Evidence map›Paper›PMID 40379950›Full record

ArticleJournal of autism and developmental disorders2025

Making a Case for an Autism-Specific Multimorbidity Index: A Comparative Cohort Study.

Dewy Nijhof, Filip Sosenko, Laura McKernan Ward, Deborah Cairns, Laura Hughes, Ewelina Rydzewska

Abstract read
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In one paragraph

Article in Journal of autism and developmental disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Dewy Nijhof *School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom. dewy.nijhof@glasgow.ac.uk.ORCID http://orcid.org/0000-0003-4846-3242
Filip Sosenko *School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.ORCID http://orcid.org/0000-0002-0557-173X
Laura McKernan WardHealth Informatics Centre, School of Medicine, Ninewells Hospital, University of Dundee, Dundee, DD1 9SY, United Kingdom.ORCID http://orcid.org/0000-0003-0880-0662
Deborah CairnsSchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.ORCID http://orcid.org/0000-0002-2626-1554
Laura HughesSchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.ORCID http://orcid.org/0000-0001-9498-8045
Ewelina RydzewskaSchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.ORCID http://orcid.org/0000-0002-9749-3133

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autistic people experience challenges in healthcare, including disparities in health outcomes and multimorbidity patterns distinct from the general population. This study investigated the efficacy of existing multimorbidity indices in predicting COVID- 19 mortality among autistic adults and proposes a bespoke index, the ASD-MI, tailored to their specific health profile. Using data from the CVD-COVID-UK/COVID-IMPACT Consortium, encompassing England's entire population, we identified 1,027 autistic adults hospitalized for COVID- 19, among whom 62 died due to the virus. Predictors were selected using logistic regression with fivefold cross-validation, comparing AUCs amongst multimorbidity indices. Diabetes, coronary heart disease, and thyroid disorders were selected as predictors for the ASD-MI, outperforming the Quan Index, a general population-based measure, with an AUC of 0.872 versus 0.828, respectively. Notably, the ASD-MI exhibited better model fit (pseudo-R2 0.25) compared to the Quan Index (pseudo-R2 0.20). These findings underscore the need for tailored indices in predicting mortality risks among autistic individuals. However, caution is warranted in interpreting results, given the limited understanding of morbidity burden in this population. Further research is needed to refine autism-specific indices and elucidate the complex interplay between long-term conditions and mortality risk, informing targeted interventions to address health disparities in autistic adults. This study highlights the importance of developing healthcare tools tailored to the unique needs of neurodivergent populations to improve health outcomes and reduce disparities.

Indexed as

Autism Spectrum DisorderCOVID- 19Long-term ConditionsMortalityMultimorbidityMultimorbidity Index

Identifiers

PMID40379950

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.