Prevalence and prognostic significance of malnutrition in early-stage multiple system atrophy

Front Nutr. 2023 Nov 22:10:1248349. doi: 10.3389/fnut.2023.1248349. eCollection 2023.

Abstract

Background: Malnutrition is associated with poor survival in some diseases. However, the nutritional status in multiple system atrophy (MSA) is unknown, and the significance of malnutrition for the prediction of mortality in MSA has not been well established.

Objective: We aimed to determine the prevalence of malnutrition and the prognostic value of malnutrition in patients with early-stage MSA.

Methods: Patients diagnosed with early phase MSA (disease duration<3 years) were recruited, and they were followed every year until May 2023. The nutritional status of patients with MSA was assessed using the Controlling Nutritional Status (CONUT) score and Geriatric Nutritional Risk Index (GNRI). Kaplan-Meier survival analysis and Cox regression model were used to assess the prognostic value of malnutrition in MSA.

Results: A total of 224 patients with probable MSA (106 MSA died and 118 were still alive) and 213 matched healthy controls (HCs) were enrolled. According to COUNT score and GNRI, patients with MSA had higher prevalence of malnutrition than HCs (44.6% vs. 14.1 and 17.9% vs. 0.9%, respectively). The median survival from symptom onset in patients with MSA in the malnutrition group was shorter than those in the normal-nutrition group (5.98 vs. 7.06 years, p = 0.012) by COUNT score. Additionally, malnutrition increased the risk of mortality in patients with MSA (HR = 1.556, p = 0.030) and MSA-P (HR = 1.973, p = 0.042) by COUNT score.

Interpretation: Malnutrition was common in patients with early-stage MSA. Malnutrition increased the risk of mortality in patients with MSA, and early nutritional supplementation should be taken into consideration.

Keywords: cohort study; controlling nutritional status score; malnutrition; multiple system atrophy; survival.

Grants and funding

The present study was supported by the funding of Sichuan Science and Technology Program (Grant No. 2022ZDZX0023), Sichuan Postdoctoral Program (Grant No. TB2022043), and the National Natural Science Foundation of China (Grant No. 82301602).