Risk Prediction Model for Frailty in Older Chinese Patients With Type 2 Diabetes Mellitus: A Systematic Review.
Liu Hongyu, Liu Qilan, Zhang Shuqing et al.
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In 30 seconds
This systematic review evaluated frailty risk prediction models for older Chinese patients with type 2 diabetes. Fourteen studies were included, analyzing 25 models with incidence rates of frailty ranging from 10.1% to 51.2%. The models demonstrated good discriminative ability, with area under the curve (AUC) values between 0.703 and 0.975, although all studies exhibited a high risk of bias.
Key findings
- Frailty incidence rates in the studies ranged from 10.1% to 51.2%.
- The AUC of the models varied from 0.703 to 0.975, indicating good discriminative ability.
- Common predictors included age, polypharmacy, nutritional status, glycated hemoglobin, and ADL score.
- All studies showed good applicability but had a high risk of bias.
Why it matters
Understanding frailty risk in older patients with diabetes is crucial for developing targeted interventions. Accurate prediction models can help healthcare professionals identify at-risk individuals and implement timely management strategies.
What to keep in mind
The included studies exhibited a high risk of bias, which may affect the reliability of the findings.