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El Alami El Hassani N, Akrichi MA, Bajit H, Alem C. Investigation of accordance between nutritional assessment tools, and bio-electrical impedance-derived phase angle, with the global leadership initiative on malnutrition criteria in hemodialysis patients. Clin Nutr ESPEN 2024; 62:260-269. [PMID: 38865238 DOI: 10.1016/j.clnesp.2024.05.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 05/22/2024] [Accepted: 05/31/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND Malnutrition (MN) is a major health concern for patients with chronic kidney disease (CKD) who receive maintenance hemodialysis (MHD). These patients are particularly vulnerable to MN due to their compromised health status, which in turn increases the risk of morbidity and mortality. However, there is limited evidence on the use of reliable and effective tools for assessing MN in this population. This lack of sufficient data highlights the crucial need to assess MN within these patients, considering the significant mortality risk it poses. The first aim of this study was to compare the concurrent validity of three nutritional methods: the 7-point Subjective Global Assessment (7p-SGA), the Nutritional Risk Index (NRI), and the Nutritional Risk Screening from 2002 (NRS-2002) with the Global Leadership Initiative on Malnutrition (GLIM) criteria in MHD patients. The second aim was to investigate the advantage of the bio-electrical impedance-derived phase angle (PhA) in predicting MN. METHODS one hundred sixty-eight outpatients (31% women) with a mean age of 56.9 ± 14.7 years and a median dialysis vintage of 48 months were included in this retrospective study. Nutritional scores, anthropometric measurements, biological markers, and body composition parameters were collected. RESULTS According to GLIM standards, MN was identified in 80% of these patients. Using logistic regression (LR) analysis, all nutritional scores were significantly associated with GLIM criteria, with optimal sensitivity (94.4%) and specificity (85.7%) for 7p-SGA and NRI, respectively. For discriminating the nutritional risk, the GLIM criteria demonstrated a good agreement with 7p-SGA (Kappa concordance coefficient (κ) = 0.677, p-value<0.001) with a good level of accuracy (Area Under the Curve (AUC) = 0.841; 95% Confidence Interval (CI) = 0.705-0.977; p-value <0.001) when compared to the NRI and NRS-2002 (κ = 0.522, p-value<0.001 and κ = 0.411, p-value = 0.006, respectively). An excellent accuracy was found between PhA and the GLIM-defined MN, with an optimal cut-off value of 5.5° for males and 4.5° for females. The LR showed that arm circumference is the parameter that most influences the decrease of PhA (odds ratio 2.710, 95% CI = 1.597-4.597, p-value <0.001). CONCLUSION Based on the results of the present study, 7p-SGA is the most sensitive score in identifying MN diagnosed by GLIM criteria. Nonetheless, NRI exhibits greater specificity. PhA is a valuable marker for MN in MHD patients.
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Affiliation(s)
- Nadia El Alami El Hassani
- Team of Biochemistry of Natural Resources, Faculty of Sciences and Techniques, Moulay Ismaïl University, Errachidia, Morocco.
| | | | - Habiba Bajit
- Team of Biochemistry of Natural Resources, Faculty of Sciences and Techniques, Moulay Ismaïl University, Errachidia, Morocco; Department of Pharmacology, Faculty of Medicine, University of Granada, Spain
| | - Chakib Alem
- Team of Biochemistry of Natural Resources, Faculty of Sciences and Techniques, Moulay Ismaïl University, Errachidia, Morocco
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Luengo-Pérez LM, Fernández-Bueso M, Ambrojo A, Guijarro M, Ferreira AC, Pereira-da-Silva L, Moreira-Rosário A, Faria A, Calhau C, Daly A, MacDonald A, Rocha JC. Body Composition Evaluation and Clinical Markers of Cardiometabolic Risk in Patients with Phenylketonuria. Nutrients 2023; 15:5133. [PMID: 38140392 PMCID: PMC10745907 DOI: 10.3390/nu15245133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 12/07/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023] Open
Abstract
Cardiovascular diseases are the main cause of mortality worldwide. Patients with phenylketonuria (PKU) may be at increased cardiovascular risk. This review provides an overview of clinical and metabolic cardiovascular risk factors, explores the connections between body composition (including fat mass and ectopic fat) and cardiovascular risk, and examines various methods for evaluating body composition. It particularly focuses on nutritional ultrasound, given its emerging availability and practical utility in clinical settings. Possible causes of increased cardiometabolic risk in PKU are also explored, including an increased intake of carbohydrates, chronic exposure to amino acids, and characteristics of microbiota. It is important to evaluate cardiovascular risk factors and body composition in patients with PKU. We suggest systematic monitoring of body composition to develop nutritional management and hydration strategies to optimize performance within the limits of nutritional therapy.
