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Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.

Publication ,  Journal Article
Bishop-Fitzpatrick, L; Movaghar, A; Greenberg, JS; Page, D; DaWalt, LS; Brilliant, MH; Mailick, MR
Published in: Autism Res
August 2018

Very little is known about the health problems experienced by individuals with autism spectrum disorder (ASD) throughout their life course. We retrospectively analyzed diagnostic codes associated with de-identified electronic health records using a machine learning algorithm to characterize diagnostic patterns in decedents with ASD and matched decedent community controls. Participants were 91 decedents with ASD and 6,186 sex and birth year matched decedent community controls who had died since 1979, the majority of whom were middle aged or older adults at the time of their death. We analyzed all ICD-9 codes, V-codes, and E-codes available in the electronic health record and Elixhauser comorbidity categories associated with those codes. Diagnostic patterns distinguished decedents with ASD from decedent community controls with 75% sensitivity and 94% specificity solely based on their lifetime ICD-9 codes, V-codes, and E-codes. Decedents with ASD had higher rates of most conditions, including cardiovascular disease, motor problems, ear problems, urinary problems, digestive problems, side effects from long-term medication use, and nonspecific lab tests and encounters. In contrast, decedents with ASD had lower rates of cancer. Findings suggest distinctive lifetime diagnostic patterns among decedents with ASD and highlight the need for more research on health outcomes across the lifespan as the population of individuals with ASD ages. As a large wave of individuals with ASD diagnosed in the 1990s enters adulthood and middle age, knowledge about lifetime health problems will become increasingly important for care and prevention efforts. Autism Res 2018, 11: 1120-1128. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study looked at patterns of lifetime health problems to find differences between people with autism who had died and community controls who had died. People with autism had higher rates of most health problems, including cardiovascular, urinary, respiratory, digestive, and motor problems, in their electronic health records. They also had lower rates of cancer. More research is needed to understand these potential health risks as a large number of individuals with autism enter adulthood and middle age.

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Published In

Autism Res

DOI

EISSN

1939-3806

Publication Date

August 2018

Volume

11

Issue

8

Start / End Page

1120 / 1128

Location

United States

Related Subject Headings

  • Young Adult
  • Sensitivity and Specificity
  • Retrospective Studies
  • Prevalence
  • Middle Aged
  • Male
  • Machine Learning
  • Infant, Newborn
  • Infant
  • Humans
 

Citation

APA
Chicago
ICMJE
MLA
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Bishop-Fitzpatrick, L., Movaghar, A., Greenberg, J. S., Page, D., DaWalt, L. S., Brilliant, M. H., & Mailick, M. R. (2018). Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder. Autism Res, 11(8), 1120–1128. https://doi.org/10.1002/aur.1960
Bishop-Fitzpatrick, Lauren, Arezoo Movaghar, Jan S. Greenberg, David Page, Leann S. DaWalt, Murray H. Brilliant, and Marsha R. Mailick. “Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.Autism Res 11, no. 8 (August 2018): 1120–28. https://doi.org/10.1002/aur.1960.
Bishop-Fitzpatrick L, Movaghar A, Greenberg JS, Page D, DaWalt LS, Brilliant MH, et al. Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder. Autism Res. 2018 Aug;11(8):1120–8.
Bishop-Fitzpatrick, Lauren, et al. “Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.Autism Res, vol. 11, no. 8, Aug. 2018, pp. 1120–28. Pubmed, doi:10.1002/aur.1960.
Bishop-Fitzpatrick L, Movaghar A, Greenberg JS, Page D, DaWalt LS, Brilliant MH, Mailick MR. Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder. Autism Res. 2018 Aug;11(8):1120–1128.
Journal cover image

Published In

Autism Res

DOI

EISSN

1939-3806

Publication Date

August 2018

Volume

11

Issue

8

Start / End Page

1120 / 1128

Location

United States

Related Subject Headings

  • Young Adult
  • Sensitivity and Specificity
  • Retrospective Studies
  • Prevalence
  • Middle Aged
  • Male
  • Machine Learning
  • Infant, Newborn
  • Infant
  • Humans