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Record W4394892955 · doi:10.1093/jbcr/irae036.331

790 A Single Institution’s Surgical Model for Pediatric Burns with ≤ 10% Body Surface Area Involvement

2024· article· en· W4394892955 on OpenAlexaff
Joel Fish, David Lee, Hawwa Chakera, Charis Kelly, Jennifer Zuccaro

Bibliographic record

VenueJournal of Burn Care & Research · 2024
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineTotal body surface areaBody surface areaSurgeryPopulationIncidence (geometry)Burn injurySkin grafting

Abstract

fetched live from OpenAlex

Abstract Introduction Burn injuries continue to be prevalent in the pediatric population and are the fifth most common cause of non-fatal injury according to the World Health Organization. Unlike the adult population, most pediatric burns in the United States are small in size and are often the result of scalds. Despite the high incidence of small burns, a standardized treatment algorithm does not currently exist, and care is often influenced by clinical judgement and resource availability. As a result, various techniques to close the burn wound and promote further healing are currently utilized. This study explores the utility of a multi-stage grafting technique, involving allograft and autograft, for treating small burns (≤ 10% total body surface area (TBSA)) in pediatric patients. Methods A retrospective review of patients aged 0-18 years who had a burn that was ≤ 10% TBSA and underwent a multi-stage grafting procedure involving the use of allograft and autograft between 09-01-2018 and 09-01-2022 was conducted. Demographic information including data pertaining to the burn injury was collected for all patients. The primary outcome measure for this study was the percentage of graft take at the graft dressing takedown procedure. All variables were summarized using descriptive statistics. P values < 0.05 indicated statistical significance. Results One hundred and sixty-eight patients met the inclusion criteria for this study. The mean time from presentation to allograft surgery was 10.8 days (SD 5.6) followed by autograft surgery approximately one week later. Most patients were discharged within 24 hours following allograft surgery (88.1%) and autograft surgery (80.9%). Mean autograft take was 97.7% (SD 11.1%) with only four patients experiencing significant graft loss requiring subsequent re-grafting. The main causes of graft loss were infection and inadequate excision of the wound bed. Conclusions This analysis revealed that patients who underwent a multi-stage grafting procedure involving the use of allograft and autograft experienced minimal graft loss. These positive outcomes demonstrate that the multi-stage grafting technique, which has traditionally been employed for larger burn injuries, can be successfully adapted for smaller burns in children. Moreover, the findings from this study help to address the significant knowledge gap regarding the optimal approach to treating small burn wounds. Further research in this area is warranted to learn more about cosmetic outcomes following multi-stage grafting and determine how it compares to other techniques for treating small burns. Applicability of Research to Practice The findings from this study will allow us to begin benchmarking our treatment of small burn wounds with other centers resulting in improvements in patient care and outcomes.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.002

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 head0.112
GPT teacher head0.392
Teacher spread0.279 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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