Yuji Mitani1,2, Yutaro Oki2,3, Yukari Fujimoto2, Takumi Yamaguchi2,3, Kentaro Iwata2,4, Yu Watanabe2,5, Kazuki Takahashi2,6, Kanji Yamada2, Akira Ishikawa2. 1. Department of Rehabilitation, Sapporo Nishimaruyama Hospital, Hokkaido, Japan. 2. Department of Community Health Sciences, Kobe University Graduate School of Health Sciences, Hyogo, Japan. 3. Department of Rehabilitation, Kobe City Medical Center West Hospital, Hyogo, Japan. 4. Department of Rehabilitation, Kobe City Medical Center General Hospital, Hyogo, Japan. 5. Department of Rehabilitation, Doi Hospital, Hyogo, Japan. 6. Department of Rehabilitation, Faculty of Medical Science and Welfare, Tohoku Bunka Gakuen University, Miyagi, Japan.
Abstract
AIM: The prevention of pneumonia is an urgent issue among Japanese older adults. However, little has been reported on the relationship between a Functional Independence Measure (FIM) and the Geriatric Nutrition Risk Index (GNRI) for the prevention of pneumonia in patients in long-term care facilities in Japan. We aimed to clarify the relevance of FIM and GNRI for inpatients with and without pneumonia. METHODS: We identified 233 patients who were hospitalized in our long-term nursing hospital from April 2012 to September 2013. We compared differences in FIM among GNRI classes for four groups: (i) pneumonia/high GNRI; (ii) pneumonia/low GNRI; (iii) no pneumonia/high GNRI; and (iv) no pneumonia/low GNRI. To assess the pneumonia predictors, we used a logistic regression for long-term nursing patients. Receiver operating characteristic analysis showed cut-off values and the area under the curve. RESULTS: A total of 88 (37.8%) of 233 inpatients had pneumonia. FIM of the pneumonia/low GNRI groups was significantly lower than that of the no pneumonia/high and low GNRI groups. Logistic regression showed that FIM (P < 0.001; OR -1.035, 95% CI -1.019-1.051) and GNRI (P = 0.017; OR -1.038, 95% CI -1.007-1.070) were predictors of pneumonia. The cut-off values for FIM and GNRI were 26.6 (P < 0.001, the area under the curve 0.70) and 80.5 (P < 0.001, the area under the curve 0.65), respectively. CONCLUSION: Low activity and malnutrition might lead to the development of pneumonia. FIM and GNRI are useful predictor tools that could help to prevent pneumonia in Japanese patients in long-term care facilities. Geriatr Gerontol Int 2017; 17: 1617-1622.
AIM: The prevention of pneumonia is an urgent issue among Japanese older adults. However, little has been reported on the relationship between a Functional Independence Measure (FIM) and the Geriatric Nutrition Risk Index (GNRI) for the prevention of pneumonia in patients in long-term care facilities in Japan. We aimed to clarify the relevance of FIM and GNRI for inpatients with and without pneumonia. METHODS: We identified 233 patients who were hospitalized in our long-term nursing hospital from April 2012 to September 2013. We compared differences in FIM among GNRI classes for four groups: (i) pneumonia/high GNRI; (ii) pneumonia/low GNRI; (iii) no pneumonia/high GNRI; and (iv) no pneumonia/low GNRI. To assess the pneumonia predictors, we used a logistic regression for long-term nursing patients. Receiver operating characteristic analysis showed cut-off values and the area under the curve. RESULTS: A total of 88 (37.8%) of 233 inpatients had pneumonia. FIM of the pneumonia/low GNRI groups was significantly lower than that of the no pneumonia/high and low GNRI groups. Logistic regression showed that FIM (P < 0.001; OR -1.035, 95% CI -1.019-1.051) and GNRI (P = 0.017; OR -1.038, 95% CI -1.007-1.070) were predictors of pneumonia. The cut-off values for FIM and GNRI were 26.6 (P < 0.001, the area under the curve 0.70) and 80.5 (P < 0.001, the area under the curve 0.65), respectively. CONCLUSION: Low activity and malnutrition might lead to the development of pneumonia. FIM and GNRI are useful predictor tools that could help to prevent pneumonia in Japanese patients in long-term care facilities. Geriatr Gerontol Int 2017; 17: 1617-1622.
Authors: K Shirado; H Wakabayashi; K Maeda; A Nishiyama; M Asada; H Isse; S Saito; C Kakitani; R Momosaki Journal: J Nutr Health Aging Date: 2020 Impact factor: 4.075