MICHELINE TEREZA PIRES DE SOUZA
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- Applied nutritional investigation Effect of age on resting energy expenditure in patients with cancer(2022) SOUZA, Micheline Tereza Pires de; OZORIO, Gislaine Aparecida; OLIVEIRA, Giovanna Nunes de; LOPEZ, Rossana Veronica Mendoza; ALVES-ALMEIDA, Maria Manuela Ferreira; KULCSAR, Marco Aurelio Vamondes; RIBEIRO JR., Ulysses; SINGER, Pierre; WAITZBERG, Dan L.Objective: Because older patients with cancer are at high risk for developing malnutrition, it is critical to understand their energy needs and to feed them appropriately. The aim of this study was to determine whether there are differences in resting energy expenditure between younger and older adults with cancer and in various age groups of older patients. Methods: This retrospective, observational, and descriptive study from a single center included adult ( 60 y) and older ( 0.001). The REE of older patients (1263.3 [234.1] kcal/d) was lower than that of patients 60 y, an REE greater than those for individuals 60 to 69 y, 70 to 79 y, and 0.001). REE in patients 60 to 69 y was greater than for those 0.001). When compared with the Harris-Benedict formula, the REE intraclass correlation coefficient for all older patients was 0.514 (95% confidence interval [CI], 0.064-0.736); for ages 60 to 69 y it was 0.527 (95% CI, 0.126-0.733), and for ages 70 y, it was 0.466 (95% CI,-0.080 to-0.756). Conclusion: Measured REE in patients with cancer decreases with age. This finding is critical for appropriate caloric provision for older patients with cancer. ?? 2022 Elsevier Inc. All rights reserved.
- Validation and improvement of the predictive equation for resting energy expenditure in advanced gastrointestinal cancer(2020) OZORIO, Gislaine Aparecida; SOUZA, Micheline Tereza Pires de; SINGER, Pierre; LOPEZ, Rossana Veronica Mendoza; ALVES-ALMEIDA, Maria Manuela Ferreira; RIBEIRO-JUNIOR, Ulysses; WAITZBERG, Dan LinetzkyObjectives: The usual predictive equations for estimating resting energy expenditure (REE) seem to be associated with significant inaccuracy in patients with advanced cancer. Recently, our group developed a predictive equation for patients with advanced head and neck cancer, showing a better accuracy when compared with indirect calorimetry. The aim of this study was to validate this predictive equation and, if necessary, to elaborate a new predictive equation for patients with advanced gastrointestinal (GI) cancer. Methods: This was a retrospective, unicentric observational study. Data regarding the characteristics of the study were collected using an electronic medical record from June 2016 to January 2018. The nutritional status was calculated by the body mass index (BMI). Patients with nutritional risk, by the Nutritional Risk Screening 2002, were subjectively evaluated in relation to the nutritional status by the Patient-Generated Subjective Global Assessment (PG-SGA). Sarcopenia was defined as fat-free mass index <= 17.4 kg/m(2) for men and <= 15 kg/m(2) for women. Body composition and phase angle values were evaluated by electrical bioimpedance. REE was measured by indirect calorimetry. Results: The study included 109 patients with advanced GI tract cancer. Most were male (72.5%), >= 60 y of age (61.5%), and had cancer in the esophagus region (62.4%). Most patients had not undergone any treatment at the time of the examination. Regarding nutritional characteristics, the majority of the patients were malnourished by BMI (71.6%), with a deficit of lean mass (79.8%), sarcopenia (83.5%), and a phase angle below the fifth percentile for age, sex, and BMI, showing in addition to a poor nutritional condition, an impaired cellular integrity. Most of the patients were hypermetabolic (56.9%) and their caloric intake in the preceding 3 d was insufficient in 43.1%. Through the intraclass correlation coefficient (ICC), it was possible to observe the satisfactory agreement between the REE measured by the gold standard (calorimetry) versus the Souza-Singer's formula (ICC, 0.730; 95% confidence interval, 0.659-0.789; P < 0.001). When we did the multiple linear regression model, we figured that in this group of patients with GI cancer, only lean mass, phase angle, and sex were the age-adjusted independent variables that influenced REE, which was different from the Souza-Singer formula. This way a new prediction formula for this population has been created and needs to be validated. Conclusion: A new equation considering phase angle and body composition can improve the accuracy of the predictive equation.