A prediction rule to identify low-risk patients with heart failure.
OBJECTIVE
To derive a prediction rule using data available in the emergency department (ED) to identify a group of patients hospitalized for the treatment of heart failure who are at low risk of death and serious complications.


METHODS
The authors analyzed data for all 33,533 patients with a primary hospital discharge diagnosis of heart failure in 1999 who were admitted from EDs in Pennsylvania. Candidate predictors were demographic and medical history variables and the most abnormal examination or diagnostic test values measured in the ED (vital signs only) or on the first day of hospitalization. The authors constructed classification trees to identify a subgroup of patients with an observed rate of death or serious medical complications before discharge < 2%; the tree that identified the subgroup with the lowest rate of this outcome and an inpatient mortality rate < 1% was chosen.


RESULTS
Within the entire cohort, 4.5% of patients died and 6.8% survived to hospital discharge after experiencing a serious medical complication. The prediction rule used 21 prognostic factors to classify 17.2% of patients as low risk; 19 (0.3%) died and 59 (1.0%) survived to hospital discharge after experiencing a serious medical complication.


CONCLUSIONS
This clinical prediction rule identified a group of patients hospitalized from the ED for the treatment of heart failure who were at low risk of adverse inpatient outcomes. Model performance needs to be examined in a cohort of patients with an ED diagnosis of heart failure and treated as outpatients or hospitalized.
Auble
Thomas E
TE
Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Hsieh
Margaret
M
Gardner
William
W
Cooper
Gregory F
GF
Stone
Roslyn A
RA
McCausland
Julie B
JB
Yealy
Donald M
DM
D000368:Aged; D015331:Cohort Studies; D016001:Confidence Intervals; D003661:Decision Support Techniques; D004635:Emergency Medicine / Q000295:instrumentation* / Q000706:statistics & numerical data; D005260:Female; D006333:Heart Failure / Q000175:diagnosis*; D006801:Humans; D008297:Male; D010043:Outcome and Process Assessment, Health Care; D011379:Prognosis; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D016019:Survival Analysis