Determinants of post-intensive care mortality in high-level treated critically ill patients.
OBJECTIVE
To assess the predictive ability of preillness and illness variables, impact of care, and discharge variables on the post-intensive care mortality.


METHODS
5,805 patients treated with high intensity of care in 89 ICUs in 12 European countries (EURICUS-I study) surviving ICU stay.


METHODS
Case-mix was split in training sample (logistic regression model for post-ICU mortality: discrimination assessed by area under ROC curve) and in testing sample. Time to death was studied by Cox regression model validated with bootstrap sampling on the unsplit case-mix.


RESULTS
There were 5,805 high-intensity patients discharged to ward and 423 who died in hospital. Significant odds ratios were observed for source of admission, medical/surgical unscheduled admission, each year age, each SAPSII point, each consecutive day in high-intensity treatment, and each NEMS point on the last ICU day. Time to death in ward was significantly shortened by different source of admission; age over 78 years, medical/unscheduled surgical admission; SAPSII score without age, comorbidity and type of admission over 16 points; more than 2 days in high-intensity treatment; all days spent in high treatment; respiratory, cardiovascular, and renal support at discharge; and last ICU day NEMS higher than 27 points


CONCLUSIONS
Worse outcome is associated with the physiological reserve before admission in the ICU, type of illness, intensity of care required, and the clinical stability and/or the grade of nursing dependence at discharge.
Iapichino
Gaetano
G
Istituto di Anestesiologia e Rianimazione, Università di Milano, Azienda Ospedaliera-Polo Universitario San Paolo, via A. Di Rudinì 8, 20142 Milan, Italy. g.iapichino@unimi.it
Morabito
Alberto
A
Mistraletti
Giovanni
G
Ferla
Luca
L
Radrizzani
Danilo
D
Reis Miranda
Dinis
D
D000368:Aged; D003422:Critical Care; D016638:Critical Illness / Q000401:mortality* / Q000628:therapy*; D006801:Humans; D008875:Middle Aged; D016016:Proportional Hazards Models