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Record W4400956601 · doi:10.1002/hed.27876

Donor site morbidity after scapula free flap surgery of head and neck reconstruction: A systematic review and meta‐analysis

2024· review· en· W4400956601 on OpenAlexaff
Sophie McGregor, Katrina Zaraska, Matthew Lynn, Sena Turkdogan, Khanh Linh Tran, Eitan Prisman

Bibliographic record

VenueHead & Neck · 2024
Typereview
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScapulaMedicineHead and neckSurgeryMeta-analysisComplicationFree flapSoft tissueInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The scapula free flap is becoming increasingly more utilized in head and neck reconstruction due to its natural geometry and soft tissue versatility. This study reviews the incidence rate, risk factors, and treatments of complications of scapula donor site morbidity. METHODS: A review was performed for articles published between October 1990 and November 2022 in Medline (OVID), PubMed, Web of Science, and CENTRAL. After screening, 24 articles meeting the criteria were included. RESULTS: Overall, 660 head and neck surgeries with the scapula donor bone across 24 studies were included. Twenty studies of 612 scapula free flaps reported a pooled postoperative complication rate of 10.7%, with no major complications. Seven studies of 199 scapula reconstructions showed a mean Disability of Arm, Shoulder and Hand (DASH) score of 14.39/100. CONCLUSION: With its low rate of morbidity, the scapula flap presents itself as a good alternative for patients at risk for poor healing.

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)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.012
Bibliometrics0.0050.007
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.062
GPT teacher head0.339
Teacher spread0.276 · 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 designMeta-analysis
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

Citations6
Published2024
Admission routes1
Has abstractyes

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