PT  - JOURNAL ARTICLE
AU  - M R Cowie
AU  - D A Wood
AU  - A J S Coats
AU  - S G Thompson
AU  - V Suresh
AU  - P A Poole-Wilson
AU  - G C Sutton
TI  - Survival of patients with a new diagnosis of heart failure: a population based study
AID  - 10.1136/heart.83.5.505
DP  - 2000 May 01
TA  - Heart
PG  - 505--510
VI  - 83
IP  - 5
4099  - http://heart.bmj.com/content/83/5/505.short
4100  - http://heart.bmj.com/content/83/5/505.full
SO  - Heart2000 May 01; 83
AB  - OBJECTIVE To describe the survival of a population based cohort of patients with incident (new) heart failure and the clinical features associated with mortality.DESIGN A population based observational study.SETTING Population of 151 000 served by 82 general practitioners in west London.PATIENTS New cases of heart failure were identified by daily surveillance of acute hospital admissions to the local district general hospital, and by general practitioner referral of all suspected new cases of heart failure to a rapid access clinic.INTERVENTIONS All patients with suspected heart failure underwent clinical assessment, and chest radiography, ECG, and echocardiogram were performed. A panel of three cardiologists reviewed all the data and determined whether the definition of heart failure had been met. Patients were subsequently managed by the general practitioner in consultation with the local cardiologist or admitting physician.MAIN OUTCOME MEASURES Death, overall and from cardiovascular causes.RESULTS There were 90 deaths (83 cardiovascular deaths) in the cohort of 220 patients with incident heart failure over a median follow up of 16 months. Survival was 81% at one month, 75% at three months, 70% at six months, 62% at 12 months, and 57% at 18 months. Lower systolic blood pressure, higher serum creatinine concentration, and greater extent of crackles on auscultation of the lungs were independently predictive of cardiovascular mortality (all p < 0.001).CONCLUSIONS In patients with new heart failure, mortality is high in the first few weeks after diagnosis. Simple clinical features can identify a group of patients at especially high risk of death.