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Record W4393442344 · doi:10.1002/hed.27721

Telemedicine‐enabled biofeedback electropalatography rehabilitation (TEBER): A pilot study for patients treated with surgery for oral cavity carcinoma

2024· article· en· W4393442344 on OpenAlexaff
Douglas B. Chepeha, Carly E. A. Barbon, Alex O. Esemezie, Majd Al Mardini, Justine Philteos, Matthew E. Spector, Tim Bressmann, Rosemary Martino, Scott V. Bratman, John B.C. Cho, Andrew Hope, Ali Abdalati Hosni, John J. H. Kim, Jolie Ringash, John Waldron, Dale Brown, John R. de Almeida, Ralph Gilbert, David P. Goldstein, Patrick Gullane, Jonathan C. Irish, Eric Monteiro, Christopher M. K. L. Yao

Bibliographic record

VenueHead & Neck · 2024
Typearticle
Languageen
FieldMedicine
TopicOral health in cancer treatment
Canadian institutionsMount Sinai HospitalPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsBiofeedbackMedicineRehabilitationTelemedicineOral cavityPhysical therapySurgeryPhysical medicine and rehabilitationDentistryHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: To address the rehabilitative barriers to frequency and precision of care, we conducted a pilot study of a biofeedback electropalatography (EPG) device paired with telemedicine for patients who underwent primary surgery +/- adjuvant radiation for oral cavity carcinoma. We hypothesized that lingual optimization followed by telemedicine-enabled biofeedback electropalatography rehabilitation (TEBER) would further improve speech and swallowing outcomes after "standard-of-care" SOC rehabilitation. METHOD: Pilot prospective 8-week (TEBER) program following 8 weeks of (SOC) rehabilitation. RESULTS: Twenty-seven patients were included and 11 completed the protocol. When examining the benefit of TEBER independent of standard of care, "range-of-liquids" improved by +0.36 [95% CI, 0.02-0.70, p = 0.05] and "range-of-solids" improved by +0.73 [95% CI, 0.12-1.34, p = 0.03]. There was a positive trend toward better oral cavity obliteration; residual volume decreased by -1.2 [95% CI, -2.45 to 0.053, p = 0.06], and "nutritional-mode" increased by +0.55 [95% CI, -0.15 to 1.24, p = 0.08]. CONCLUSION: This pilot suggests that TEBER bolsters oral rehabilitation after 8 weeks of SOC lingual range of motion.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.038
GPT teacher head0.335
Teacher spread0.297 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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