A new model can help physicians determine if a kidney disease patient on dialysis is likely to die within the next few months, according to a study just mentioned in (CJASN). This clinical tool could help medical professionals initiate discussions with patients about end of life care. Five simple factors: a 'no' answer to the surprise question, older age, decreased serum albumin, presence of dementia, and presence of peripheral vascular disease (blockage of an artery that leads to an arm or a leg), could be mathematically combined to accurately predict that a patient is unlikely to survive past six months. When comparing a patient who died within six months with one who remained alive, 87% of the time the model accurately predicted that the former patient had a higher risk of dying within that timeframe than the latter. The researchers validated their model by testing its accuracy in another 514 kidney disease patients on dialysis, where the model's predictive accuracy was only slightly lower (80%).
This is fascinating and hopefully we can have this tool available to be used in clinical practice. Nutrition has again and again shown to be an important predicting variable for survival on dialysis.