Martin et al reported a model for predicting readmission of a surgical ICU patient. This can help to identify a patient who may benefit from more aggressive management. The authors are from University of Utah.
Patient selection: surgical ICU patient being discharged from the ICU
Parameters:
(1) respiratory rate in breaths per minute
(2) serum BUN in mg/dL
(3) age in years
(4) serum glucose in mg/dL
(5) serum chloride in mmol/L
(6) history of atrial fibrillation
(7) history of renal insufficiency
Parameter
Finding
Points
respiratory rate
0.04883 * (rate)
serum BUN
0.004967 * (BUN)
age in years
0.011588 * (age)
serum glucose
0.003519 * (glucose)
serum chloride
0.036104 * (chloride)
atrial fibrillation
no
0
yes
0.580153
renal insufficiency
no
0
yes
0.458202
value of X =
= SUM(points for all of the parameters) - 9.284491
probability of readmission =
= 1 / (1 + EXP((-1) * X))
Performance:
• The area under the ROC curve is 0.71.
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