A prognostic model for one-year mortality in patients requiring prolonged mechanical ventilation.
OBJECTIVE
A measure that identifies patients who are at high risk of mortality after prolonged ventilation will help physicians communicate prognoses to patients or surrogate decision makers. Our objective was to develop and validate a prognostic model for 1-yr mortality in patients ventilated for 21 days or more.


METHODS
The authors conducted a prospective cohort study.


METHODS
The study took place at a university-based tertiary care hospital.


METHODS
Three hundred consecutive medical, surgical, and trauma patients requiring mechanical ventilation for at least 21 days were prospectively enrolled.


RESULTS
Predictive variables were measured on day 21 of ventilation for the first 200 patients and entered into logistic regression models with 1-yr and 3-mo mortality as outcomes. Final models were validated using data from 100 subsequent patients. One-year mortality was 51% in the development set and 58% in the validation set. Independent predictors of mortality included requirement for vasopressors, hemodialysis, platelet count < or = 150 x 10(9)/L, and age > or = 50 yrs. Areas under the receiver operating characteristic curve for the development model and validation model were .82 (SE .03) and .82 (SE .05), respectively. The model had sensitivity of .42 (SE .12) and specificity of .99 (SE .01) for identifying patients who had > or = 90% risk of death at 1 yr. Observed mortality was highly consistent with both 3- and 12-mo predicted mortality. These four predictive variables can be used in a simple prognostic score that clearly identifies low-risk patients (no risk factors, 15% mortality) and high-risk patients (three or four risk factors, 97% mortality).


CONCLUSIONS
Simple clinical variables measured on day 21 of mechanical ventilation can identify patients at highest and lowest risk of death from prolonged ventilation.
Carson
Shannon S
SS
Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA. scarson@med.unc.edu
Garrett
Joanne
J
Hanson
Laura C
LC
Lanier
Joyce
J
Govert
Joe
J
Brake
Mary C
MC
Landucci
Dante L
DL
Cox
Christopher E
CE
Carey
Timothy S
TS
D000328:Adult; D000368:Aged; D016638:Critical Illness / Q000401:mortality*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D012121:Respiration, Artificial; D018570:Risk Assessment; D012720:Severity of Illness Index