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Clin Nutr ESPEN. 2018 Jun;25:114-120. doi: 10.1016/j.clnesp.2018.03.122. Epub 2018 Apr 4.

The use of computed tomography images as a prognostic marker in critically ill cancer patients.

Author information

1
Department of Critical Care Medicine, Hospital Israelita Albert Einstein, São Paulo, Brazil. Electronic address: diogootoledo@gmail.com.
2
Department of Critical Care Medicine, Hospital Do Cancer de Barretos, Barretos, Brazil.
3
Federal University of Rio Grande Do Norte, Brazil.
4
Department of Surgery, Hopsital Servidor Público Estadual, São Paulo, Brazil.
5
Department of Agricultural, Food and Nutritional Sciences, University of Alberta, Canada.
6
Department of Critical Care Medicine, Hospital Israelita Albert Einstein, São Paulo, Brazil.

Abstract

BACKGROUND & AIMS:

In the intensive care unit (ICU) setting, body composition is typically estimated through anthropometry, which does not specifically quantify skeletal muscle (SM). Recent findings have shown that computed tomography (CT) is a useful tool to identify low SM in critically ill patients, which in turn is associated with poor clinical outcomes. So, the present study aims at comparing low SM assessed by CT to BMI anthropometric data and its association with outcomes in critically ill patients.

METHODS:

Observational study was used, which included >18 year-old patients, with over 72 h of ICU length of stay, who had an abdominal CT at ICU admission. Demographic, body mass index (BMI), hospital outcomes and abdominal CT data (SM and adipose tissue at the 3rd lumbar vertebrae) were collected for analysis. ROC curve optimal stratification analysis for hospital mortality was applied to classify people into low SM (sarcopenic) versus normal SM (non-sarcopenic). A Cox regression was applied to find independent associations between sarcopenia and 30-day survival.

RESULTS:

The study involved 99 patients, 56% male, mean-age of 61.6 years old, BMI 24.19 ± 4.49 kg/m2; hospital mortality was 26%. According to BMI, 19.4% of the patients were underweight. However, a poor correlation was observed between BMI and SM index by CT: R2 = 0.39, P < 0.001. The cutoff point for determining sarcopenia by CT was 41.2 cm2/m2 (sensitivity 70%, specificity 69.5%, AUC 70.3) for both sexes. The sarcopenia diagnosis by CT as nutritional evaluation parameters was correlated with malnutrition BMI diagnosis in only 35.5%. When compared to non-sarcopenic patients, those with sarcopenia presented worse 30-day survival adjusted by age and SAPS 3 (HR = 2.74, 95%CI = 1.02-7.35, P = 0.04), higher hospital mortality (41.9% vs 14.6%, P = 0.006) and ICU non-infectious complications (76.7% vs 52.1%, P = 0.016).

CONCLUSION:

Sarcopenia assessed by abdominal CT demonstrated low correlation with BMI and was a risk factor for lower 30-day survival, higher hospital mortality and higher complications in critically ill patients.

KEYWORDS:

Cancer; Critically ill patients; Muscle mass index; Outcome; Sarcopenia

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