Development, reliability, and validity of a diagnostic algorithm for sarcopenic dysphagia

• Published in: JCSM clinical reports Vol. 2; no. 2; pp. 1 - 10
• Main Authors: Mori, Takashi, Fujishima, Ichiro, Wakabayashi, Hidetaka, Oshima, Fumiko, Itoda, Masataka, Kunieda, Kenjiro, Kayashita, Jun, Nishioka, Shinta, Sonoda, Akiko, Kuroda, Yoshitoshi, Yamada, Minoru, Ogawa, Sumito
• Format: Journal Article
• Language: English
• Published: 01.07.2017
• Subjects: Algorithm; Diagnosis; Dysphagia; Nutrition; Reliability; Sarcopenia
• ISSN: 2521-3555; 2521-3555
• DOI: 10.17987/jcsm-cr.v2i2.17

Background Sarcopenic dysphagia is characterized by difficulty swallowing due to loss of whole‐body skeletal and swallowing muscle mass and function. Despite multiple reports regarding sarcopenic dysphagia, no verified diagnostic methods exist. The purpose of this study was to develop a diagnostic algorithm for sarcopenic dysphagia and verify its reliability and validity. Methods First, our research group, the Working Group on Sarcopenic Dysphagia, developed a diagnostic algorithm for sarcopenic dysphagia. Patients 65 years and older who could follow commands were eligible for assessment using the algorithm. Patients without whole‐body sarcopenia, with normal swallowing function, and with a disease that was an obvious cause of their dysphagia were considered not to have sarcopenic dysphagia. Then, swallowing muscle strength was assessed by tongue pressure. Those with poor swallowing muscle strength were deemed to be at probable risk for sarcopenic dysphagia and those with normal swallowing muscle strength to be at possible risk for sarcopenic dysphagia. Second, we applied the algorithm to inpatients 65 years and older and investigated their characteristics, muscle mass, muscle strength, motor function, swallowing muscle strength, swallowing function, and nutritional status. We investigated the reliability of the algorithm by analyzing intra‐ and inter‐class correlation coefficients using kappa statistics. Third, we investigated the validity of the algorithm by analyzing the difference in the proportion of patients with sarcopenic dysphagia between the no malnutrition and malnutrition groups and investigated the risk factors for sarcopenic dysphagia using logistic regression analysis. Results A total of 119 patients participated in this study. Their mean age was 86.1 years, and 55 (46%) were men. Among the 119 patients, 32 were categorized as having possible sarcopenic dysphagia, 18 probable sarcopenic dysphagia, and 69 no sarcopenic dysphagia. The intra‐class coefficient for the algorithm was 0.87 (95% confidence interval [CI]: 0.73‐1.01), and the inter‐class coefficient was 0.98 (95% CI: 0.92‐1.02), indicating high intra‐ and inter‐rater reliabilities. In the investigation of the algorithm's validity, 67 patients were analyzed. The proportion of patients with sarcopenic dysphagia was significantly higher in the malnutrition than in the no malnutrition group (P = 0.028). Malnutrition and age were independently associated with sarcopenic dysphagia (P = 0.013 and 0.003, respectively). Conclusions A diagnostic algorithm for sarcopenic dysphagia was developed, and its reliability and validity were verified. All older patients with sarcopenia or dysphagia should be assessed for sarcopenic dysphagia, which requires treatment involving not only rehabilitation for dysphagia but also nutritional improvement.