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Record W4409073251 · doi:10.1093/jbcr/iraf019.164

535 Double-blind, Randomized, Controlled Trial Evaluating Early Application of a Surfactant-based Dressing for Partial-thickness Burns (EARLY)

2025· article· en· W4409073251 on OpenAlexaboutno aff
David Hill

Bibliographic record

VenueJournal of Burn Care & Research · 2025
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialPulmonary surfactantDouble blindSurgeryPathologyPlaceboAlternative medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Surfactant-based wound dressings (WSD) have been utilized in chronic, non-healing wounds and small burn wounds to soften and aid removal of wound debris. We conducted a double-blind, randomized controlled study evaluating paired, non-contiguous partial thickness burn wounds comparing WSD versus bacitracin. We hypothesized early application of WSD would lead to less wound conversion and less painful wound care. Methods Sample size was determined based on a projected 25% improvement in salvaged tissue (i.e., excised tissue) with bacitracin as the comparator. Wounds were paired; two non-contiguous partial thickness areas less than 10% TBSA each. Wound care was performed daily, per protocol. Additional outcomes included grafted area, infection, and procedure-associated pain. Patients and assessing surgeons were blinded to treatment assignment. Paired analysis performed for primary outcome and mixed modeling for change in Numeric Pain Rating Scale. SAS 9.4 was used for analysis. Results Patients were consented and treated within 24 hours of injury. All cases were deemed initially necessary for admission. Patients were followed until 95% re-epithelialization occurred or were discharged. Vancouver scar scale was utilized post discharge. Twenty-seven patients were consented. The average time from injury to consent was 14.6 ± 5.6 hours. The average age was 40.9 ± 16.5 years with 65% being male, 50% Black, and 50% Caucasian. Flame injury was most common. The average total body surface area burned was 8.8 ± 3.6%. There was no difference in percent of salvaged tissue, calculated as the amount excised (cm2) relative to the original size of injury [6.1% (95% CI -9.7, 21.9), p=0.4363); 26.9% versus 38.5% of patients had their wounds convert to a deeper injury. However, there was a significant difference [-0.61 (95% CI -1.04, -0.17), p=0.0065) in patient reported pain between treatment assignment (measured at baseline and after each wound care session). There was one wound infection in each group. Conclusions WSD facilitates easier debridement, is resistant to infection without need of antimicrobial exposure, and shows improved patient tolerability. Applicability of Research to Practice WSD is a useful dressing that can be easily applied early after injury and can improve patient’s wound care experience. Funding for the Study Medline funded this study through an investigator-initiated grant, but has not reviewed the results.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.138
GPT teacher head0.499
Teacher spread0.361 · 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 designRandomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

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