OBJECTIVES: This study was designed to determine the relevance of a proposed classification for advanced heart failure (HF). Profiles based on clinical assessment of congestion and perfusion at the time of hospitalization were compared with subsequent outcomes. BACKGROUND: Optimal design of therapy and trials for advanced HF remains limited by the lack of simple clinical profiles to characterize patients. METHODS: Prospective analysis was performed for 452 patients admitted to the cardiomyopathy service at the Brigham and Women's Hospital with a diagnosis of HF. Patients were classified by clinical assessment into four profiles: profile A, patients with no evidence of congestion or hypoperfusion (dry-warm, n = 123); profile B, congestion with adequate perfusion (wet-warm, n = 222); profile C, congestion and hypoperfusion (wet-cold, n = 91); and profile L, hypoperfusion without congestion (dry-cold, n = 16). Other standard predictors of outcome were included and patients were followed for the end points of death (n = 117) and death or urgent transplantation (n = 137) at one year. RESULTS: Survival analysis showed that clinical profiles predict outcomes in HF. Profiles B and C increase the risk of death plus urgent transplantation by univariate (hazard ratio [HR] 1.83, p = 0.02) and multivariate analyses (HR 2.48, p = 0.003). Moreover, clinical profiles add prognostic information even when limited to patients with New York Heart Association (NYHA) class III/IV symptoms (profile B: HR 2.23, p = 0.026; profile C: HR 2.73, p = 0.009). CONCLUSIONS: Simple clinical assessment can be used to define profiles in patients admitted with HF. These profiles predict outcomes and may be used to guide therapy and identify populations for future investigation.
OBJECTIVES: This study was designed to determine the relevance of a proposed classification for advanced heart failure (HF). Profiles based on clinical assessment of congestion and perfusion at the time of hospitalization were compared with subsequent outcomes. BACKGROUND: Optimal design of therapy and trials for advanced HF remains limited by the lack of simple clinical profiles to characterize patients. METHODS: Prospective analysis was performed for 452 patients admitted to the cardiomyopathy service at the Brigham and Women's Hospital with a diagnosis of HF. Patients were classified by clinical assessment into four profiles: profile A, patients with no evidence of congestion or hypoperfusion (dry-warm, n = 123); profile B, congestion with adequate perfusion (wet-warm, n = 222); profile C, congestion and hypoperfusion (wet-cold, n = 91); and profile L, hypoperfusion without congestion (dry-cold, n = 16). Other standard predictors of outcome were included and patients were followed for the end points of death (n = 117) and death or urgent transplantation (n = 137) at one year. RESULTS: Survival analysis showed that clinical profiles predict outcomes in HF. Profiles B and C increase the risk of death plus urgent transplantation by univariate (hazard ratio [HR] 1.83, p = 0.02) and multivariate analyses (HR 2.48, p = 0.003). Moreover, clinical profiles add prognostic information even when limited to patients with New York Heart Association (NYHA) class III/IV symptoms (profile B: HR 2.23, p = 0.026; profile C: HR 2.73, p = 0.009). CONCLUSIONS: Simple clinical assessment can be used to define profiles in patients admitted with HF. These profiles predict outcomes and may be used to guide therapy and identify populations for future investigation.
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Authors: Mark H Drazner; Anne S Hellkamp; Carl V Leier; Monica R Shah; Leslie W Miller; Stuart D Russell; James B Young; Robert M Califf; Anju Nohria Journal: Circ Heart Fail Date: 2008-09 Impact factor: 8.790
Authors: Veli-Pekka Harjola; Wilfried Mullens; Marek Banaszewski; Johann Bauersachs; Hans-Peter Brunner-La Rocca; Ovidiu Chioncel; Sean P Collins; Wolfram Doehner; Gerasimos S Filippatos; Andreas J Flammer; Valentin Fuhrmann; Mitja Lainscak; Johan Lassus; Matthieu Legrand; Josep Masip; Christian Mueller; Zoltán Papp; John Parissis; Elke Platz; Alain Rudiger; Frank Ruschitzka; Andreas Schäfer; Petar M Seferovic; Hadi Skouri; Mehmet Birhan Yilmaz; Alexandre Mebazaa Journal: Eur J Heart Fail Date: 2017-05-30 Impact factor: 15.534
Authors: Behnam N Tehrani; Alexander G Truesdell; Mitchell A Psotka; Carolyn Rosner; Ramesh Singh; Shashank S Sinha; Abdulla A Damluji; Wayne B Batchelor Journal: JACC Heart Fail Date: 2020-11 Impact factor: 12.035
Authors: John R Teerlink; Marco Metra; Valerio Zacà; Hani N Sabbah; Gadi Cotter; Mihai Gheorghiade; Livio Dei Cas Journal: Heart Fail Rev Date: 2009-12 Impact factor: 4.214
Authors: Marco Metra; Eric Eichhorn; William T Abraham; Jennifer Linseman; Michael Böhm; Ramon Corbalan; David DeMets; Teresa De Marco; Uri Elkayam; Michael Gerber; Michel Komajda; Peter Liu; Vyacheslev Mareev; Sergio V Perrone; Philip Poole-Wilson; Ellen Roecker; Jennifer Stewart; Karl Swedberg; Michal Tendera; Brian Wiens; Michael R Bristow Journal: Eur Heart J Date: 2009-12 Impact factor: 29.983