The complexity of multidisciplinary respiratory care in amyotrophic lateral sclerosis

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

The complexity of multidisciplinary respiratory care in amyotrophic lateral sclerosis.

UNLABELLED: 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

The importance of 'memory' in statistical models for animal feeding behaviour

We investigate models for animal feeding behaviour, with the aim of improving understanding of how animals organise their behaviour in the short term. We consider three classes of model: latent Gaussian, hidden Markov and semi-Markov. Each can predict the typical `clustered ' feeding behaviour that is generally observed, however they dier in the extent to which `memory ' of previous behaviour is allowed to aect future behaviour. The hidden Markov model has `lack of memory', the current behavioural state being dependent on the previous state only. The latent Gaussian model assumes feeding/non-feeding periods to occur by the thresholding of an underlying continuous variable, incorporating some `short-term memory'. The semi-Markov model, by taking into account the duration of time spent in the previous state, can be said to incorporate `longer-term memory'. We t each of these models to a dataset of cow feeding behaviour. We nd the semi-Markov model (longer-term memory) to have the best t to the data and the hidden Markov (lack of memory) model the worst. We argue that in view of eects of satiety on short-term feeding behaviour of animal species in general, biologically suitable models should allow `memory ' to play a role. We conclude that our ndings are equally relevant for the analysis of other types of short-term behaviour that are governed by satiety-like principles