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Holdom CJ, Janse van Mantgem MR, He J, Howe SL, McCombe PA, Fan D, van den Berg LH, Henderson RD, van Eijk R, Steyn FJ, Ngo ST. Variation in Resting Metabolic Rate Affects Identification of Metabolic Change in Geographically Distinct Cohorts of Patients With ALS. Neurology 2024; 102:e208117. [PMID: 38350046 DOI: 10.1212/wnl.0000000000208117] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 11/16/2023] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Altered metabolism is observed in amyotrophic lateral sclerosis (ALS). However, without a standardized methodology to define metabolic changes, our understanding of factors contributing to and the clinical significance of altered metabolism in ALS is limited. METHODS We aimed to determine how geographic variation in metabolic rates influences estimates and accuracy of predicted resting energy expenditure (REE) in patients with ALS and controls, while validating the effectiveness of cohort-specific approaches in predicting altered metabolic rate in ALS. Participants from 3 geographically distinct sites across Australia, China, and the Netherlands underwent REE assessments, and we considered 22 unique equations for estimating REE. Analyses evaluated equation performance and the influence of demographics on metabolic status. Comparisons were made using standardized and local reference values to identify metabolic alterations. RESULTS 606 participants were included from Australia (patients with ALS: 140, controls: 154), the Netherlands (patients with ALS: 79, controls: 37) and China (patients with ALS: 67, controls: 129). Measured REE was variable across geographic cohorts, with fat-free mass contributing to this variation across all patients (p = 0.002 to p < 0.001). Of the 22 predication equations assessed, the Sabounchi Structure 4 (S4) equation performed relatively well across all control cohorts. Use of prediction thresholds generated using data from Australian controls generally increased the prevalence of hypermetabolism in Chinese (55%, [43%-67%]) and Dutch (44%, [33%-55%]) cases when compared with Australian cases (30%, [22%-38%]). Adjustment of prediction thresholds to consider geographically distinct characteristics from matched control cohorts resulted in a decrease in the proportion of hypermetabolic cases in Chinese and Dutch cohorts (25%-31% vs 55% and 20%-34% vs 43%-44%, respectively), and increased prevalence of hypometabolism in Dutch cases with ALS (1% to 8%-10%). DISCUSSION The identification of hypermetabolism in ALS is influenced by the formulae and demographic-specific prediction thresholds used for defining alterations in metabolic rate. A consensus approach is needed for identification of metabolic changes in ALS and will facilitate improved understanding of the cause and clinical significance of this in ALS.
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Affiliation(s)
- Cory J Holdom
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Mark R Janse van Mantgem
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Ji He
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Stephanie L Howe
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Pamela A McCombe
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Dongsheng Fan
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Leonard H van den Berg
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Robert D Henderson
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Ruben van Eijk
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Frederik J Steyn
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
| | - Shyuan T Ngo
- From the Australian Institute for Bioengineering and Nanotechnology (C.J.H., S.L.H., S.T.N.), The University of Queensland, Australia; Department of Neurology (M.R.J.M., R.P.A.E., L.H.B.), UMC Utrecht Brain Centre, University Medical Centre Utrecht, The Netherlands; Department of Neurology (D.F.), Peking University Third Hospital; Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases (D.F.), China; Centre for Clinical Research (P.A.M., R.D.H., F.J.S., S.T.N.), The University of Queensland; Department of Neurology (P.A.M., R.D.H., F.J.S., S.T.N.), Royal Brisbane and Women's Hospital, Australia; Biostatistics and Research Support (R.P.A.E.), Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands; and School of Biomedical Sciences (F.J.S.), The University of Queensland, Australia
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Berlowitz DJ, Mathers S, Hutchinson K, Hogden A, Carey KA, Graco M, Whelan BM, Charania S, Steyn F, Allcroft P, Crook A, Sheers NL. The complexity of multidisciplinary respiratory care in amyotrophic lateral sclerosis. Breathe (Sheff) 2023; 19:220269. [PMID: 37830099 PMCID: PMC10567075 DOI: 10.1183/20734735.0269-2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/20/2023] [Indexed: 10/14/2023] Open
Abstract
Motor neurone disease/amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder with no known cure, where death is usually secondary to progressive respiratory failure. Assisting people with ALS through their disease journey is complex and supported by clinics that provide comprehensive multidisciplinary care (MDC). This review aims to apply both a respiratory and a complexity lens to the key roles and areas of practice within the MDC model in ALS. Models of noninvasive ventilation care, and considerations in the provision of palliative therapy, respiratory support, and speech and language therapy are discussed. The impact on people living with ALS of both inequitable funding models and the complexity of clinical care decisions are illustrated using case vignettes. Considerations of the impact of emerging antisense and gene modifying therapies on MDC challenges are also highlighted. The review seeks to illustrate how MDC members contribute to collective decision-making in ALS, how the sum of the parts is greater than any individual care component or health professional, and that the MDC per se adds value to the person living with ALS. Through this approach we hope to support clinicians to navigate the space between what are minimum, guideline-driven, standards of care and what excellent, person-centred ALS care that fully embraces complexity could be. Educational aims To highlight the complexities surrounding respiratory care in ALS.To alert clinicians to the risk that complexity of ALS care may modify the effectiveness of any specific, evidence-based therapy for ALS.To describe the importance of person-centred care and shared decision-making in optimising care in ALS.
