Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterised mainly by differences in social communication and interaction and repetitive and restrictive behaviours, including differences in sensory preferences. Autistic people are estimated to account for 0.6 to 1.0% of the global population. They experience substantial health inequalities, including multimorbidity, defined as the association of at least two chronic health conditions. ASD has been proposed as a potential risk factor for the development of COVID-19 infections due to a number of factors including experiencing difficulties in maintaining social distancing due to sensory difficulties and use of atypical antipsychotics, such as risperidone, frequently prescribed to individuals with ASD, which have been shown to disrupt immune responses, and therefore increase the risk of COVID infection and mortality.
People with autism have a different pattern of multimorbidity compared to the general population which in turn can affect their lifespan/mortality. What is more, literature suggests that autistic people are likely to experience poor physical health, multimorbidity, and premature mortality, making it even more important to capture the full multimorbidity burden in order to detect poor health and provide suitable care.
Multimorbidity indices, which are used to predict the prognosis of patients based on their medical history or to measure the comorbidity burden, are currently based on the general population, and therefore may not accurately pick up on conditions affecting mortality in autistic adults or may have the right conditions but assign them weights that are incorrect for the autistic population. Multimorbidity indices use previous and current diagnoses as predictors for the outcome of interest, such as quality of life, hospital admissions, healthcare use, and mortality. Alternatively, the list is used to control for long-term conditions or multimorbidity (the presence of two or more long-term health conditions) while studying other associations.
A variety of multimorbidity indices exist, and characteristics amongst these instruments vary in terms of included conditions, weighting of conditions and even outcome measures. The most used and well-known index is the Charlson Comorbidity Index (CCI) which uses scores for 17 long-term conditions to predict the ten-year risk of death within one year after hospital admission. Since its conception, several modifications of the CCI have been created, ranging in selection of conditions, number of diseases included, weights of individual conditions and overall score construction. The most well-known modifications include the Elixhauser Index (including 30 – or, for some variants, 31 – comorbidities) and the van Walraven (VW) variant of the Elixhauser Index, which includes a weighted summary score for streamlined use, based on the 30 comorbidities from the Elixhauser Index.
Most indices use scores to estimate prognosis, with higher scores usually being indicative of more severe risk of death. These scores are usually additive, where the presence of multiple conditions will lead to a higher score. Scores are based on weights for each condition, which usually are derived from the modelling of the risk, in which the weight quantifies their contribution towards the outcome. The long history of development and validation of these instruments has resulted in establishing strong evidence of associations between the coexistence of multiple long-term conditions and mortality risk, decline in physical and mental functioning, and quality of life. However, less research has focused on the selection criteria for inclusion of conditions and most indices are constructed for the general population.
This may be of importance for the autistic population, as common physical and mental comorbidities differ from those in the general population. Therefore, the effectiveness and sensitivity of the established multimorbidity indices for the prediction of health outcomes in the autistic population and subsequent treatment based on those predictions warrants an investigation into their validity. Indeed, studies examining the association between health comorbidities and mortality in autism make use of established multimorbidity indices, such as the CCI, but include health conditions known to be prevalent in the autistic population. These studies found that the included health conditions, such as epilepsy, mental health conditions (e.g., bipolar disorder, schizophrenia, major depressive disorder) or intellectual disabilities carried higher risk of death in the autistic population. This suggests that traditional indices may not accurately reflect the health profile or capture the full extent of multimorbidity and its concurrent risk for the autistic population.
To our knowledge, there has been no previous research into the effectiveness of using existing multimorbidity indices to investigate health outcomes in autism nor the construction of a multimorbidity index for autistic populations specifically. As such, the current study aimed to create a multimorbidity index which better captures long-term conditions presenting a risk to the health of the autistic population and to pilot this index in the context of COVID-19 outcomes in this population.
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- View the analysis code used in NHS England's SDE for England
- View the phenotyping algorithms and codelists used in NHS England's SDE for England
This is a sub-project of project CCU030 approved by the CVD-COVID-UK / COVID-IMPACT Approvals & Oversight Board (sub-project: CCU030_03).
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