Assessment of malnutrition-related risk in patients with idiopathic pleuroparenchymal fibroelastosis - Yuzo Suzuki; Atsuki Fukada; Kazutaka Mori; Masato Kono; Hirotsugu Hasegawa; Dai Hashimoto; Koshi Yokomura; Shiro Imokawa; Yusuke Inoue; Hideki Yasui; Hironao Hozumi; Masato Karayama; et al. (ERJ Open Research, 2023)
Background Idiopathic pleuroparenchymal fibroelastosis (IPPFE) is characterised by upper lobe-dominant fibrosis involving the pleura and subpleural lung parenchyma, with advanced cases often complicated by progressive weight loss. Therefore, we hypothesised that nutritional status is associated with mortality in IPPFE. Methods This retrospective study assesses nutritional status at the time of diagnosis and 1 year after diagnosis in 131 patients with IPPFE. Malnutrition-related risk was evaluated using the Geriatric Nutritional Risk Index (GNRI). Results Of the 131 patients, 96 (73.8%) were at malnutrition-related risk at the time of diagnosis according to the GNRI. Of these, 21 patients (16.0%) were classified as at major malnutrition-related risk (GNRI <82). Patients at major malnutrition-related risk were significantly older and had worse pulmonary function than patients at low (GNRI 92– <98) and moderate (GNRI 82– <92) malnutrition-related risk. GNRI scores decreased significantly from the time of diagnosis to 1 year after diagnosis. Patients with a lower GNRI (<91.8) had significantly shorter survival than patients with a median GNRI or higher (≥91.8). Patients with declines in annual GNRI scores of ≥5 had significantly shorter survival than patients with declines in annual GNRI scores of <5. In multivariate analysis, major malnutrition-related risk was significantly associated with increased mortality after adjustment for age, sex and forced vital capacity (hazard ratio 1.957). A composite scoring model including age, sex and major malnutrition-related risk was able to separate mortality risk in IPPFE. Conclusion Assessment of nutritional status by the GNRI provides useful information for managing patients with IPPFE by predicting mortality risk.