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Peter Marckmann - One of the best experts on this subject based on the ideXlab platform.
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Nutritional status of maintenance dialysis patients: Low Lean Body Mass index and obesity are common, protein-energy wasting is uncommon.
2019Co-Authors: Mette Koefoed, Charles Kromann, Sophie Ryberg Juliussen, Danni Hvidtfeldt, Bo Ekelund, Niels Erik Frandsen, Peter MarckmannAbstract:Nutritional status of maintenance dialysis patients: Low Lean Body Mass index and obesity is common, protein-energy wasting is uncommon Abstract Background and aims: Maintenance dialysis patients are at increased risk of abnormal nutritional status due to numerous causative factors, both nutritional and non-nutritional. The present study assessed the current prevalence of protein-energy wasting, low Lean Body Mass index and obesity in maintenance dialysis patients, and compared different methods of nutritional assessment. Methods: In a cross-sectional study conducted in 2014 at Roskilde Hospital, Denmark, we performed anthropometry (Body weight, skinfolds, mid-arm, waist, and hip circumferences), and determined plasma albumin and normalized protein catabolic rate in order to assess the prevalence of protein-energy wasting, low Lean Body Mass index and obesity in these patients. Results: Seventy-nine eligible maintenance dialysis patients participated. The prevalence of protein-energy wasted patients was 4% (95% CI: 2-12) as assessed by the coexistence of low Lean Body Mass index and low fat Mass index. Low Lean Body Mass index was seen in 32% (95% CI: 22-44). Obesity prevalence as assessed from fat Mass index was 43% (95% CI: 32-55). Coexistence of low Lean Body Mass index and obesity was seen in 10% (95% CI: 5-19). The prevalence of protein-energy wasting and obesity varied considerably, depending on nutritional assessment methodology. Conclusions: Our data indicate that protein-energy wasting is uncommon, whereas low Lean Body Mass index and obesity are frequent conditions among patients in maintenance dialysis. A focus on how to increase and preserve Lean Body Mass in dialysis patients is suggested in the future. In order to clearly distinguish between shortage, sufficiency and abundance of protein and/or fat deposits in maintenance dialysis patients, we suggest the simple measurements of Lean Body Mass index and fat Mass index
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Nutritional Status of Maintenance Dialysis Patients: Low Lean Body Mass Index and Obesity Are Common, Protein-Energy Wasting Is Uncommon.
PLOS ONE, 2016Co-Authors: Mette Koefoed, Charles Kromann, Sophie Ryberg Juliussen, Danni Hvidtfeldt, Bo Ekelund, Niels Erik Frandsen, Peter MarckmannAbstract:Background and Aims Maintenance dialysis patients are at increased risk of abnormal nutritional status due to numerous causative factors, both nutritional and non-nutritional. The present study assessed the current prevalence of protein-energy wasting, low Lean Body Mass index and obesity in maintenance dialysis patients, and compared different methods of nutritional assessment.
Maurizio Muscaritoli - One of the best experts on this subject based on the ideXlab platform.
