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Record W2979908446 · doi:10.1590/2317-1782/20182018238

Correlação entre escalas de avaliação da cicatrização e as alterações miofuncionais orofaciais em pacientes com queimaduras de cabeça e pescoço

2019· article· pt· W2979908446 on OpenAlexaboutno aff
D. Magnani, Fernanda Chiarion Sassi, Luiz Philipe Molina Vana, Cláudia Regina Furquim de Andrade

Bibliographic record

VenueCoDAS · 2019
Typearticle
Languagept
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

PURPOSE: Verify the correlation between two scar assessment scales and the presence of orofacial myofunctional disorders (OMD) in patients with head and neck (H&N) burns. METHODS: Participants of this study were 16 adult individuals with H&N full-thickness burns. Data were collected through assessment of mandibular range of movement and application of the following instruments: Patient and Observer Scar Assessment Scale (POSAS), Vancouver Scar Scale, and Orofacial Myofunctional Evaluation with Scores (OMES). RESULTS: Results showed moderate negative correlation between the variables deglutition, breathing, total score of the functions, total score on the OMES and scores on the scar assessment scales, indicating that the higher (more severe) the scores on these scales, the lower the scores on the items of the OMES (indicative of greater OMD severity). No correlations were observed between the items of the OMES and the POSAS Patient scale. CONCLUSION: Results suggest that there is correlation between scar severity in burn patients, measured through clinical scales, and presence of OMD. Patients who present scores indicative of H&N pathological scars should be immediately referred to orofacial myofunctional assessment.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.015

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 head0.018
GPT teacher head0.287
Teacher spread0.268 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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Same venueCoDASSame topicBurn Injury Management and OutcomesFrench-language works237,207