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Record W2537098531 · doi:10.1002/hed.24600

High‐dose intravenous steroid regimen for radiation‐induced hypoglossal nerve palsy

2016· article· en· W2537098531 on OpenAlexaff
Lachlan McDowell, Marlene C. Jacobson, Wilfred Levin

Bibliographic record

VenueHead & Neck · 2016
Typearticle
Languageen
FieldMedicine
TopicOral health in cancer treatment
Canadian institutionsSunnybrook Health Science CentrePrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineSwallowingHypoglossal nerveAnesthesiaRadiation therapyAirwayRegimenSurgeryTongue

Abstract

fetched live from OpenAlex

BACKGROUND: Hypoglossal nerve palsies are infrequent complications of head and neck radiotherapy. Treatments focus on maintaining function and prevention of abnormal airway-related swallowing events. METHODS: A patient with longstanding cranial neuropathies, including bilateral hypoglossal involvement, secondary to chemoradiotherapy for nasopharyngeal carcinoma, experienced repeated episodes of life-threatening complications. Initially, 2 courses of 2 weekly 24-hour intravenous methylprednisolone (IVMP) infusions were administered 2 years apart. We report the results of a third course comprising 5 weekly cycles. RESULTS: Patient-reported outcomes revealed significant improvement in swallowing function, speech, and psychosocial status. Airway invasion during swallowing and pharyngeal retention were assessed videofluoroscopically and evaluated using the Penetration-Aspiration Scale (PAS) and a residue rating scale, respectively. PAS ratings after infusions 2 and 5, improved dramatically from baseline and were maintained at 1-year follow-up. CONCLUSION: High doses of IVMP may improve radiation-induced neuropathies. Further testing in similar patients is needed to prove reproducibility. © 2016 Wiley Periodicals, Inc. Head Neck 39: E23-E28, 2017.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.049
GPT teacher head0.345
Teacher spread0.296 · 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 designOther design
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

Citations12
Published2016
Admission routes1
Has abstractyes

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