Cormac McCarthy1, Borislav D Dimitrov2, Imran J Meurling3, Cedric Gunaratnam3, Noel G McElvaney3. 1. Respiratory Research Division, Royal College of Surgeons in Ireland, Dublin, Ireland; Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland. Electronic address: cmccarthy@rcsi.ie. 2. Department of Medicine, and Department of General Practice, Royal College of Surgeons in Ireland, Dublin, Ireland; Academic Unit of Primary Care and Population Sciences, University of Southampton, Southampton, England. 3. Respiratory Research Division, Royal College of Surgeons in Ireland, Dublin, Ireland; Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland.
Abstract
BACKGROUND: Determining prognosis and predicting outcomes in cystic fibrosis (CF) is a complex issue, and there have been very few clinically applicable models for this. The aim was to create a simple, practical outcome prediction tool for CF. METHODS: Forty-nine consecutive patients with CF from a single center were studied over an 84-month period (2004-2010). All baseline clinical parameters were gathered, and FEV₁ measurements were analyzed over the study period. Using patterns of FEV₁ decline, a tipping point of 52.8% predicted was identified. Other clinical variables were analyzed and correlated with outcome. Poor outcome was defined as death or transplantation. Using age, BMI, lung function (ie, FEV₁), and number of exacerbations in the past 3 months, the CF-ABLE score was created. The score was validated for data from 370 patients from the national Cystic Fibrosis Registry of Ireland. RESULTS: The ABLE score uses clinical parameters that are measured at every clinic visit and scored on a scale from 0 to 7. If FEV₁ is < 52%, then 3.5 points are added; if the number of exacerbations in the past 3 months is > 1, then 1.5 points are added; if BMI is < 20.1 kg/m² or age < 24 years, each receive 1 point. CONCLUSIONS: Patients with a low score have a very low risk of death or lung transplantation within 4 years; however, as the score increases, the risk significantly increases. Patients who score > 5 points have a 26% risk of poor outcome within 4 years. This score is simple and applicable and better predicts outcome than FEV₁ alone.
BACKGROUND: Determining prognosis and predicting outcomes in cystic fibrosis (CF) is a complex issue, and there have been very few clinically applicable models for this. The aim was to create a simple, practical outcome prediction tool for CF. METHODS: Forty-nine consecutive patients with CF from a single center were studied over an 84-month period (2004-2010). All baseline clinical parameters were gathered, and FEV₁ measurements were analyzed over the study period. Using patterns of FEV₁ decline, a tipping point of 52.8% predicted was identified. Other clinical variables were analyzed and correlated with outcome. Poor outcome was defined as death or transplantation. Using age, BMI, lung function (ie, FEV₁), and number of exacerbations in the past 3 months, the CF-ABLE score was created. The score was validated for data from 370 patients from the national Cystic Fibrosis Registry of Ireland. RESULTS: The ABLE score uses clinical parameters that are measured at every clinic visit and scored on a scale from 0 to 7. If FEV₁ is < 52%, then 3.5 points are added; if the number of exacerbations in the past 3 months is > 1, then 1.5 points are added; if BMI is < 20.1 kg/m² or age < 24 years, each receive 1 point. CONCLUSIONS:Patients with a low score have a very low risk of death or lung transplantation within 4 years; however, as the score increases, the risk significantly increases. Patients who score > 5 points have a 26% risk of poor outcome within 4 years. This score is simple and applicable and better predicts outcome than FEV₁ alone.
Authors: C McCarthy; O O'Carroll; M E O'Brien; T McEnery; A Franciosi; C Gunaratnam; N G McElvaney Journal: Ir J Med Sci Date: 2017-08-15 Impact factor: 1.568
Authors: Emer P Reeves; Cormac McCarthy; Oliver J McElvaney; Maya Sakthi N Vijayan; Michelle M White; Danielle M Dunlea; Kerstin Pohl; Noreen Lacey; Noel G McElvaney Journal: World J Crit Care Med Date: 2015-08-04
Authors: Daan Caudri; Lidija Turkovic; Nicholas H de Klerk; Tim Rosenow; Conor P Murray; Ewout W Steyerberg; Sarath C Ranganathan; Peter Sly; Stephen M Stick; Oded Breuer Journal: Pediatr Pulmonol Date: 2021-10-12
Authors: Lori J Silveira; Matthew Strand; Michael V Van Dyke; Margaret M Mroz; Anna V Faino; Dana M Dabelea; Lisa A Maier; Tasha E Fingerlin Journal: PLoS One Date: 2017-11-16 Impact factor: 3.240