Evidence map›Paper›PMID 38743420›Full record

ArticleJAMA network open2024

Eye-Tracking Biomarkers and Autism Diagnosis in Primary Care.

Brandon Keehn, Patrick Monahan, Brett Enneking, Tybytha Ryan, Nancy Swigonski, Rebecca McNally Keehn

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 4 pooled it
–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

19 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  16. Parent Perspectives on Mobile Health Autism Screeners.Journal of autism and developmental disorders · 2026
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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.

Brandon KeehnDepartment of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana.
Patrick MonahanDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis.
Brett EnnekingDepartment of Pediatrics, Indiana University School of Medicine, Indianapolis.
Tybytha RyanDepartment of Pediatrics, Indiana University School of Medicine, Indianapolis.
Nancy SwigonskiDepartment of Pediatrics, Indiana University School of Medicine, Indianapolis.
Rebecca McNally KeehnDepartment of Pediatrics, Indiana University School of Medicine, Indianapolis.

Funding

CTSA K12 Program at Indiana UniversityK12TR004415 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI SAMIR KUMAR GUPTA · 2023 to 2026
$3.4M
An innovative model of early ASD diagnosis in the primary care setting: Integrating clinical evaluation and biomarkers to improve diagnostic accuracyR21MH121747 · NIMH · INDIANA UNIVERSITY INDIANAPOLIS · PI KEEHN, BRANDON, MCNALLY KEEHN, REBECCA · 2020 to 2020
$435k
NCATS NIH HHS K12 TR004415NIMH NIH HHS R21 MH121747
6 · The paper itself

Abstract

Importance: Finding effective and scalable solutions to address diagnostic delays and disparities in autism is a public health imperative. Approaches that integrate eye-tracking biomarkers into tiered community-based models of autism evaluation hold promise for addressing this problem. Objective: To determine whether a battery of eye-tracking biomarkers can reliably differentiate young children with and without autism in a community-referred sample collected during clinical evaluation in the primary care setting and to evaluate whether combining eye-tracking biomarkers with primary care practitioner (PCP) diagnosis and diagnostic certainty is associated with diagnostic outcome. Design, Setting, and Participants: Early Autism Evaluation (EAE) Hub system PCPs referred a consecutive sample of children to this prospective diagnostic study for blinded eye-tracking index test and follow-up expert evaluation from June 7, 2019, to September 23, 2022. Participants included 146 children (aged 14-48 months) consecutively referred by 7 EAE Hubs. Of 154 children enrolled, 146 provided usable data for at least 1 eye-tracking measure. Main Outcomes and Measures: The primary outcomes were sensitivity and specificity of a composite eye-tracking (ie, index) test, which was a consolidated measure based on significant eye-tracking indices, compared with reference standard expert clinical autism diagnosis. Secondary outcome measures were sensitivity and specificity of an integrated approach using an index test and PCP diagnosis and certainty. Results: Among 146 children (mean [SD] age, 2.6 [0.6] years; 104 [71%] male; 21 [14%] Hispanic or Latine and 96 [66%] non-Latine White; 102 [70%] with a reference standard autism diagnosis), 113 (77%) had concordant autism outcomes between the index (composite biomarker) and reference outcomes, with 77.5% sensitivity (95% CI, 68.4%-84.5%) and 77.3% specificity (95% CI, 63.0%-87.2%). When index diagnosis was based on the combination of a composite biomarker, PCP diagnosis, and diagnostic certainty, outcomes were concordant with reference standard for 114 of 127 cases (90%) with a sensitivity of 90.7% (95% CI, 83.3%-95.0%) and a specificity of 86.7% (95% CI, 70.3%-94.7%). Conclusions and Relevance: In this prospective diagnostic study, a composite eye-tracking biomarker was associated with a best-estimate clinical diagnosis of autism, and an integrated diagnostic model including PCP diagnosis and diagnostic certainty demonstrated improved sensitivity and specificity. These findings suggest that equipping PCPs with a multimethod diagnostic approach has the potential to substantially improve access to timely, accurate diagnosis in local communities.

Indexed as

Autistic DisorderBiomarkersEye-Tracking TechnologyPrimary Health CareChild, PreschoolFemaleHumansInfantMaleProspective StudiesSensitivity and SpecificityBiomarkers

Identifiers

PMID38743420
PMCPMC11094561

What OpenQuestion holds

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LicenceCC BY
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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.