Predictors of Overtreatment

Uses

How it works

Risks & contraindications

Other

Highlighted claims

• The top three predictors in the gradient boosting model were blood glucose test strip use, diabetes duration and medication count in the prior 180 days. — Estimating prevalence and predictors of glucose-lowering overtreatment among older adults with type 2 diabetes in long-term care and community settings: a machine learning–based cohort study
• Potential intervention targets included frequent monitoring, polypharmacy, longer diabetes duration, prior hypoglycaemia, retinopathy and endocrinology involvement. — Estimating prevalence and predictors of glucose-lowering overtreatment among older adults with type 2 diabetes in long-term care and community settings: a machine learning–based cohort study
• Chronic hypoglycaemia, retinopathy and endocrinology involvement highlighted the challenge of balancing disease management and safety in complex cases. — Estimating prevalence and predictors of glucose-lowering overtreatment among older adults with type 2 diabetes in long-term care and community settings: a machine learning–based cohort study
• Blood glucose test strip use likely reflected higher-intensity glucose monitoring. — Estimating prevalence and predictors of glucose-lowering overtreatment among older adults with type 2 diabetes in long-term care and community settings: a machine learning–based cohort study
• Polypharmacy may indicate greater clinical complexity and higher adverse-event risk in older adults. — Estimating prevalence and predictors of glucose-lowering overtreatment among older adults with type 2 diabetes in long-term care and community settings: a machine learning–based cohort study