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Record W4402572675 · doi:10.1016/j.ijporl.2024.112115

Dysphagia is a strong predictor of revision supraglottoplasty in pediatric laryngomalacia

2024· article· en· W4402572675 on OpenAlexaff
Amy Callaghan, Hamdy El‐Hakim, Amanda Adsett, Daniela Migliarese Isaac, André Isaac

Bibliographic record

VenueInternational Journal of Pediatric Otorhinolaryngology · 2024
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsUniversity of Alberta HospitalStollery Children's Hospital
Fundersnot available
KeywordsLaryngomalaciaMedicineDysphagiaPediatricsSurgeryStridorAirway

Abstract

fetched live from OpenAlex

BACKGROUND: There is growing research on the association between swallowing dysfunction and laryngomalacia. Supraglottoplasty is the surgical intervention used to treat laryngomalacia, however a portion of patients who undergo this procedure will require a revision surgery. Predictive risk factors for revision supraglottoplasty in patients with laryngomalacia are not well understood, and previous studies failed to evaluate swallowing systematically. HYPOTHESIS: We predict a significant association between swallowing dysfunction and revision supraglottoplasty for patients with laryngomalacia. METHODS: This was a retrospective cohort study of consecutive patients between 2013 and 2023 at a tertiary pediatric care centre (Stollery Children's Hospital). All patients had an endoscopic diagnosis of laryngomalacia by a staff otolaryngologist and at minimum a systematic clinical swallowing assessment by a speech language pathologist, with an instrumental assessment as needed. Patients with genetic or neurological comorbidities, lack of follow up information, or age of >3 years were excluded. Clinical and instrumental swallow data, demographic information, surgical outcomes and revision surgeries were documented and collected. Univariate analysis was done to determine associations between variables and revision supraglottoplasty. Binary logistic regression was done to determine independent predictors of revision supraglottoplasty. RESULTS: 214 patients met the inclusion criteria and were analyzed in the study. 24 patients (11 %) required revision supraglottoplasty. 118 out of the 214 patients (55 %) had an instrumental assessment completed (FEES or VFSS). Of those, 92 (78 %) had abnormal findings on instrumental assessments. Univariate analysis showed Type 2 laryngomalacia (P = 0.017), presence of aspiration (P=<0.001), presence of cyanosis (P = 0.002) and abnormal findings on an instrumental assessment (P = 0.013) to be significantly associated with the need for revision supraglottoplasty. Binary regression analysis showed aspiration (OR = 5.6 {2.087-14.889}, P=<0.001) and cyanosis (OR = 5.3 {1.852-15.181}, P = 0.002) to be the only independent predictors of revision supraglottoplasty. CONCLUSION: Presence of aspiration is a strong predictive factor for revision supraglottoplasty in patients with laryngomalacia, when swallowing is evaluated systematically. More prospective research is needed to understand the relationship between swallowing dysfunction, laryngomalacia and surgery.

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)0.005
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.291
Teacher spread0.279 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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