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Affiliation(s)
- Luis M. Luengo-Pérez
- Biomedical Sciences Department, University of Extremadura, 06008 Badajoz, Spain
- Clinical Nutrition and Dietetics Unit, Badajoz University Hospital, 06008 Badajoz, Spain; (M.F.-B.); (A.A.); (M.G.)
| | - Mercedes Fernández-Bueso
- Clinical Nutrition and Dietetics Unit, Badajoz University Hospital, 06008 Badajoz, Spain; (M.F.-B.); (A.A.); (M.G.)
| | - Ana Ambrojo
- Clinical Nutrition and Dietetics Unit, Badajoz University Hospital, 06008 Badajoz, Spain; (M.F.-B.); (A.A.); (M.G.)
| | - Marta Guijarro
- Clinical Nutrition and Dietetics Unit, Badajoz University Hospital, 06008 Badajoz, Spain; (M.F.-B.); (A.A.); (M.G.)
| | - Ana Cristina Ferreira
- Reference Centre of Inherited Metabolic Diseases, Centro Hospitalar Universitário de Lisboa Central, Rua Jacinta Marto, 1169-045 Lisboa, Portugal; (A.C.F.); or (J.C.R.)
| | - Luís Pereira-da-Silva
- CHRC—Comprehensive Health Research Centre, Nutrition Group, NOVA Medical School, Universidade Nova de Lisboa, 1349-008 Lisboa, Portugal; (L.P.-d.-S.); (A.F.)
- NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (A.M.-R.); (C.C.)
| | - André Moreira-Rosário
- NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (A.M.-R.); (C.C.)
- CINTESIS@RISE, Nutrition and Metabolism, NOVA Medical School (NMS), Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal
| | - Ana Faria
- CHRC—Comprehensive Health Research Centre, Nutrition Group, NOVA Medical School, Universidade Nova de Lisboa, 1349-008 Lisboa, Portugal; (L.P.-d.-S.); (A.F.)
- CINTESIS@RISE, Nutrition and Metabolism, NOVA Medical School (NMS), Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal
| | - Conceição Calhau
- NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (A.M.-R.); (C.C.)
- CINTESIS@RISE, Nutrition and Metabolism, NOVA Medical School (NMS), Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal
| | - Anne Daly
- Birmingham Children’s Hospital, Birmingham B4 6NH, UK; (A.D.); (A.M.)
| | - Anita MacDonald
- Birmingham Children’s Hospital, Birmingham B4 6NH, UK; (A.D.); (A.M.)
| | - Júlio César Rocha
- Reference Centre of Inherited Metabolic Diseases, Centro Hospitalar Universitário de Lisboa Central, Rua Jacinta Marto, 1169-045 Lisboa, Portugal; (A.C.F.); or (J.C.R.)
- NOVA Medical School (NMS), Faculdade de Ciências Médicas (FCM), Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal; (A.M.-R.); (C.C.)
- CINTESIS@RISE, Nutrition and Metabolism, NOVA Medical School (NMS), Faculdade de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal
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Low Tissue Creatine: A Therapeutic Target in Clinical Nutrition. Nutrients 2022; 14:nu14061230. [PMID: 35334887 PMCID: PMC8955088 DOI: 10.3390/nu14061230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/07/2022] [Accepted: 03/08/2022] [Indexed: 11/25/2022] Open
Abstract
Low tissue creatine characterizes many conditions, including neurodegenerative, cardiopulmonary, and metabolic diseases, with a magnitude of creatine shortfall often corresponds well to a disorder’s severity. A non-invasive monitoring of tissue metabolism with magnetic resonance spectroscopy (MRS) might be a feasible tool to evaluate suboptimal levels of creatine for both predictive, diagnostic, and therapeutic purposes. This mini review paper summarizes disorders with deficient creatine levels and provides arguments for assessing and employing tissue creatine as a relevant target in clinical nutrition.
