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Record W4394892877 · doi:10.1093/jbcr/irae036.258

714 Our Experience with Enzymatic Debriding Agent, Anacaulase, for Burn Injuries: A 14 Patient Case Series

2024· article· en· W4394892877 on OpenAlexaboutno aff
Cole L. Bird, Jessica Reynolds, Dhaval Bhavsar

Bibliographic record

VenueJournal of Burn Care & Research · 2024
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEscharSurgeryBurn woundBurn injuryScarsDebridement (dental)Burn centerWound careContractureBromelainDemographicsSecond-Degree BurnNegative-pressure wound therapyWound healingPoison controlEmergency medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Background: Enzymatic debridement of burn wounds facilitates early removal of eschar. It has shown to improve healing time and decrease need for surgical intervention. We wanted to review our results of use of an enzymatic debriding agent (EDA - Anacaulase) in deep partial and full thickness burns. Methods: Methods We undertook a retrospective review of consecutive 14 adult patients treated with EDA at our Burn Center. These patients received therapy with Anacaulase, a novel enzymatic debriding agent, spanning from the year 2020 to the present day. Burn characteristics, EDA applications details, surgical interventions if any, time of heal, scar assessments were noted. We used Microsoft Excel for a descriptive analysis of the data. We examined continuous variables within specific ranges and provided summaries including median, minimum, maximum values, and percentages. Results: Results Patients demographics and burn injury characteristics are included in table 1. We were able to achieve >95% eschar removal with single application in all 14 patients. 57% patients required subsequent skin grafts. The time to achieve 95% wound closure averaged 35.5 days. Scars improved substantially over the study period, as indicated by mean Vancouver Scar Scale scores of 3.8 to 0.5 at 3 and 12 months, respectively. Only 2 patients required scar release surgery due to contracture. Conclusions Conclusion: Our review highlights potential benefits of early eschar removal with EDA. 47% patients were able to avoid autologous skin graft closure of deep partial and full thickness burn wounds. EDA (Anacaulase) may add value in care of select patients with deep partial and full thickness burn wounds. Applicability of Research to Practice Our review highlights potential benefits of early eschar removal with EDA. EDA (Anacaulase) may add value in care of select patients with deep partial and full thickness burn wounds.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.091
GPT teacher head0.445
Teacher spread0.354 · 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 designCase report
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

Citations1
Published2024
Admission routes1
Has abstractyes

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