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Record W1968213357 · doi:10.12968/ijpn.2007.13.5.23498

Management of dysphagia in advanced oropharyngeal cancer

2007· review· en· W1968213357 on OpenAlexaff
Jamie Penner, Susan McClement, Jo‐Ann V. Sawatzky

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2007
Typereview
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsCancerCare ManitobaUniversity of Manitoba
Fundersnot available
KeywordsDysphagiaMedicinePsychological interventionOropharyngeal dysphagiaQuality of life (healthcare)Intensive care medicinePopulationCancerMEDLINEPhysical therapyNursingSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Individuals with advanced oropharyngeal cancer often experience dysphagia as a result of their illness and its treatment. Research consistently demonstrates that dysphagia and difficulty with oral intake have many implications, including a negative impact on quality of life. Nurses are in a key position to provide support and initiate appropriate interventions for individuals with dysphagia. Using the Human Response to Illness model (Mitchell et al, 1991) as an organising framework, this paper presents a critical review of the empirical literature regarding dysphagia in individuals with advanced oropharyngeal cancer that will: i) provide the reader with a comprehensive understanding of dysphagia; ii) identify current gaps in our knowledge; and iii) establish the foundation for appropriate evidence-based interventions to optimise functioning and quality of life in this patient population.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.152
GPT teacher head0.580
Teacher spread0.429 · 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 designOther design
Domainnot available
GenreReview

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

Citations19
Published2007
Admission routes1
Has abstractyes

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