Risk prediction models for malnutrition in dialysis patients in China: a systematic review and meta-analysis.
Mengyao Liu, Yan Wu, Fen Ye et al.
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In 30 seconds
This systematic review and meta-analysis evaluated risk prediction models for malnutrition in dialysis patients in China. The analysis included 12 studies, revealing a pooled prevalence of malnutrition at 41%. The nine internally validated models showed a pooled effect of 0.83, indicating good discriminatory performance, despite high risk of bias in all models.
Key findings
- The pooled prevalence of malnutrition in dialysis patients was 41%.
- Age, serum calcium, Kt/V, triglycerides, sex, vitamin D, NT-proBNP, and comorbid diabetes were identified as significant predictors.
- The pooled effect of the nine internal validated models was 0.83, indicating good discriminatory performance.
- All included models were rated at high risk of bias due to poor data sources and reporting.
Why it matters
Understanding the prevalence and predictors of malnutrition in dialysis patients is crucial for clinicians to identify at-risk individuals and implement timely interventions, potentially improving patient outcomes.
What to keep in mind
All included models were rated at high risk of bias, primarily due to inappropriate data sources and poor reporting of the analysis.