DATA:
ICU
OBSERVATIONS: 200
VARIABLES: 21
VARIABLE DESCRIPTION:
ID
ID number of the patient
STA
Vital status
0 = Lived
1 = Died
AGE
Patient's age in years
SEX
Patient's sex
0 = Male
1 = Female
RACE
Patient's race
1 = White
2 = Black
3 = Other
SER
Service at ICU admission
0 = Medical
1 = Surgical
CAN
Is cancer part of the present problem?
0 = No
1 = Yes
CRN
History of chronic renal failure
0 = No
1 = Yes
INF
Infection probable at ICU admission
0 = No
1 = Yes
CPR
CPR prior to ICU admission
0 = No
1 = Yes
SYS
Systolic blood pressure at ICU admission (in mm Hg)
HRA
Heart rate at ICU admission (beats/min)
PRE: Previous admission to an ICU within 6 months
0 = No
1 = Yes
TYP
Type of admission
0 = Elective
1 = Emergency
FRA
Long bone, multiple, neck, single area, or hip fracture
0 = No
1 = Yes
PO2
PO2 from initial blood gases
0 = PO2 > 60
1 = PO2  60
PH
PH from initial blood gases
0 = PH  7.25
1 = PH < 7.25
PCO
PCO2 from initial blood gases
0 = PCO2  45
1 = PCO2 > 45
BIC
Bicarbonate from initial blood gases
0 = Bicarb  18
1 = Bicarb < 18
CRE
Creatinine from initial blood gases
0 = Creatin  2.0
1 = Creatin > 2.0
LOC
Level of consciousness at admission
0 = no coma or stupor
1 = deep stupor
2 = coma
DESCRIPTIVE ABSTRACT:
The ICU data set consists of a sample of 200 subjects who were part of
a much larger study on survival of patients following admission to an adult
intensive care unit (ICU). The major goal of this study was to develop a
logistic regression model to predict the probability of survival to hospital
discharge of these patients and to study the risk factors associated with
ICU mortality (Vital status variable).
SOURCES:
Data were collected at Baystate Medical Center in Springfield, Massachusetts.
REFERENCES:
1. Hosmer and Lemeshow, Applied Logistic Regression, Wiley, (1989), Appendix 2.
2.
Lemeshow, S., Teres, D., Avrunin, J. S., Pastides, H. (1988). Predicting
the Outcome of Intensive Care Unit Patients. Journal of the American
Statistical Association, 83, 348-356.
WEBSITE:
http://lib.stat.cmu.edu/DASL/