Intensive Care Unit, Clinical Municipal Hospital, 400139 Cluj-Napoca, Romania.
Faculty of Medicine, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania.
Nutrients. 2022 May 18;14(10):2105. doi: 10.3390/nu14102105.
Malnutrition predicts a worse outcome for critically ill patients. However, quick, easy-to-use nutritional risk assessment tools have not been adequately validated.
The study aimed to evaluate the role of four biological nutritional risk assessment instruments (the Prognostic Nutritional Index-PNI, the Controlling Nutritional Status Score-CONUT, the Nutrition Risk in Critically Ill-NUTRIC, and the modified NUTRIC-mNUTRIC), along with CT-derived fat tissue and muscle mass measurements in predicting in-hospital mortality in a consecutive series of 90 patients hospitalized in the intensive care unit for COVID-19-associated ARDS.
In-hospital mortality was 46.7% ( = 42/90). Non-survivors had a significantly higher nutritional risk, as expressed by all four scores. All scores were independent predictors of mortality on the multivariate regression models. PNI had the best discriminative capabilities for mortality, with an area under the curve (AUC) of 0.77 for a cut-off value of 28.05. All scores had an AUC above 0.72. The volume of fat tissue and muscle mass were not associated with increased mortality risk.
PNI, CONUT, NUTRIC, and mNUTRIC are valuable nutritional risk assessment tools that can accurately predict mortality in critically ill patients with COVID-19-associated ARDS.
营养不良预示着危重症患者的预后更差。然而,快速、易用的营养风险评估工具尚未得到充分验证。
本研究旨在评估四种生物营养风险评估工具(预后营养指数-PNI、控制营养状态评分-CONUT、重症患者营养风险-NUTRIC 和改良 NUTRIC-mNUTRIC),以及 CT 衍生的脂肪组织和肌肉质量测量在预测因 COVID-19 相关 ARDS 而住院的 90 例连续 ICU 患者住院期间死亡率中的作用。
住院死亡率为 46.7%(=42/90)。非幸存者的营养风险明显更高,所有四个评分都显示出这一点。所有评分在多变量回归模型中都是死亡率的独立预测因子。PNI 对死亡率具有最佳的区分能力,截断值为 28.05 时,曲线下面积(AUC)为 0.77。所有评分的 AUC 均高于 0.72。脂肪组织和肌肉质量的体积与死亡率风险增加无关。
PNI、CONUT、NUTRIC 和 mNUTRIC 是有价值的营养风险评估工具,可准确预测 COVID-19 相关 ARDS 危重症患者的死亡率。