such as "Introduction", "Conclusion"..etc
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 appearing in an upcoming issue of the (CJASN). This
clinical tool could help medical professionals initiate discussions
with patients and their families about end-of-life care such as hospice.
Some kidney disease patients on dialysis are very ill and long-term
survival is not anticipated. Because dialysis can be tedious and cause
medical complications, patients who know that they likely have only a
short time to live may wish to consider alternatives such as stopping
dialysis. Unfortunately, doctors have not had accurate ways to predict
dialysis patients' likelihood of long-term survival.
Michael Germain, MD; Lewis Cohen, MD (Baystate Medical Center); and
their colleagues designed a model to help physicians assess the
likelihood of long-term survival for these very ill patients. The
investigators derived their model after studying 512 kidney disease
patients on dialysis. One major component of the model is a doctor's
estimate of prognosis, called the "surprise question." (Would you be
surprised if your patient died in the next six months?) The model also
takes into consideration a patient's nutritional status, age, and
additional illnesses or conditions.
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%).
Discussing a kidney disease patient's likelihood of dying can help
seriously ill patients and their families make informed clinical
decisions: some will decide to stop dialysis and start hospice care,
while others may prefer continuing vigorous treatments to prolong life
as long as possible. "Terminal care is complicated and it is always
preferable if decisions can be discussed in advance, goals established,
and decisions reached collaboratively between patient and physician,"
said Dr. Germain.
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