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Morton SU, Leyshon BJ, Tamilia E, Vyas R, Sisitsky M, Ladha I, Lasekan JB, Kuchan MJ, Grant PE, Ou Y. A Role for Data Science in Precision Nutrition and Early Brain Development. Front Psychiatry 2022; 13:892259. [PMID: 35815018 PMCID: PMC9259898 DOI: 10.3389/fpsyt.2022.892259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 05/17/2022] [Indexed: 11/13/2022] Open
Abstract
Multimodal brain magnetic resonance imaging (MRI) can provide biomarkers of early influences on neurodevelopment such as nutrition, environmental and genetic factors. As the exposure to early influences can be separated from neurodevelopmental outcomes by many months or years, MRI markers can serve as an important intermediate outcome in multivariate analyses of neurodevelopmental determinants. Key to the success of such work are recent advances in data science as well as the growth of relevant data resources. Multimodal MRI assessment of neurodevelopment can be supplemented with other biomarkers of neurodevelopment such as electroencephalograms, magnetoencephalogram, and non-imaging biomarkers. This review focuses on how maternal nutrition impacts infant brain development, with three purposes: (1) to summarize the current knowledge about how nutrition in stages of pregnancy and breastfeeding impact infant brain development; (2) to discuss multimodal MRI and other measures of early neurodevelopment; and (3) to discuss potential opportunities for data science and artificial intelligence to advance precision nutrition. We hope this review can facilitate the collaborative march toward precision nutrition during pregnancy and the first year of life.
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Affiliation(s)
- Sarah U Morton
- Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States.,Department of Pediatrics, Harvard Medical School, Boston, MA, United States
| | | | - Eleonora Tamilia
- Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States.,Department of Pediatrics, Harvard Medical School, Boston, MA, United States
| | - Rutvi Vyas
- Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States
| | - Michaela Sisitsky
- Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States
| | - Imran Ladha
- Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States
| | | | | | - P Ellen Grant
- Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States.,Department of Pediatrics, Harvard Medical School, Boston, MA, United States.,Department of Radiology, Boston Children's Hospital, Boston, MA, United States
| | - Yangming Ou
- Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States.,Department of Pediatrics, Harvard Medical School, Boston, MA, United States.,Department of Radiology, Boston Children's Hospital, Boston, MA, United States
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Yu B, Huang C, Liu S, Li T, Guan Y, Zheng X, Ding J. Application of first-order feature analysis of DWI-ADC in rare malignant mesenchymal tumours of the maxillofacial region. BMC Oral Health 2021; 21:463. [PMID: 34556116 PMCID: PMC8459531 DOI: 10.1186/s12903-021-01835-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 09/16/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To research the first-order features of apparent diffusion coefficient (ADC) values on diffusion-weighted magnetic resonance imaging (DWI) in maxillofacial malignant mesenchymal tumours. METHODS The clinical data of 12 patients with rare malignant mesenchymal tumours of the maxillofacial region (6 cases of sarcoma and 6 cases of lymphoma) treated in the hospital from May 2018 to June 2020 and were confirmed by postoperative pathology were retrospectively analyzed. The patients were all examined by 1.5T magnetic resonance imaging. PyRadiomics were used to extract radiomics imaging first-order features. Group differences in quantitative variables were examined using independent-samples t-tests. RESULTS The voxels number of ADCmean and ADCmedian of sarcoma tissues were 44.9124 and 44.2064, respectively, significantly higher than those in lymphoma tissues (ADCmean (- 68.8379) and ADCmedian (- 74.0045)), the difference considered statistically significant, so do the ADCkurt and ADCskew. CONCLUSIONS The statistical difference of ADCmean and ADCmedian is significant, it is consistent with the outcome of the manual measurement of the ADC mean value of the most significant cross-section of twelve cases of lymphoma. Development of tumour volume based on the ADC parameter map of DWI demonstrates that the first-order ADC radiomics features analysis can provide new imaging markers for the differentiation of maxillofacial sarcoma and lymphoma. Therefore, first-order ADC features of ADCkurt combined ADCskew may improve the diagnosis level.
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Affiliation(s)
- Baoting Yu
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Chencui Huang
- Department of Research Collaboration, R&D Center, Beijing Deepwise and League of PHD Technology Co. Ltd., Beijing, 100080, China
| | - Shuo Liu
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Tong Li
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Yuyao Guan
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Xuewei Zheng
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China
| | - Jun Ding
- Department of Radiology, China-Japan Union Hospital of Jilin University, No. 829 of Xinmin Street, Chaoyang District, Changchun, 130021, China.
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Extension of Healthy Life Span of Dialysis Patients in the Era of a 100-Year Life. Nutrients 2021; 13:nu13082693. [PMID: 34444853 PMCID: PMC8400994 DOI: 10.3390/nu13082693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 07/30/2021] [Indexed: 12/11/2022] Open
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