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Lean Body Mass wasting and toxicity in early breast cancer patients receiving anthracyclines
Oncotarget, 2018Co-Authors: Federica Mazzuca, Concetta Elisa Onesti, Michela Roberto, Marco Di Girolamo, Andrea Botticelli, Paola Begini, Lidia Strigari, Paolo Marchetti, Maurizio MuscaritoliAbstract:// Federica Mazzuca 1, 2 , Concetta Elisa Onesti 1, 3 , Michela Roberto 1, 2 , Marco Di Girolamo 4 , Andrea Botticelli 1 , Paola Begini 5 , Lidia Strigari 6 , Paolo Marchetti 1, 2 and Maurizio Muscaritoli 7 1 Department of Clinical and Molecular Medicine, “Sapienza” University of Rome, Rome, Italy 2 Department of Medical Oncology, Sant’Andrea Hospital, Rome, Italy 3 Department of Medical Oncology, University Hospital (CHU) and University of Liege, Liege, Belgium 4 Department of Radiology, Sant’Andrea Hospital, Rome, Italy 5 Department of Gastroenterology, Sant’Andrea Hospital, Rome, Italy 6 Laboratory of Medical Physics and Expert Systems, Regina Elena National Cancer Institute, Rome, Italy 7 Department of Clinical Medicine, Sapienza University of Rome, Rome, Italy Correspondence to: Concetta Elisa Onesti, email: elisaonesti@gmail.com Keywords: breast cancer; sarcopenia; Lean Body Mass; anthracyclines toxicity; adjuvant chemotherapy Received: February 12, 2018 Accepted: April 28, 2018 Published: May 22, 2018 ABSTRACT Background: Sarcopenia refers to the reduction of both volume and number of skeletal muscle fibers. Lean Body Mass loss is associated with survival, quality of life and tolerance to treatment in cancer patients. The aim of our study is to analyse the association between toxicities and sarcopenia in early breast cancer patients receiving adjuvant treatment. Materials and Methods: Breast cancer patients who have received anthracycline-based adjuvant treatment were retrospectively enrolled. CT scan images performed before, during and after adjuvant chemotherapy were used to evaluate Lean Body Mass at third lumbar vertebra level with the software Slice Omatic V 5.0. Results: 21 stage I–III breast cancer patients were enrolled. According to the skeletal muscle index at third lumbar vertebra cut-off ≤38.5 cm 2 /m 2 , 8 patients (38.1%) were classified as sarcopenic before starting treatment, while 10 patients (47.6%) were sarcopenic at the end of treatment. A lower baseline L3 skeletal muscle index is associated with G3-4 vs G0-2 toxicities (33.4 cm 2 /m 2 (31.1–39.9) vs 40.5 cm 2 /m 2 (33.4–52.0), p = 0.028). Similarly skeletal muscle cross sectional area was significantly lower in patients with G3-4 toxicities (86.7 cm 2 (82.6–104.7) vs 109.0 cm 2 (83.3–143.9), p = 0.017). L3 skeletal muscle index is an independent predictor of severe toxicity ( p = 0.0282) in multivariate analysis. Conclusion: Lean Body Mass loss is associated with higher grade of toxicity in early breast cancer patients receiving adjuvant chemotherapy.
Mette Koefoed - One of the best experts on this subject based on the ideXlab platform.
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Nutritional status of maintenance dialysis patients: Low Lean Body Mass index and obesity are common, protein-energy wasting is uncommon.
2019Co-Authors: Mette Koefoed, Charles Kromann, Sophie Ryberg Juliussen, Danni Hvidtfeldt, Bo Ekelund, Niels Erik Frandsen, Peter MarckmannAbstract:Nutritional status of maintenance dialysis patients: Low Lean Body Mass index and obesity is common, protein-energy wasting is uncommon Abstract Background and aims: Maintenance dialysis patients are at increased risk of abnormal nutritional status due to numerous causative factors, both nutritional and non-nutritional. The present study assessed the current prevalence of protein-energy wasting, low Lean Body Mass index and obesity in maintenance dialysis patients, and compared different methods of nutritional assessment. Methods: In a cross-sectional study conducted in 2014 at Roskilde Hospital, Denmark, we performed anthropometry (Body weight, skinfolds, mid-arm, waist, and hip circumferences), and determined plasma albumin and normalized protein catabolic rate in order to assess the prevalence of protein-energy wasting, low Lean Body Mass index and obesity in these patients. Results: Seventy-nine eligible maintenance dialysis patients participated. The prevalence of protein-energy wasted patients was 4% (95% CI: 2-12) as assessed by the coexistence of low Lean Body Mass index and low fat Mass index. Low Lean Body Mass index was seen in 32% (95% CI: 22-44). Obesity prevalence as assessed from fat Mass index was 43% (95% CI: 32-55). Coexistence of low Lean Body Mass index and obesity was seen in 10% (95% CI: 5-19). The prevalence of protein-energy wasting and obesity varied considerably, depending on nutritional assessment methodology. Conclusions: Our data indicate that protein-energy wasting is uncommon, whereas low Lean Body Mass index and obesity are frequent conditions among patients in maintenance dialysis. A focus on how to increase and preserve Lean Body Mass in dialysis patients is suggested in the future. In order to clearly distinguish between shortage, sufficiency and abundance of protein and/or fat deposits in maintenance dialysis patients, we suggest the simple measurements of Lean Body Mass index and fat Mass index
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Nutritional Status of Maintenance Dialysis Patients: Low Lean Body Mass Index and Obesity Are Common, Protein-Energy Wasting Is Uncommon.
