The Seattle Heart Failure Model: prediction of survival in heart failure.
BACKGROUND
Heart failure has an annual mortality rate ranging from 5% to 75%. The purpose of the study was to develop and validate a multivariate risk model to predict 1-, 2-, and 3-year survival in heart failure patients with the use of easily obtainable characteristics relating to clinical status, therapy (pharmacological as well as devices), and laboratory parameters.


RESULTS
The Seattle Heart Failure Model was derived in a cohort of 1125 heart failure patients with the use of a multivariate Cox model. For medications and devices not available in the derivation database, hazard ratios were estimated from published literature. The model was prospectively validated in 5 additional cohorts totaling 9942 heart failure patients and 17,307 person-years of follow-up. The accuracy of the model was excellent, with predicted versus actual 1-year survival rates of 73.4% versus 74.3% in the derivation cohort and 90.5% versus 88.5%, 86.5% versus 86.5%, 83.8% versus 83.3%, 90.9% versus 91.0%, and 89.6% versus 86.7% in the 5 validation cohorts. For the lowest score, the 2-year survival was 92.8% compared with 88.7%, 77.8%, 58.1%, 29.5%, and 10.8% for scores of 0, 1, 2, 3, and 4, respectively. The overall receiver operating characteristic area under the curve was 0.729 (95% CI, 0.714 to 0.744). The model also allowed estimation of the benefit of adding medications or devices to an individual patient's therapeutic regimen.


CONCLUSIONS
The Seattle Heart Failure Model provides an accurate estimate of 1-, 2-, and 3-year survival with the use of easily obtained clinical, pharmacological, device, and laboratory characteristics.
Levy
Wayne C
WC
University of Washington, Seattle, WA 98177, USA. levywc@u.washington.edu
Mozaffarian
Dariush
D
Linker
David T
DT
Sutradhar
Santosh C
SC
Anker
Stefan D
SD
Cropp
Anne B
AB
Anand
Inder
I
Maggioni
Aldo
A
Burton
Paul
P
Sullivan
Mark D
MD
Pitt
Bertram
B
Poole-Wilson
Philip A
PA
Mann
Douglas L
DL
Packer
Milton
M
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D002304:Cardiac Pacing, Artificial / Q000706:statistics & numerical data; D002317:Cardiovascular Agents / Q000627:therapeutic use; D015331:Cohort Studies; D003131:Combined Modality Therapy; D015897:Comorbidity; D017147:Defibrillators, Implantable / Q000706:statistics & numerical data; D004232:Diuretics / Q000009:adverse effects / Q000627:therapeutic use; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D006333:Heart Failure / Q000188:drug therapy / Q000209:etiology / Q000401:mortality* / Q000601:surgery; D006353:Heart-Assist Devices / Q000706:statistics & numerical data; D006454:Hemoglobins / Q000032:analysis; D006801:Humans; D008017:Life Expectancy; D018655:Lymphocyte Count; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012372:ROC Curve; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D016019:Survival Analysis; D015996:Survival Rate; D016896:Treatment Outcome; D018487:Ventricular Dysfunction, Left / Q000150:complications / Q000188:drug therapy / Q000601:surgery
D002317:Cardiovascular Agents; D004232:Diuretics; D006454:Hemoglobins