2型糖尿病营养指标——回顾性研究

Nutrition Indicators in Type 2 Diabetes Mellitus-Retrospective Study.

作者信息

Piersa Jakub, Bajek Wiktoria, Pilśniak Aleksandra, Jarosińska Agnieszka, Pietrukaniec Marta, Holecki Michał

机构信息

Student Scientific Society at the Department of Internal, Autoimmune and Metabolic Diseases, School of Medicine, Medical University of Silesia, 40-752 Katowice, Poland.

Department of Internal, Autoimmune and Metabolic Diseases, School of Medicine, Medical University of Silesia, 40-752 Katowice, Poland.

出版信息

Biomedicines. 2025 May 8;13(5):1137. doi: 10.3390/biomedicines13051137.

Abstract

: This study aims to evaluate the prevalence and degree of malnutrition among patients with type 2 diabetes mellitus using the CONUT and PNI scores. : The CONUT and PNI scores provide a reliable assessment of the nutritional status of patients with type 2 diabetes. : The retrospective study was run at the Department of Internal, Autoimmune and Metabolic Diseases in the Central Clinical Hospital of the Medical University of Silesia in Katowice from January to December of 2022. From 266 patients diagnosed with diabetes, only 64 met the criteria and were included in this study. : We found varying degrees of malnutrition among patients. Only 20.3% of them were well nourished. Mild to moderate malnutrition was observed in, altogether, 67.2% of patients. : The strong correlation between the CONUT and PNI (r = -0.88) indices confirms their diagnostic value. The introduction of the CONUT or PNI tools into routine practice should be considered in patients with T2DM, especially those over 65 years of age, but taking into account the significant limitations of these indices and the influence of various factors on the laboratory data considered.

摘要

本研究旨在使用CONUT和PNI评分评估2型糖尿病患者营养不良的患病率和程度。CONUT和PNI评分能可靠地评估2型糖尿病患者的营养状况。这项回顾性研究于2022年1月至12月在卡托维兹西里西亚医科大学中央临床医院的内科、自身免疫和代谢疾病科进行。在266名确诊为糖尿病的患者中,只有64名符合标准并被纳入本研究。我们发现患者中存在不同程度的营养不良。其中只有20.3%的患者营养良好。总共67.2%的患者观察到轻度至中度营养不良。CONUT和PNI指数之间的强相关性(r = -0.88)证实了它们的诊断价值。对于2型糖尿病患者,尤其是65岁以上的患者,应考虑将CONUT或PNI工具引入常规实践,但要考虑到这些指数的显著局限性以及各种因素对所考虑的实验室数据的影响。

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