PLOS ONE, 2016Co-Authors: Mette Koefoed, Charles Kromann, Sophie Ryberg Juliussen, Danni Hvidtfeldt, Bo Ekelund, Niels Erik Frandsen, Peter MarckmannAbstract:Background and Aims Maintenance dialysis patients are at increased risk of abnormal nutritional status due to numerous causative factors, both nutritional and non-nutritional. The present study assessed the current prevalence of protein-energy wasting, low Lean Body Mass index and obesity in maintenance dialysis patients, and compared different methods of nutritional assessment.
C S Mcardle - One of the best experts on this subject based on the ideXlab platform.
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Lean Body Mass changes in cancer patients with weight loss
Clinical Nutrition, 2000Co-Authors: Donald C Mcmillan, Walter S Watson, T Preston, C S McardleAbstract:Abstract Background and Aims : Metabolic measurements (e.g. resting energy expenditure) are adjusted to Lean Body Mass to account for Body composition differences. Usually Lean Body Mass is estimated from total Body water. However, this may be compromised in weight-losing cancer patients owing to alterations in the degree of hydration of the Lean Body Mass. This study examined the relationship between two independent estimates of Lean Body Mass in healthy subjects and cancer patients with weight loss. Methods and Results : Height, weight, total Body water and total Body potassium were measured in healthy subjects ( n =9) and weight losing cancer patients ( n =13). They were similar in terms of age and gender. However, the cancer group had a significantly lower percentage ideal Body weight ( P P r =0.698, P Conclusions : These results suggest that total Body water significantly overestimates metabolically active tissue in weight-losing cancer patients and therefore its use as the basis for metabolic requirements in this group of patients is questionable.
Edward Giovannucci - One of the best experts on this subject based on the ideXlab platform.
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predicted Lean Body Mass fat Mass and risk of lung cancer prospective us cohort study
European Journal of Epidemiology, 2019Co-Authors: Su Min Jeong, Dong Hoon Lee, Edward GiovannucciAbstract:An inverse association between Body Mass index (BMI) and risk of lung cancer has been reported. However, the association of Body composition such as fat Mass (FM) and Lean Body Mass (LBM) with risk of lung cancer has not been fully investigated. Using two large prospective cohort studies (Nurses’ Health Study, 1986–2014; Health Professionals Follow-up Study, 1987–2012) in the United States, we included 100,985 participants who were followed for occurrence of lung cancer. Predicted FM and LBM derived from validated anthropometric prediction equations were categorized by sex-specific deciles. During an average 22.3-year follow-up, 2615 incident lung cancer cases were identified. BMI showed an inverse association with lung cancer risk. Participants in the 10th decile of predicted FM and LBM had a lower risk of lung cancer compared with those in the 1st decile, but when mutually adjusted for each other, predicted FM was not associated with lung cancer risk (adjusted hazard ratio [aHR] = 0.98, 95% confidence interval [CI] 0.72–1.35; P(trend) = 0.97) whereas predicted LBM had an inverse association (aHR = 0.73, 95% CI 0.53–1.00; P(trend) = 0.03), especially among participants who were current smokers or had smoked in the previous 10 years (aHR = 0.55, 95% CI 0.36–0.84; P(trend) = 0.008). In conclusion, BMI was inversely associated with lung cancer risk. Based on anthropometric prediction equations, low LBM rather than low FM accounted for the inverse association between BMI and lung cancer risk.