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Affiliation(s)
- David J. Berlowitz
- The University of Melbourne, Parkville, Australia
- Institute for Breathing and Sleep, Heidelberg, Australia
- Department of Physiotherapy, Austin Health, Heidelberg, Australia
- Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Australia
| | - Susan Mathers
- Calvary Health Care Bethlehem, Caulfield South, Australia
- School of Clinical Sciences, Monash University, Clayton, Australia
| | - Karen Hutchinson
- Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
- Central Coast Local Health District, Gosford, Australia
| | - Anne Hogden
- School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
| | - Kate A. Carey
- The University of Melbourne, Parkville, Australia
- Institute for Breathing and Sleep, Heidelberg, Australia
| | - Marnie Graco
- The University of Melbourne, Parkville, Australia
- Institute for Breathing and Sleep, Heidelberg, Australia
| | - Brooke-Mai Whelan
- School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia
| | - Salma Charania
- Motor Neurone Disease Association of Queensland, Oxley, Australia
| | - Frederik Steyn
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Peter Allcroft
- Southern Adelaide Palliative Services, Flinders Medical Centre, Bedford Park, Australia
- College of Medicine and Public Health, Flinders University, Bedford Park, Australia
| | - Ashley Crook
- Graduate School of Health, University of Technology Sydney, Chippendale, Australia
- Centre for MND Research and Department of Clinical Medicine, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
| | - Nicole L. Sheers
- The University of Melbourne, Parkville, Australia
- Institute for Breathing and Sleep, Heidelberg, Australia
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Barone M, Leo AD, de van der Schueren MAE. Malnutrition assessment by Global Leadership Initiative on Malnutrition criteria in patients with amyotrophic lateral sclerosis. Nutrition 2023; 109:111997. [PMID: 36905838 DOI: 10.1016/j.nut.2023.111997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 01/15/2023] [Accepted: 02/03/2023] [Indexed: 02/12/2023]
Abstract
Malnutrition can play an important prognostic role in terms of survival in patients with amyotrophic lateral sclerosis (ALS). In this clinical context, applying criteria defining malnutrition requires particular attention, especially in the initial stage of the disease. This article discusses the application of the most recent criteria used for the definition of malnutrition when applied to patients with ALS. Currently, the Global Leadership Initiative on Malnutrition (GLIM) criteria, which have received a worldwide consensus, are based on parameters such as unintentional weight loss, low body mass index (BMI), and reduced muscle mass (phenotypic criteria) in combination with reduced food intake and assimilation or inflammation and disease (etiologic criteria). However, as discussed in this review, the initial unintentional weight loss and the consequent BMI reduction could be attributed, at least in part, to muscle atrophy, which also alters the reliability of muscle mass assessment. Moreover, the condition of hypermetabolism, which is observed in up to 50% of these patients, may complicate the calculation of total energy requirements. Finally, it remains to be established if the presence of neuroinflammation can be considered a type of inflammatory process able to induce malnutrition in these patients. In conclusion, the monitoring of BMI, associated with body composition evaluation by bioimpedance measurement or specific formulas, could be a practicable approach to the diagnosis of malnutrition in patients with ALS. In addition, attention should be given to dietary intake (e.g., in patients with dysphagia) and excessive involuntary weight loss. On the other hand, as suggested by GLIM criteria, a single assessment of BMI resulting in <20 kg/m2 or <22 kg/m2 in patients aged <70 y and ≥70 y, respectively, should always be considered a sign of malnutrition.
