Glycaemic-Cognitive Association

Uses

How it works

Benefits

Evidence quality

Where it comes from

Highlighted claims

• The Spearman test found a statistically significant positive association between glycaemic control and cognitive function. — A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing
• The Kruskal-Wallis test did not find significant differences in glycaemic control across cognitive groups. — A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing
• Better glycaemic control co-occurred with higher cognitive function scores. — A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing
• Stage 3 tested whether glycaemic control related to cognitive group status and cognitive function in the Ohio cognitive dataset. — A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing
• The significant continuous association was not treated as causal evidence of cognitive decline. — A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing
• The Type 3 diabetes result motivates longitudinal modelling of metabolic control and cognitive trajectories. — A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing