A critical view of the use of predictive energy equations for the identification of hypermetabolism in motor neuron disease : a pilot study

Background and Aims People living with motor neuron disease (MND) frequently struggle to consume an optimal caloric intake. Often compounded by hypermetabolism, this can lead to dysregulated energy homeostasis, prompting the onset of malnutrition and associated weight loss. This is associated with a poorer prognosis and reduced survival. It is therefore important to establish appropriate nutritional goals to ensure adequate energy intake. This is best done by measuring resting energy expenditure (mREE) using indirect calorimetry. However, indirect calorimetry is not widely available in clinical practice, thus dietitians caring for people living with MND frequently use energy equations to predict resting energy expenditure (pREE) and estimate caloric requirements. Energy prediction equations have previously been shown to underestimate resting energy expenditure in over two-thirds of people living with MND. Hypermetabolism has previously been identified using the metabolic index. The metabolic index is a ratio of mREE to pREE, whereby an increase of mREE by ≥ 110% indicates hypermetabolism. We aim to critically reflect on the use of the Harris-Benedict (1919) and Henry (2005) energy prediction equations to inform a metabolic index to indicate hypermetabolism in people living with MND. Methods mREE was derived using VO₂ and VCO₂ measurements from a GEMNutrition indirect calorimeter. pREE was estimated by Harris-Benedict (HB) (1919), Henry (2005) and kcal/kg/day predictive energy equations. The REE variation, described as the percentage difference between mREE and pREE, determined the accuracy of pREE ([pREE-mREE]/mREE) x 100), with accuracy defined as ≤ ± 10%. A metabolic index threshold of ≥ 110% was used to classify hypermetabolism. All resting energy expenditure data are presented as kcal/24hr. Results Sixteen people living with MND were included in the analysis. The mean mREE was 1642 kcal/24hr ranging between 1110 and 2015 kcal/24hr. When REE variation was analysed for the entire cohort, the HB, Henry and kcal/kg/day equations all overestimated REE, but remained within the accuracy threshold (mean values were 2.81% for HB, 4.51% for Henry and 8.00% for kcal/kg/day). Conversely, inter-individual REE variation within the cohort revealed HB and Henry equations both inaccurately reflected mREE for 68.7% of participants, with kcal/kg/day inaccurately reflecting 41.7% of participants. Whilst the overall cohort was not classified as hypermetabolic (mean values were 101.04% for HB, 98.62% for Henry and 95.64% for kcal/kg/day), the metabolic index ranges within the cohort were 70.75% - 141.58% for HB, 72.82% - 127.69% for Henry and 66.09% – 131.58% for kcal/kg/day, indicating both over- and under-estimation of REE by these equations. We have shown that pREE correlates with body weight (kg), whereby the lighter the individual, the greater the underprediction of REE. When applied to the metabolic index, this underprediction biases towards the classification of hypermetabolism in lighter individuals. Conclusion Whilst predicting resting energy expenditure using the HB, Henry or kcal/kg/day equations accurately reflects derived mREE at group level, these equations are not suitable for informing resting energy expenditure and classification of hypermetabolism when applied to individuals in clinical practice

Impact of the covid-19 pandemic on amyotrophic lateral sclerosis care in the UK

The Covid-19 pandemic has impacted healthcare. Our aim was to identify how amyotrophic lateral sclerosis (ALS) care in the UK has been affected by the pandemic by exploring the experiences of people living with ALS (plwALS), healthcare professionals (HCPs) working with plwALS, and ALS care centers. Three surveys were carried out to explore the experiences of plwALS, HCPs and ALS care centers during the pandemic. Quantitative data were analyzed using descriptive and inferential statistics and triangulated with the qualitative data which were analyzed thematically. Responses from 53 plwALS, 73 HCPs and 23 ALS care centers were analyzed. Five main themes were identified: keeping safe, losses, negative emotions, delivering care and alternative care delivery in a pandemic. PlwALS and HCPs felt that care was sub-optimal as a result of the pandemic. Changes to care included longer waiting times and face-to-face appointments being canceled or replaced by virtual consultations. While benefits of virtual consultations were reported, concerns were raised about incomplete clinical assessments and the disruption of provision of testing and interventions. ALS care has changed as a result of the pandemic. Patients have had a lack of face-to-face contact with HCPs and have experienced delays to investigations and treatments. PlwALS and HCPs were concerned about the impact of this change, but the long-term implications remain unclear. We propose recommendations for HCPs caring for plwALS, that will promote continuity of evidenced based care in the context of a pandemic

The Primary Care Memory Assessment Pathway (MAP): a Narrative Summary of Best Practice and Uncertainties

This document will act as a narrative summary of best practice and uncertainties in the primary care memory assessment pathway (MAP) in the UK. The MAP refers to the process of assessing a patient with memory concerns from initial consultation, typically in a primary care setting, until diagnosis is reached. It is separate from the medical care offered to patients with dementia. This article will review national and local guidance in addition to relevant literature in order to summarise current issues and potential future directions. It will form the basis of the topic guide for a qualitative study with GPs on this topic, intended to inform the implementation of a digital screening tool (CognoSpeak).</p

A critical view of the use of predictive energy equations for the identification of hypermetabolism in motor neuron disease: a pilot study

Background and aims: people living with motor neuron disease (MND) frequently struggle to consume an optimal caloric intake. Often compounded by hypermetabolism, this can lead to dysregulated energy homeostasis, prompting the onset of malnutrition and associated weight loss. This is associated with a poorer prognosis and reduced survival. It is therefore important to establish appropriate nutritional goals to ensure adequate energy intake. This is best done by measuring resting energy expenditure (mREE) using indirect calorimetry. However, indirect calorimetry is not widely available in clinical practice, thus dietitians caring for people living with MND frequently use energy equations to predict resting energy expenditure (pREE) and estimate caloric requirements. Energy prediction equations have previously been shown to underestimate resting energy expenditure in over two-thirds of people living with MND. Hypermetabolism has previously been identified using the metabolic index. The metabolic index is a ratio of mREE to pREE, whereby an increase of mREE by !110% indicates hypermetabolism. We aim to critically reflect on the use of the Harris-Benedict (1919) and Henry (2005) energy prediction equations to inform a metabolic index to indicate hypermetabolism in people living with MND.Methods: mREE was derived using VO2 and VCO2 measurements from a GEMNutrition indirect calo- rimeter. pREE was estimated by Harris-Benedict (HB) (1919), Henry (2005) and kcal/kg/day predictive energy equations. The REE variation, described as the percentage difference between mREE and pREE, determined the accuracy of pREE ([pREE-mREE]/mREE) x 100), with accuracy defined as ± 10%. A metabolic index threshold of !110% was used to classify hypermetabolism. All resting energy expendi- ture data are presented as kcal/24hr.Results: sixteen people living with MND were included in the analysis. The mean mREE was 1642 kcal/ 24hr ranging between 1110 and 2015 kcal/24hr. When REE variation was analysed for the entire cohort, the HB, Henry and kcal/kg/day equations all overestimated REE, but remained within the accuracy threshold (mean values were 2.81% for HB, 4.51% for Henry and 8.00% for kcal/kg/day). Conversely, inter- individual REE variation within the cohort revealed HB and Henry equations both inaccurately reflected mREE for 68.7% of participants, with kcal/kg/day inaccurately reflecting 41.7% of participants. Whilst the overall cohort was not classified as hypermetabolic (mean values were 101.04% for HB, 98.62% for Henry and 95.64% for kcal/kg/day), the metabolic index ranges within the cohort were 70.75%e141.58% for HB, 72.82%e127.69% for Henry and 66.09%e131.58% for kcal/kg/day, indicating both over- and under- estimation of REE by these equations. We have shown that pREE correlates with body weight (kg), whereby the lighter the individual, the greater the underprediction of REE. When applied to the metabolic index, this underprediction biases towards the classification of hypermetabolism in lighter individuals.Conclusion: whilst predicting resting energy expenditure using the HB, Henry or kcal/kg/day equations accurately reflects derived mREE at group level, these equations are not suitable for informing resting energy expenditure and classification of hypermetabolism when applied to individuals in clinical practice

A critical view of the use of predictive energy equations for the identification of hypermetabolism in motor neuron disease

Background and Aims People living with motor neuron disease (MND) frequently struggle to consume an optimal caloric intake. Often compounded by hypermetabolism, this can lead to dysregulated energy homeostasis, prompting the onset of malnutrition and associated weight loss. This is associated with a poorer prognosis and reduced survival. It is therefore important to establish appropriate nutritional goals to ensure adequate energy intake. This is best done by measuring resting energy expenditure (mREE) using indirect calorimetry. However, indirect calorimetry is not widely available in clinical practice, thus dietitians caring for people living with MND frequently use energy equations to predict resting energy expenditure (pREE) and estimate caloric requirements. Energy prediction equations have previously been shown to underestimate resting energy expenditure in over two-thirds of people living with MND. Hypermetabolism has previously been identified using the metabolic index. The metabolic index is a ratio of mREE to pREE, whereby an increase of mREE by ≥ 110% indicates hypermetabolism. We propose that the use of energy prediction equations to inform a metabolic index to indicate hypermetabolism in people living with MND is inappropriate and results in a biased identification of hypermetabolism in lighter individuals. Methods mREE was derived using VO2 and VCO2 measurements from a GEMNutrition indirect calorimeter. pREE was estimated by Harris-Benedict (HB) (1919), Henry (2005) and kcal/kg/day predictive energy equations. The REE variation, described as the percentage difference between mREE and pREE, determined the accuracy of pREE ([pREE-mREE]/mREE) x 100), with accuracy defined as ≤ ± 10%. A metabolic index threshold of ≥ 110% was used to classify hypermetabolism. All resting energy expenditure data are presented as kcal/24hr. Results Sixteen people living with MND were included in the analysis. The mean mREE was 1642 kcal/24hr ranging between 1110 and 2015 kcal/24hr. When REE variation was analysed for the entire cohort, the HB, Henry and kcal/kg/day equations all overestimated REE, but remained within the accuracy threshold (mean values were 2.81% for HB, 4.51% for Henry and 8.00% for kcal/kg/day). Conversely, inter-individual REE variation within the cohort revealed HB and Henry equations both inaccurately reflected mREE for 68.7% of participants, with kcal/kg/day inaccurately reflecting 41.7% of participants. Whilst the overall cohort was not classified as hypermetabolic (mean values were 101.04% for HB, 98.62% for Henry and 95.64% for kcal/kg/day), the metabolic index ranges within the cohort were 70.75% - 141.58% for HB, 72.82% - 127.69% for Henry and 66.09% – 131.58% for kcal/kg/day, indicating both over- and under-estimation of REE by these equations. We have shown that pREE correlates with body weight (kg), whereby the lighter the individual, the greater the underprediction of REE. When applied to the metabolic index, this underprediction biases towards the classification of hypermetabolism in lighter individuals. Conclusion Whilst predicting resting energy expenditure using the HB, Henry or kcal/kg/day equations accurately reflects derived mREE at group level, these equations are not suitable for informing resting energy expenditure and classification of hypermetabolism when applied to individuals in clinical practice

The nutritional management of people living with amyotrophic lateral sclerosis:A national survey of dietitians

Background People living with amyotrophic lateral sclerosis (ALS) face many challenges with respect to taking adequate nutrition. Growing evidence links weight loss with negative prognostic outcomes. We aimed to explore the practice of dietitians in the UK with regard to the nutritional management of ALS. Methods A national online survey was disseminated via professional groups, social media and newsletters to UK healthcare professionals between September and November 2018. The survey examined the nutritional management of ALS. Dietitian responses are reported in the present study. Results In total, 130 dietitians responded to the survey. Two-thirds reported that ALS comprised less than 20% of their total patient caseload. Forty-two percent reported that nutritional screening took place in their organisation. One-half of dietitians reported that patients were referred for dietetic assessment at ‘about the right time’, although 44% reported referrals were made too late. The majority (83%) of dietitians used resting energy expenditure predictive equations not validated in ALS. When setting weight goals, dietitians reported most frequently recommending weight maintenance if the patient’s body mass index was 18.5–25 kg m−2 (72%), 25–30 kg m−2 (98%), and > 30 kg m−2 (79%). In addition, 43% reported that people with ALS were not weighed sufficiently frequently. Conclusions Although the importance of early nutritional assessment is recognised, the timeliness of dietetic input and on-going monitoring of nutritional status in ALS care might not currently be ideal. Dietitians report using energy requirement predictive equations and setting weight goals that may not promote positive outcomes. Further research is required to understand the optimal nutritional management of ALS

Health care professionals’ views on psychological factors affecting nutritional behaviour in people with motor neuron disease: A thematic analysis

Motor neuron disease (MND), also known as amyotrophic lateral sclerosis, is a neurodegenerative disorder that causes progressive muscle paralysis and typically leads to death within 3 years. As no cure is currently available, symptomatic management is the mainstay of treatment. An important part of this is optimizing nutritional intake with evidence that this may positively affect survival and quality of life. Health care professionals (HCPs) play a pivotal role in nutritional management of people with MND (pwMND) but, to date, their views on the psychological barriers faced by pwMND have not been explored. Such an exploration may identify ways in which the delivery of nutritional care for pwMND can be optimized. Methods Five qualitative focus groups were carried out across the United Kingdom in June 2018 with 51 participants, including 47 HCPs involved with MND care and four service user representatives. Data were analysed through thematic analysis. Results Four overarching themes were identified: psychological adjustment and patient engagement; nutrition and the need for control; knowledge of nutrition and the complexity of MND; and the psychosocial nature of eating. Conclusions The findings suggest that the nutritional management of pwMND should be mindful of factors such as the impact of distress at the time of diagnosis, the availability of clear information on nutrition and MND, as well as the importance of illness perceptions and coping strategies. Moreover, tailored psychological interventions should be considered to mitigate the impact on MND on the experience of eating