%0 Journal Article %T What are the best indicators to assess malnutrition in idiopathic pulmonary fibrosis patients? A cross-sectional study in a referral center %+ Institut de recherche en santé, environnement et travail (Irset) %+ CHU Pontchaillou [Rennes] %+ Centre d'Investigation Clinique [Rennes] (CIC) %+ Laboratoire Traitement du Signal et de l'Image (LTSI) %+ Chemistry, Oncogenesis, Stress and Signaling (COSS) %+ Nutrition, Métabolismes et Cancer (NuMeCan) %A Jouneau, Stéphane %A Kerjouan, Mallorie %A Rousseau, Chloé %A Lederlin, Mathieu %A Llamas-Guttierez, Francisco %A de Latour, Bertrand %A Guillot, Stéphanie %A Vernhet, Laurent %A Desrues, Benoit %A Thibault, Ronan %< avec comité de lecture %@ 0899-9007 %J Nutrition %I Elsevier %V 62 %P 115-121 %8 2019-06 %D 2019 %R 10.1016/j.nut.2018.12.008 %M 30878815 %K Malnutrition %K Lean body mass %K Food intake %K Bioelectrical impedance analysis %K Interstitial lung disease %Z Life Sciences [q-bio]/Food and Nutrition %Z Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO] %Z Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tractJournal articles %X 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. %G English %2 https://univ-rennes.hal.science/hal-02088078/document %2 https://univ-rennes.hal.science/hal-02088078/file/Jouneau%20et%20al_2018_What%20are%20the%20best%20indicators%20to%20assess%20malnutrition%20in%20idiopathic%20pulmonary.pdf %L hal-02088078 %U https://univ-rennes.hal.science/hal-02088078 %~ UNIV-RENNES1 %~ UNIV-ANGERS %~ INRA %~ LTSI %~ IFR140 %~ FNCLCC %~ MARQUIS %~ HL %~ CIC %~ CIC203 %~ IRSET %~ STATS-UR1 %~ IRSET-SMS %~ IRSET-CCII %~ IRSET-TREC %~ IRSET-HIAEC %~ IRSET-SMLF %~ IRSET-ERD %~ IRSET-VCER %~ IRSET-NEED %~ IRSET-TNGC %~ OSS %~ NUMECAN %~ NUMECAN-ALICE %~ UR1-UFR-SVE %~ UR1-HAL %~ UR1-MATH-STIC %~ UR1-SDV %~ AGREENIUM %~ IRSET-1 %~ TEST-UR-CSS %~ UNIV-RENNES %~ INRAE %~ NUMECAN-EAT %~ UR1-MATH-NUM %~ UR1-BIO-SA