Stéphane Jouneau1, Mallorie Kerjouan2, Chloé Rousseau3, Mathieu Lederlin4, Francisco Llamas-Guttierez5, Bertrand De Latour6, Stéphanie Guillot7, Laurent Vernhet8, Benoit Desrues9, Ronan Thibault10. 1. Department of Respiratory Medicine, Competence Centre for Rare Pulmonary Diseases, CHU Rennes, Univ Rennes, Rennes, France; IRSET, Research Institute for Environmental and Occupational Health UMR1085, Univ Rennes, Rennes, France. 2. Department of Respiratory Medicine, Competence Centre for Rare Pulmonary Diseases, CHU Rennes, Univ Rennes, Rennes, France. 3. Centre d'Investigation clinique, INSERM 1414, CHU Rennes, Rennes University Hospital, Rennes, France. 4. Department of Radiology, CHU Rennes, Rennes University Hospital, Rennes, France; LTSI, INSERM U1099, Rennes University Hospital, Rennes, France. 5. Department of Histopathology, CHU Rennes, Rennes University Hospital, Rennes, France. 6. Department of Thoracic Surgery, CHU Rennes, Rennes University Hospital, Rennes, France. 7. Department of Pulmonary Function Testing, CHU Rennes, Rennes University Hospital, Rennes, France. 8. IRSET, Research Institute for Environmental and Occupational Health UMR1085, Univ Rennes, Rennes, France. 9. Department of Respiratory Medicine, Competence Centre for Rare Pulmonary Diseases, CHU Rennes, Univ Rennes, Rennes, France; Chemistry, Oncogenesis and Stress Signalling, INSERM U1242, Centre Eugène Marquis, Rennes, France. 10. Unité de Nutrition, CHU Rennes, Rennes University Hospital, Rennes, France; INRA, INSERM, Univ Rennes, Nutrition Metabolisms and Cancer, NuMeCan, Rennes, France. Electronic address: ronan.thibault@chu-rennes.fr.
Abstract
OBJECTIVES: Little is known about the indicators to assess malnutrition in patients with idiopathic pulmonary fibrosis (IPF). This study aimed to determine the following: 1) the prevalence of malnutrition in IPF patients; 2) the nutritional indicators predictive of low fat-free mass (FFM) as measured by bioimpedance analysis; 3) the IPF patients' characteristics associated with low FFM. METHODS: The IPF patients were consecutively recruited in a referral center for rare pulmonary diseases. Malnutrition was defined as a fat-free mass index (FFMI) = FFM (kg) / (height [m]2) <17 (men) or <15 (women). Nutritional assessment included body mass index (BMI), mid-arm circumference (MAC), triceps skinfold thickness, analogue food intake scale, and serum albumin and transthyretin. The primary endpoint was FFMI. Area under the receiver operating characteristic curve (AUC) assessed low FFMI prediction from nutritional indicators. Multivariable logistic regression determined variables associated with low FFMI. RESULTS: Eighty-one patients were consecutively recruited. Low FFMI prevalence was 28% (23 of 81). BMI AUC was 0.91 (95% confidence interval [CI], 0.84‒0.97) and MAC AUC was 0.85 (0.76‒0.94). Multivariable analysis associated BMI (odds ratio [OR] 0.26 [95% CI, 0.12-0.54], P = 0.0003), male sex (OR 0.02 [0.00-0.33], P = 0.005), and smoking (OR 0.10 [0.01-0.75], P = 0.024) with a lower risk of malnutrition. CONCLUSIONS: Malnutrition occurred in nearly one-third of IPF patients. Malnutrition screening should become systematic based on BMI and MAC, which are good clinical indicators of low FFMI. We propose a practical approach to screen malnutrition in IPF patients.
OBJECTIVES: Little is known about the indicators to assess malnutrition in patients with idiopathic pulmonary fibrosis (IPF). This study aimed to determine the following: 1) the prevalence of malnutrition in IPF patients; 2) the nutritional indicators predictive of low fat-free mass (FFM) as measured by bioimpedance analysis; 3) the IPF patients' characteristics associated with low FFM. METHODS: The IPF patients were consecutively recruited in a referral center for rare pulmonary diseases. Malnutrition was defined as a fat-free mass index (FFMI) = FFM (kg) / (height [m]2) <17 (men) or <15 (women). Nutritional assessment included body mass index (BMI), mid-arm circumference (MAC), triceps skinfold thickness, analogue food intake scale, and serum albumin and transthyretin. The primary endpoint was FFMI. Area under the receiver operating characteristic curve (AUC) assessed low FFMI prediction from nutritional indicators. Multivariable logistic regression determined variables associated with low FFMI. RESULTS: Eighty-one patients were consecutively recruited. Low FFMI prevalence was 28% (23 of 81). BMI AUC was 0.91 (95% confidence interval [CI], 0.84‒0.97) and MAC AUC was 0.85 (0.76‒0.94). Multivariable analysis associated BMI (odds ratio [OR] 0.26 [95% CI, 0.12-0.54], P = 0.0003), male sex (OR 0.02 [0.00-0.33], P = 0.005), and smoking (OR 0.10 [0.01-0.75], P = 0.024) with a lower risk of malnutrition. CONCLUSIONS:Malnutrition occurred in nearly one-third of IPF patients. Malnutrition screening should become systematic based on BMI and MAC, which are good clinical indicators of low FFMI. We propose a practical approach to screen malnutrition in IPF patients.
Authors: Paola Faverio; Alessia Fumagalli; Sara Conti; Fabiana Madotto; Francesco Bini; Sergio Harari; Michele Mondoni; Tiberio Oggionni; Emanuela Barisione; Paolo Ceruti; Maria Chiara Papetti; Bruno Dino Bodini; Antonella Caminati; Angela Valentino; Stefano Centanni; Donatella Noè; Matteo Della Zoppa; Silvia Crotti; Marco Grosso; Samir Giuseppe Sukkar; Denise Modina; Marco Andreoli; Roberta Nicali; Giulia Suigo; Federica De Giacomi; Sara Busnelli; Elena Cattaneo; Lorenzo Giovanni Mantovani; Giancarlo Cesana; Alberto Pesci; Fabrizio Luppi Journal: ERJ Open Res Date: 2022-03-07