### Description

Patients discharged from the intensive care unit (ICU) can have a high early after-discharge mortality (EADM). Latour et al developed an equation which can be used to identify a group of patients at high risk (21-46%) for early death after discharge from the ICU. The authors are from several hospitals in Spain.

Population: 700 patients older than 14 years discharged from ICUs at 3 hospitals in Valencia, Spain, during the period of January 1986 to May 1987.

Parameters found predictive of outcome:

(1) age

(2) days in the ICU

(3) number of organ system failures

(4) SAPS score in the first hour after admission to the ICU

 Parameter beta Finding Value age -0.633 <= 65 - 1 >= 66 + 1 days in ICU -0.415 <= 9 - 1 >= 10 + 1 organ system failure (OSF) -0.423 0 - 1 >= 1 + 1 SAPS -0.822 <= 10 - 1 >= 11 + 1

X =

= 2.08 - (0.822 * (SAPS value)) - (0.423 * (organ system failure value)) - (0.415 * (days in ICU value)) - (0.633 * (age value))

probability of early death within 2 months after discharge from the ICU =

= 1 / (1 + EXP(X))

Interpretation:

• The minimum mortality rate is about 1% with all favorable parameters.

• The maximum mortality rate is about 56% with all unfavorable parameters.

• The authors found that the equation was not suitable to make predictions in the individual patient since the variables had a low predictive value. However, it did allow identification of a high risk group of patients who might benefit from more intensive care.

• Patients with an initial SAPs score >= 11 had a 6-fold greater risk of dying in the immediate post-ICU period than those with a score <= 10.

NOTE: On page 126, ln (p / (1 - p)) = X. If this is rearranged, p = 1 / (1 + EXP(-X)), not 1 / (1 + EXP(X)) as given. Since (1 / (1 + EXP(-X))) + (1 / (1 + EXP(X))) = 1, one value is the probability of death and the other is the probability of survival. I have elected to go with the example given at the bottom of the page.