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Record W4416535584 · doi:10.1002/hed.70102

Tracheostomy in Flap‐Based Head and Neck Cancer Surgery: A Meta‐Analysis of Indications and Adverse Outcomes

2025· article· en· W4416535584 on OpenAlexaff
Raisa Chowdhury, Khanh Linh Tran, Naser Mohamad Karimi, Jhorrit Kahlon, Cornelius Kürten, Sena Turkdogan, Eitan Prisman

Bibliographic record

VenueHead & Neck · 2025
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsVancouver General HospitalMcGill UniversityUniversity of British ColumbiaMcGill University Health Centre
Fundersnot available
KeywordsHead and neck cancerAdverse effectCancerProspective cohort studyAirwayMEDLINE

Abstract

fetched live from OpenAlex

ABSTRACT Background Tracheostomy is frequently performed during flap‐based reconstruction for head and neck cancer, but predictive factors and complications are not well established. Methods A systematic review and meta‐analysis was conducted per PRISMA guidelines. Studies of adult patients undergoing free or pedicled flap reconstruction were included. Pooled tracheostomy rates, predictors, and complications were analyzed using random‐effects models. Heterogeneity was assessed with the I 2 statistic. Results Twenty‐six studies (27 029 patients) were included. The pooled tracheostomy rate was 54.6%, decreasing to 42.4% when routine tracheostomy studies were excluded. Advanced tumor stage, oropharyngeal site, bilateral neck dissection, prior radiotherapy, and smoking predicted tracheostomy. Flap type was not significantly associated. The overall complication rate was 16.3%, including airway issues (2.6%). No significant change in tracheostomy rates was observed over 30 years. Conclusions Tracheostomy use is influenced by tumor, surgical, and patient factors. Selective tracheostomy and validated risk tools may improve outcomes. Further prospective studies are needed.

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 score0.018
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.045
GPT teacher head0.347
Teacher spread0.302 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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