AIMS: The purpose of the study was to assess the profile of adult patients with congenital heart disease who reported a good, moderate, or poor quality of life. METHODS: We conducted a secondary analysis of data from a large-scale quality-of-life study that included 627 patients. Demographic and clinical variables were retrieved from the medical records and functional status from patient interviews. Overall quality of life was measured using a Linear Analogue Scale. Using K-means cluster analysis, we categorized subjects into a 3-cluster solution: good, moderate, or poor quality of life. RESULTS: Four hundred ninety patients (78.1%) clustered into the good quality-of-life category; 126 patients (20.1%) clustered into the moderate quality-of-life category; and 11 patients (1.8%) clustered into the poor quality-of-life category. Poorer quality of life was associated with lower educational level, unemployment or disability, associated syndromes, instability of the heart disease, and a poorer functional status. CONCLUSION: Over three-quarters of the patients had a good quality of life, whereas only a small proportion had a poor quality of life. Specific demographic and clinical characteristics associated with a poor quality of life could assists in identifying patients at risk for developing a poor quality of life.
AIMS: The purpose of the study was to assess the profile of adult patients with congenital heart disease who reported a good, moderate, or poor quality of life. METHODS: We conducted a secondary analysis of data from a large-scale quality-of-life study that included 627 patients. Demographic and clinical variables were retrieved from the medical records and functional status from patient interviews. Overall quality of life was measured using a Linear Analogue Scale. Using K-means cluster analysis, we categorized subjects into a 3-cluster solution: good, moderate, or poor quality of life. RESULTS: Four hundred ninety patients (78.1%) clustered into the good quality-of-life category; 126 patients (20.1%) clustered into the moderate quality-of-life category; and 11 patients (1.8%) clustered into the poor quality-of-life category. Poorer quality of life was associated with lower educational level, unemployment or disability, associated syndromes, instability of the heart disease, and a poorer functional status. CONCLUSION: Over three-quarters of the patients had a good quality of life, whereas only a small proportion had a poor quality of life. Specific demographic and clinical characteristics associated with a poor quality of life could assists in identifying patients at risk for developing a poor quality of life.
Authors: Matthäus Vigl; Eva Niggemeyer; Alfred Hager; Gerda Schwedler; Siegfried Kropf; Ulrike Bauer Journal: Qual Life Res Date: 2010-11-02 Impact factor: 4.147
Authors: Flávio Miguel Teixeira; Rosália Maria Coelho; Cidália Proença; Ana Margarida Silva; Daniela Vieira; Cláudia Vaz; Cláudia Moura; Victor Viana; José Carlos Areias; Maria Emília Guimarães Areias Journal: Pediatr Cardiol Date: 2011-06-28 Impact factor: 1.655
Authors: Maria Emília Guimarães Areias; Catarina I Pinto; Patrícia F Vieira; Flávio Teixeira; Rosália Coelho; Isabela Freitas; Samantha Matos; Marta Castro; Sofia Sarmento; Victor Viana; Jorge Quintas; José C Areias Journal: Transl Pediatr Date: 2013-07
Authors: Edward Callus; Silvana Pagliuca; Sara Boveri; Federico Ambrogi; Koen Luyckx; Adrienne H Kovacs; Silke Apers; Werner Budts; Junko Enomoto; Maayke A Sluman; Jou-Kou Wang; Jamie L Jackson; Paul Khairy; Stephen C Cook; Shanthi Chidambarathanu; Luis Alday; Katrine Eriksen; Mikael Dellborg; Malin Berghammer; Bengt Johansson; Andrew S Mackie; Samuel Menahem; Maryanne Caruana; Gruschen Veldtman; Alexandra Soufi; Susan M Fernandes; Kamila White; Shelby Kutty; Philip Moons Journal: Health Qual Life Outcomes Date: 2021-02-10 Impact factor: 3.186