associated with cognitive impairment in Type 2 diabetes patients.

The DCIS score achieved 79.5% accuracy in identifying cognitive impairment in the training cohort.

The score showed 77% accuracy in an external validation cohort.

Abstract

Purpose: Diabetes has been associated with an excess risk of cognitive impairment. The hyperphosphorylation of tau protein leads to neurodegeneration and is closely related to Type 2 diabetes (T2D). This study aimed to characterize the association between P-tau181 and diabetic cognitive impairment and to develop a nomogram-based score to screen cognitive impairment in T2D patients.

Methods: We used a cohort of 379 patients diagnosed with T2D as a training dataset to develop a predictive model. Risk factors associated with cognitive impairment were identified using stepwise multivariate logistic regressive analysis. A nomogram was established by incorporating these risk factors, and the diabetic cognitive impairment score (DCIS) was built and externally validated in another cohort.

Results: In the training cohort, patients with cognitive impairment had higher levels of P-tau181 (13.3 [10.5–18.7] vs. 10.0 [8.0–13.0], p < 0.001). P-tau181 was negatively correlated with MOCA (r = −0.308, p < 0.001) and MMSE (r = −0.289, p < 0.001), and it was independently associated with cognitive impairment in T2D patients (OR, 1.137 [95% CI, 1.080–1.198]; p < 0.001). Other independent risk factors of diabetic cognitive impairment included age, education level, and diabetic retinopathy. The DCIS was built by nomogram based on the four risk factors, which had an area under the receiver operating characteristic curve (AUC) of 0.795 (95% CI, 0.751–0.840). The optimal cut-off of DCIS for the diagnosis of cognitive impairment in T2D patients was 139.5, with a sensitivity of 72.9% and a specificity of 75.3%. In the validation cohort, the AUC of DCIS for screening diabetic cognitive impairment was 0.770 (95% CI, 0.716–0.824).

Conclusions: P-tau181 was independently associated with diabetic cognitive impairment. The DCIS, based on P-tau181, age, education level, and diabetic retinopathy, is effective to identify cognitive impairment in T2D patients.

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