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Record W2770623367 · doi:10.1016/j.ctro.2017.11.005

Skull base or cervical vertebral osteomyelitis following chemoradiotherapy for pharyngeal carcinoma: A serious but treatable complication

2017· article· en· W2770623367 on OpenAlexaff
Nafisha Lalani, Shao Hui Huang, Coleman Rotstein, Eugene Yu, Jonathan C. Irish, Brian O’Sullivan

Bibliographic record

VenueClinical and Translational Radiation Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicInfectious Diseases and Tuberculosis
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health NetworkPrincess Margaret Cancer Centre
FundersUniversity of Warwick
KeywordsMedicineOsteomyelitisRadiation therapyVertebral osteomyelitisChemoradiotherapySurgeryHead and neck cancerComplicationSkullRadiologyCervical vertebrae

Abstract

fetched live from OpenAlex

Osteomyelitis, infection of the bone and marrow, following high dose (chemo-)radiotherapy for head and neck cancer is uncommon and rarely seen in the cervical spine or temporal bone. Due to its proximity to critical structures, osteomyelitis in the latter regions could carry potentially important consequences. Furthermore, involvement near the skull base (e.g. temporal bone and high cervical vertebrae) presents unique challenges in diagnosis (especially in the differentiation from disease recurrence) and treatment, making early detection and timely intervention critical. In this report, we describe two cases of osteomyelitis, one involving the temporal bone and the other affecting the 2nd and 3rd cervical vertebrae, diagnosed and treated with good outcome in the setting of definitive chemoradiotherapy for locally advanced pharyngeal carcinomas. We suggest that for new or evolving post-radiotherapy osseous changes in regions that have received a high dose of radiotherapy, associated with unexpected and deteriorating spinal symptoms such as pain and spasm, radiation-related osteomyelitis should be considered in the differential diagnosis from tumor progression. Timely referral to a surgical oncologist and infectious diseases specialist is paramount in achieving satisfactory clinical outcomes.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.409
Teacher spread0.349 · 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 designCase report
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

Citations14
Published2017
Admission routes1
Has abstractyes

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