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Clinical and videofluoroscopic diagnosis of dysphagia in chronic encephalopathy of childhood

2014· article· en· W1972123160 on OpenAlexaff
Brenda Carla Lima Araújo, Maria Eugênia Almeida Motta, Adriana Castro, Cláudia Marina Tavares de Araújo

Bibliographic record

VenueRadiologia Brasileira · 2014
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsCanadian Association of Occupational Therapists
FundersFundação de Amparo à Ciência e Tecnologia do Estado de PernambucoConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsDysphagiaSwallowingMedicinePediatricsClinical diagnosisPhysical therapyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the contribution of deglutition videofluoroscopy in the clinical diagnosis of dysphagia in chronic encephalopathy of childhood. MATERIALS AND METHODS: The study sample consisted of 93 children diagnosed with chronic encephalopathy, in the age range between two and five years, selected by convenience among patients referred to the authors' institution by speech therapists, neurologists and gastroenterologists in the period from March 2010 to September 2011. The data collection was made at two different moments, by different investigators who were blind to each other. RESULTS: The method presented low sensitivity for detecting aspiration with puree consistency (p = 0.04). Specificity and negative predictive value were high for clinical diagnosis of dysphagia with puree consistency. CONCLUSION: In the present study, the value for sensitivity in the clinical diagnosis of dysphagia demonstrates that this diagnostic procedure may not detect any change in the swallowing process regardless of the food consistency used during the investigation. Thus, the addition of the videofluoroscopic method can significantly contribute to the diagnosis of dysphagia.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.396
Teacher spread0.360 · 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 teacher head, 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

Citations9
Published2014
Admission routes1
Has abstractyes

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