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Affiliation(s)
- Michele Barone
- Gastroenterology Unit, Department of Emergency and Organ Transplantation, University "Aldo Moro" of Bari, Bari, Italy.
| | - Alfredo Di Leo
- Gastroenterology Unit, Department of Emergency and Organ Transplantation, University "Aldo Moro" of Bari, Bari, Italy
| | - Marian A E de van der Schueren
- Department of Nutrition, Dietetics and Lifestyle, HAN University of Applied Sciences, School of Allied Health, Nijmegen, the Netherlands; Department of Human Nutrition and Health, Wageningen University and Research, Wageningen, the Netherlands
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Fayemendy P, Marin B, Labrunie A, Boirie Y, Walrand S, Achamrah N, Coëffier M, Preux PM, Lautrette G, Desport JC, Couratier P, Jésus P. Hypermetabolism is a reality in amyotrophic lateral sclerosis compared to healthy subjects. J Neurol Sci 2020; 420:117257. [PMID: 33290920 DOI: 10.1016/j.jns.2020.117257] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/08/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
RATIONALE Hypermetabolism (HM) in Amyotrophic lateral sclerosis (ALS) is the reflection of a high energy metabolic level, but this alteration seems controversial. The main objective of the study was to confirm the existence of HM during ALS compared to healthy subjects. METHODS A cohort of ALS patients was compared to a control group without metabolic disorder. The assessment included anthropometric criteria measurements, body composition by bioelectric impedance analysis and resting energy expenditure (REE) by indirect calorimetry. HM was defined as a variation > +10% between measured and calculated REE. Statistical analysis used Mann-Withney and Chi2 tests. Multivariate analysis included logistic regression. RESULTS 287 patients and 75 controls were included. The metabolic level was higher in ALS patients (1500 kcal/24 h [1290-1693] vs. 1230 kcal/24 h [1000-1455], p < 0.0001) as well as the REE/fat free mass ratio (33.5 kcal/kg/24 h [30.4-37.8] vs. 28.3 kcal/kg/24 h [26.1-33.6], p < 0.0001). 55.0% of ALS patients had HM vs. 13.3% of controls (p < 0.0001). HM was strongly and positively associated with ALS (OR = 9.50 [4.49-20.10], p < 0.0001). CONCLUSIONS HM in ALS is a reality, which affects more than half of the patients and is associated with ALS. This work confirms a very frequent metabolic deterioration during ALS. The identification of HM can allow a better adaptation of the patients' nutritional intake.
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Affiliation(s)
- Philippe Fayemendy
- Nutrition Unit, University Hospital of Limoges, Limoges, France; INSERM UMR 1094, Tropical Neuroepidemiology, Limoges, France.
| | - Benoit Marin
- INSERM UMR 1094, Tropical Neuroepidemiology, Limoges, France; Center for Epidemiology, Biostatistics and Methodology of Research, University Hospital of Limoges, France
| | - Anaïs Labrunie
- Center for Epidemiology, Biostatistics and Methodology of Research, University Hospital of Limoges, France
| | - Yves Boirie
- University Clermont Auvergne, INRA, UNH, Human Nutrition Unit, CRNH Auvergne, Clermont-Ferrand, France
| | - Stéphane Walrand
- University Clermont Auvergne, INRA, UNH, Human Nutrition Unit, CRNH Auvergne, Clermont-Ferrand, France
| | | | | | - Pierre-Marie Preux
- INSERM UMR 1094, Tropical Neuroepidemiology, Limoges, France; Center for Epidemiology, Biostatistics and Methodology of Research, University Hospital of Limoges, France
| | | | - Jean-Claude Desport
- Nutrition Unit, University Hospital of Limoges, Limoges, France; INSERM UMR 1094, Tropical Neuroepidemiology, Limoges, France
| | - Philippe Couratier
- INSERM UMR 1094, Tropical Neuroepidemiology, Limoges, France; ALS center, University Hospital of Limoges, France
| | - Pierre Jésus
- Nutrition Unit, University Hospital of Limoges, Limoges, France; INSERM UMR 1094, Tropical Neuroepidemiology, Limoges, France
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