MétaCan
Menu
Back to cohort
Record W1963818340 · doi:10.1111/dmcn.12749

Feeding–swallowing difficulties in children later diagnosed with language impairment

2015· article· en· W1963818340 on OpenAlexafffund
Kathy Malas, Natacha Trudeau, Miguel Chagnon, David H. McFarland

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2015
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsMcGill UniversityUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationCentre Hospitalier Universitaire Sainte-Justine
FundersCentre hospitalier universitaire Sainte-Justine
KeywordsSwallowingMedicinePediatricsAudiologyLanguage impairmentPsychologyDevelopmental psychologySurgery

Abstract

fetched live from OpenAlex

AIM: The aim of this retrospective study was to assess the relationship between feeding-swallowing difficulties (FSDs) and later language impairments in children. METHOD: Retrospective analyses were carried out using the clinical files of 82 children with language impairments from a large urban rehabilitation center. Two subgroups of these children were established: children with motor impairments, referred to as the language impairment with motor impairment ('LI+MI') subgroup (n=23, mean age 4y 6mo, SD 8.7mo), and children without motor impairments, referred to as the language impairment without motor impairment ('LI-MI') subgroup (n=59, mean age 5y, SD 8mo). The prevalence of food selectivity, difficulties in sucking, salivary control issues, and food transition difficulties was extracted. Data were compared with a general population estimate of FSDs. RESULTS: FSDs were documented in 62% of the clinical files; 87% of these files were from the LI+MI subgroup and 53% were from the LI-MI subgroup. Among each subgroup of children with language impairments, the prevalence of FSDs was significantly higher than the general population estimate of 20% (LI+MI:χ(2) =55.965, df=1, p<0.001; LI-MI: χ(2) =32.807, df=1, p<0.001). Furthermore, the prevalence of FSDs was significantly higher in children with language impairments and motor impairments than in those with language impairments but without motor impairments (χ(2) =6.936, df=1, p<0.01). Both food transition difficulties (χ(2) =14.99, df=1, p<0.001) and salivary control issues (χ(2) =5.02, df=1, p=0.02) were more frequent in the LI+MI subgroup than in the LI-MI subgroup. Combinations of two or more FSDs were also more frequent in the LI+MI subgroup than in the LI-MI subgroup (χ(2) =4.19, df=1, p=0.04). INTERPRETATIONS: These findings suggest that early FSDs may be used as a potential marker for language impairment. However, larger prospective studies are needed to confirm this.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.249
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueDevelopmental Medicine & Child NeurologySame topicChild Nutrition and Feeding IssuesFrench-language works237,207