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Record W2011614668 · doi:10.1002/hed.21102

Quality of life analysis in patients with anterior skull base neoplasms

2009· article· en· W2011614668 on OpenAlexaff
Carsten E. Palme, Jonathan C. Irish, Patrick Gullane, Mark R. Katz, Gerald M. Devins, Gideon Bachar

Bibliographic record

VenueHead & Neck · 2009
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchSouthlake Regional Health CenterUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Radiation therapyHead and neck cancerDepression (economics)Rating scaleSkullSurgeryInternal medicinePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Significant morbidity is associated with management of anterior skull base neoplasms. The aim of this study was to evaluate the posttreatment patient's quality of life (QOL). METHODS: A retrospective chart review identified 27 patients. QOL tools included the Functional Assessment of Cancer Therapy-Head & Neck, Centre for Epidemiologic Studies Depression Scale (CES-D), Atkinson Life Happiness Rating (ALHR), and Midface Dysfunction Scale (MDS). RESULTS: Postoperative radiotherapy and chemotherapy was required in 16 and 2 patients, respectively. The median FACT, ALHR, and CES-D scores were 118 +/- 21, 9 +/- 2, and 17 +/- 8, respectively. Smell and nasal crusting disturbance was reported by 69% and 61%, respectively. CES-D > 16 and patients with recurrent disease correlated with a lower Total-FACT score. Adjuvant radiotherapy correlated with a lower FACT-H&N score. Patient sex, marital-status, pathology, surgical technique, or complication rate did not correlate with worse QOL. CONCLUSION: Anterior skull base neoplasms survivors have an overall acceptable QOL. Most complaints relate to MDS. Recurrence, adjuvant radiotherapy, and MDS had lower QOL scores.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.347

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 head0.021
GPT teacher head0.317
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 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

Citations35
Published2009
Admission routes1
Has abstractyes

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