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Record W1900738324 · doi:10.5376/ijccr.2014.04.0002

Paediatric Parameningeal Rhabdomyosarcoma: A Case Report Post-multimodal Treatment

2014· article· en· W1900738324 on OpenAlexvenueno aff
Gustave Buname, Richard Byaruhanga, Emily Kakande, Justine Namwagala, David Alele, Christopher Ndoleriire

Bibliographic record

VenueInternational Journal of Clinical Case Reports · 2014
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsRhabdomyosarcomaMultimodal therapyMedicineRadiologySurgerySarcomaPathology

Abstract

fetched live from OpenAlex

Rhabdomyosarcoma is the most common soft tissue sarcoma of childhood, representing 5% of all childhood cancers. We are reporting an interesting case of parameningeal rhabdomyosarcoma in a child who underwent multimodal treatment. A 7 year old boy presented to our clinic with a history of bad breath, nasal obstruction and recurrent epistaxis from the left nostril for 3 months. On examination he had mild left proptosis with normal eye vision and movements, reddish left nasal mass with a smooth surface. Paranasal CT scan showed slightly enhancing soft tissue mass 72×77 mm in the nasal cavity that deviated the nasal septum to the right, extending to the nasopharynx posteriorly and to the maxillary and ethmoidal sinuses with another mass 11×16 mm extension into the orbit. Biopsy was taken and histology showed embryonal rhabdomyosarcoma. An extensive tumour debulking was done folwed by chemotherapy (vincristine, dactinomycin and cyclophosphamide) and 50 grays of radiotherapy. A surveillance CT scan a month after treatment revealed over 90% tumour reduction. All patients with metastatic disease (group IV, stage 4) are considered high risk, except children and adolescents younger than 14 years with embryonal rhabdomyosarcoma. Advances into the multimodality management have dramatically improved survival in PM-RMS from approximately 25% to 75%.

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)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.282
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.051
GPT teacher head0.415
Teacher spread0.364 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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