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Record W4324056879 · doi:10.3390/life13030762

Mid-Term Follow-Up Study of Children Undergoing Autologous Skin Transplantation for Burns

2023· article· en· W4324056879 on OpenAlexaboutno aff
Angyalka Válik, Katalin Harangozó, András Garami, Zsolt Juhász, Gergő Józsa, Aba Lőrincz

Bibliographic record

VenueLife · 2023
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
FundersNational Research, Development and Innovation OfficeÁltalános Orvostudományi Kar, Pécsi Tudományegyetem
KeywordsMedicineScarsSurgeryTransplantationRetrospective cohort studyCohortInternal medicine

Abstract

fetched live from OpenAlex

Deep partial and full-thickness burns require surgical treatment with autologous skin grafts after necrectomy, which is the generally accepted way to achieve permanent wound coverage. This study sought to examine the grafted and donor areas of children who underwent autologous skin transplantation, using two assessment scales to determine the severity of the scarring and the cosmetic outcome during long-term follow-up. At the Surgical Unit of the Department of Paediatrics of the University of Pécs, between 1 January 2015 and 31 December 2019, children who had been admitted consecutively and received autologous skin transplantation were analyzed. Twenty patients met the inclusion criteria in this retrospective cohort study. The authors assessed the results using the Patient and Observer Scar Assessment Scale (POSAS) and the Vancouver Scar Scale (VSS). There was a significant difference in how parents and examiners perceived the children’s scars. In the evaluation of the observer scale, the most critical variables for the area of skin grafted were relief and thickness. Besides color, relief was the worst clinical characteristic on the patient scale. However, when medical professionals evaluated the donor site, significantly better results were obtained compared to the transplanted area (average observer scale score: 1.4 and 2.35, p = 0.001; VSS: 0.85 vs. 2.60, p < 0.001), yet it was similar to the graft site in the parents’ opinion (Patient Scale: 2.95 and 4.45, p = 0.181).

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 score0.010
Threshold uncertainty score0.264

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 head0.034
GPT teacher head0.327
Teacher spread0.293 · 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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