Evidence map›Paper›PMID 38712155›Full record

ArticlemedRxiv : the preprint server for health sciences2024

The clinical and genetic spectrum of paediatric speech and language disorders in 52,143 individuals.

Jan Magielski, Sarah M Ruggiero, Julie Xian, Shridhar Parthasarathy, Peter Galer, Shiva Ganesan, Amanda Back, Jillian McKee, Ian McSalley, Alexander K Gonzalez and 3 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. 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
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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

5 · Who and what money

Authors and funding

13 authors.

Jan MagielskiDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.ORCID 0000-0001-7290-4939
Sarah M RuggieroDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.ORCID 0000-0002-0834-0750
Julie XianDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.ORCID 0000-0002-0205-0648
Shridhar ParthasarathyDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Peter GalerDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Shiva GanesanDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Amanda BackDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Jillian McKeeDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Ian McSalleyDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Alexander K GonzalezDepartment of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, 19146, USA.
Angela MorganMurdoch Children's Research Institute, Parkville 3052, Australia.
Joseph DonaherCenter for Childhood Communication, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Ingo HelbigDivision of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.ORCID 0000-0001-8486-0558

Funding

Joint analysis of genomic and electronic medical record data to assess outcomes and drug response in pediatric epilepsiesK02NS112600 · NINDS · CHILDREN'S HOSP OF PHILADELPHIA · PI HELBIG, INGO · 2020 to 2024
$963k
NINDS NIH HHS K02 NS112600
6 · The paper itself

Abstract

Speech and language disorders are known to have a substantial genetic contribution. Although frequently examined as components of other conditions, research on the genetic basis of linguistic differences as separate phenotypic subgroups has been limited so far. Here, we performed an in-depth characterization of speech and language disorders in 52,143 individuals, reconstructing clinical histories using a large-scale data mining approach of the Electronic Medical Records (EMR) from an entire large paediatric healthcare network. The reported frequency of these disorders was the highest between 2 and 5 years old and spanned a spectrum of twenty-six broad speech and language diagnoses. We used Natural Language Processing to assess to which degree clinical diagnosis in full-text notes were reflected in ICD-10 diagnosis codes. We found that aphasia and speech apraxia could be easily retrieved through ICD-10 diagnosis codes, while stuttering as a speech phenotype was only coded in 12% of individuals through appropriate ICD-10 codes. We found significant comorbidity of speech and language disorders in neurodevelopmental conditions (30.31%) and to a lesser degree with epilepsies (6.07%) and movement disorders (2.05%). The most common genetic disorders retrievable in our EMR analysis were

Indexed as

electronic medical recordsgeneticsHuman Phenotype Ontologylanguage disorderspeech disorder

Identifiers

PMID38712155
PMCPMC11071575

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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.