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Record W3169006986 · doi:10.1007/s00405-021-06920-4

A European survey on the practice of nutritional interventions in head–neck cancer patients undergoing curative treatment with radio(chemo)therapy

2021· article· en· W3169006986 on OpenAlexaff
Federico Bozzetti, Cristina Gurizzan, Simon Lal, A. van Gossum, Geert Wanten, Wojciech Golusiński, Şefik Hoşal, Paolo Bossi

Bibliographic record

VenueEuropean Archives of Oto-Rhino-Laryngology · 2021
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsSurgical Specialties (Canada)
FundersEuropean Society for Clinical Nutrition and MetabolismUniversità degli Studi di Brescia
KeywordsMedicineGastrostomyParenteral nutritionHead and neck cancerEnteral administrationHead and neckMedical nutrition therapyIntensive care medicinePsychological interventionCancerSurgeryInternal medicineNursing

Abstract

fetched live from OpenAlex

PURPOSE: As the practice of nutritional support in patients with head and neck cancer (HNC) during curative radio(chemo)therapy is quite heterogeneous, we carried out a survey among European specialists. METHODS: A 19-item questionnaire was drawn up and disseminated via the web by European scientific societies involved in HNC and nutrition. RESULTS: Among 220 responses, the first choice was always for the enteral route; naso-enteral tube feeding was preferred to gastrostomy in the short term, while the opposite for period longer than 1 month. Indications were not solely related to the patient's nutritional status, but also to the potential burden of the therapy. CONCLUSION: European HNC specialists contextualize the use of the nutritional support in a comprehensive plan of therapy. There is still uncertainty relating to the role of naso-enteral feeding versus gastrostomy feeding in patients requiring < 1 month nutritional support, an issue that should be further investigated.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.360
Teacher spread0.284 · 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 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

Citations9
Published2021
Admission routes1
Has abstractyes

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Same venueEuropean Archives of Oto-Rhino-LaryngologySame topicNutrition and Health in AgingFrench-language works237,207