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Record W4360599941 · doi:10.1111/iwj.14145

Functional and aesthetic outcomes of abdominal full‐thickness skin grafts in paediatric postburn digital and palmar flexion contractures

2023· article· en· W4360599941 on OpenAlexaboutno aff
Hongyu Liang, Quan Hu, Jianhua Cai, Pengcheng Li, Jun Shi, Hailiang Liu, Longlong Yang, Chuanan Shen

Bibliographic record

VenueInternational Wound Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMuscle contractureSurgerySignificant differenceInternal medicine

Abstract

fetched live from OpenAlex

The study aimed to assess the functional and aesthetic outcomes of abdominal full-thickness skin grafts (FTSGs) in paediatric postburn digital and palmar flexion contractures. The digital and palmar functions and aesthetics of 50 children who met the criteria were evaluated at pre-operation, the 3rd- and 12th-month post-operation, respectively. In the evaluation, the Vancouver Scar Scale (VSS), total active movement (TAM), and Jebsen-Taylor Hand Function Test (JHFT) were used. The contralateral, unaffected hand served as the criteria for functional recovery. The complications of donor sites were observed, and the take rate of skin grafts was calculated. The VSS scores at the 3rd and 12th months post-operation were lower than those before the operation. The TAM of each finger was improved at the 3rd and 12th months post-operation, compared with that before the operation. There was a significant difference in the time to complete the JHFT between the affected hand and the unaffected at the 3rd month post-operation, but no significant difference between them at the 12th month post-operation. The excellent and good take rate of the skin grafts was 90.00%.No donor site complications were observed. The abdominal FTSGs are effective in repairing paediatric digital and palmar scar contractures, with satisfying functional and aesthetic results, especially in large defects after scar release and resection.

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 score0.165
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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