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predicted Lean Body Mass fat Mass and all cause and cause specific mortality in men prospective us cohort study
BMJ, 2018Co-Authors: Dong Hoon Lee, Nana Keum, John E Orav, Eric B Rimm, Walter C Willett, Edward GiovannucciAbstract:Abstract Objective To investigate the association of predicted Lean Body Mass, fat Mass, and Body Mass index (BMI) with all cause and cause specific mortality in men. Design Prospective cohort study. Setting Health professionals in the United States Participants 38 006 men (aged 40-75 years) from the Health Professionals Follow-up Study, followed up for death (1987-2012). Main outcome measures All cause and cause specific mortality. Results Using validated anthropometric prediction equations previously developed from the National Health and Nutrition Examination Survey, Lean Body Mass and fat Mass were estimated for all participants. During a mean of 21.4 years of follow-up, 12 356 deaths were identified. A J shaped association was consistently observed between BMI and all cause mortality. Multivariable adjusted Cox models including predicted fat Mass and Lean Body Mass showed a strong positive monotonic association between predicted fat Mass and all cause mortality. Compared with those in the lowest fifth of predicted fat Mass, men in the highest fifth had a hazard ratio of 1.35 (95% confidence interval 1.26 to 1.46) for mortality from all causes. In contrast, a U shaped association was found between predicted Lean Body Mass and all cause mortality. Compared with those in the lowest fifth of predicted Lean Body Mass, men in the second to fourth fifths had 8-10% lower risk of mortality from all causes. In the restricted cubic spline models, the risk of all cause mortality was relatively flat until 21 kg of predicted fat Mass and increased rapidly afterwards, with a hazard ratio of 1.22 (1.18 to 1.26) per standard deviation. For predicted Lean Body Mass, a large reduction of the risk was seen within the lower range until 56 kg, with a hazard ratio of 0.87 (0.82 to 0.92) per standard deviation, which increased thereafter (P for non-linearity Conclusions The shape of the association between BMI and mortality was determined by the relation between two Body components (Lean Body Mass and fat Mass) and mortality. This finding suggests that the “obesity paradox” controversy may be largely explained by low Lean Body Mass, rather than low fat Mass, in the lower range of BMI.
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development and validation of anthropometric prediction equations for Lean Body Mass fat Mass and percent fat in adults using the national health and nutrition examination survey nhanes 1999 2006
British Journal of Nutrition, 2017Co-Authors: Dong Hoon Lee, Nana Keum, John E Orav, Eric B Rimm, Walter C Willett, Qi Sun, Edward GiovannucciAbstract:Quantification of Lean Body Mass and fat Mass can provide important insight into epidemiological research. However, there is no consensus on generalisable anthropometric prediction equations to validly estimate Body composition. We aimed to develop and validate practical anthropometric prediction equations for Lean Body Mass, fat Mass and percent fat in adults (men, n 7531; women, n 6534) from the National Health and Nutrition Examination Survey 1999-2006. Using a prediction sample, we predicted each of dual-energy X-ray absorptiometry (DXA)-measured Lean Body Mass, fat Mass and percent fat based on different combinations of anthropometric measures. The proposed equations were validated using a validation sample and obesity-related biomarkers. The practical equation including age, race, height, weight and waist circumference had high predictive ability for Lean Body Mass (men: R 2=0·91, standard error of estimate (SEE)=2·6 kg; women: R 2=0·85, SEE=2·4 kg) and fat Mass (men: R 2=0·90, SEE=2·6 kg; women: R 2=0·93, SEE=2·4 kg). Waist circumference was a strong predictor in men only. Addition of other circumference and skinfold measures slightly improved the prediction model. For percent fat, R 2 were generally lower but the trend in variation explained was similar. Our validation tests showed robust and consistent results with no evidence of substantial bias. Additional validation using biomarkers demonstrated comparable abilities to predict obesity-related biomarkers between direct DXA measurements and predicted scores. Moreover, predicted fat Mass and percent fat had significantly stronger associations with obesity-related biomarkers than BMI did. Our findings suggest the potential application of the proposed equations in various epidemiological settings.
