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Record W2157649179 · doi:10.1002/hed.20639

Predictors of morbidity following free flap reconstruction for cancer of the head and neck

2007· article· en· W2157649179 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHead & Neck · 2007
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsToronto General HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicinePerioperativeHead and neck cancerSurgeryComorbidityFree flap reconstructionFree flapUnivariate analysisCancerHead and neckRadiation therapyMultivariate analysisInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Free flap reconstruction of head and neck cancer defects is complex with many factors that influence perioperative complications. The aim was to determine if there was an association between perioperative variables and postoperative outcome. METHODS: We evaluated 185 patients undergoing free flap reconstruction following ablation of head and neck cancer between 1999 and 2001. Demographic, laboratory, surgical and anesthetic variables were analyzed using univariate and multivariable techniques. RESULTS: Ninety-eight patients (53%) developed complications, of which 74 were considered major, giving a major morbidity rate of 40%. Predictors of major complications were increasing patient age, ASA class, and smoking. Predictors of medical complications were ASA class, smoking, age and crystalloid replacement. Predictors of surgical complications were tracheostomy, preoperative hemoglobin, and preoperative radiotherapy. CONCLUSION: Patient age, comorbidity, smoking, preoperative hemoglobin, and perioperative fluid management are potential predictors of postoperative complications following free flap reconstruction for cancer of the head and neck.

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.

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 score0.390
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.022
GPT teacher head0.301
Teacher spread0.278 · 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