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Clinical signs associated with earlier diagnosis of children with autism Spectrum disorder.


ABSTRACT:

Background

The objective of this study is to gain new insights into the relationship between clinical signs and age at diagnosis.

Method

We utilize a new, large, online survey of 1743 parents of children diagnosed with ASD, and use multiple statistical approaches. These include regression analysis, factor analysis, and machine learning (regression tree).

Results

We find that clinical signs that most strongly predict early diagnosis are not necessarily specific to autism, but rather those that initiate the process that eventually leads to an ASD diagnosis. Given the high correlations between symptoms, only a few signs are found to be important in predicting early diagnosis. For several clinical signs we find that their presence and intensity are positively correlated with delayed diagnosis (e.g., tantrums and aggression). Even though our data are drawn from parents' retrospective accounts, we provide evidence that parental recall bias and/or hindsight bias did not play a significant role in shaping our results.

Conclusion

In the subset of children without early deficits in communication, diagnosis is delayed, and this might be improved if more attention will be given to clinical signs that are not necessarily considered as ASD symptoms. Our findings also suggest that careful attention should be paid to children showing excessive tantrums or aggression, as these behaviors may interfere with an early ASD diagnoses.

SUBMITTER: Sicherman N 

PROVIDER: S-EPMC7905573 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Clinical signs associated with earlier diagnosis of children with autism Spectrum disorder.

Sicherman Nachum N   Charite Jimmy J   Eyal Gil G   Janecka Magdalena M   Loewenstein George G   Law Kiely K   Lipkin Paul H PH   Marvin Alison R AR   Buxbaum Joseph D JD  

BMC pediatrics 20210225 1


<h4>Background</h4>The objective of this study is to gain new insights into the relationship between clinical signs and age at diagnosis.<h4>Method</h4>We utilize a new, large, online survey of 1743 parents of children diagnosed with ASD, and use multiple statistical approaches. These include regression analysis, factor analysis, and machine learning (regression tree).<h4>Results</h4>We find that clinical signs that most strongly predict early diagnosis are not necessarily specific to autism, bu  ...[more]

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