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Use of a Novel Epidermal Harvesting System in Resource-Poor Countries

2015· article· en· W2090354024 on OpenAlexaff
Thomas E Serena, Adler Francius, Cristin Taylor, John MacDonald

Bibliographic record

VenueAdvances in Skin & Wound Care · 2015
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsMedicineWound careSurgerySkin grafting

Abstract

fetched live from OpenAlex

The 2010 earthquake in Port-au-Prince, Haiti, highlighted the need for wound care in resource-poor countries. Subsequently, the University of Miami in Florida established one of the first interprofessional wound care centers located at Bernard Mevs Hospital in the central portion of Port-au-Prince, caring for patients with acute and chronic wounds. In 2012, the authors used a novel epidermal harvesting system (CelluTome Epidermal Harvesting System; Kinetic Concepts Inc, San Antonio, Texas) to harvest epithelium to be grafted on 7 patients at the Mevs Hospital with longstanding wounds. Epidermal microblisters were obtained from each patient's thigh using the CelluTome Epidermal Harvesting System. After 35 minutes, microblisters were raised using the device harvester, and an adhesive dressing was inserted into the harvester for transfer to the wound site. In patients with lower-extremity wounds, a 2-layer compression dressing was placed over epidermal grafts. Six of the 7 wounds improved or achieved complete closure in 4 weeks. One of the patients with a 2-year-old thigh wound failed to demonstrate improvement; this may have been secondary to an inability to adequately secure the graft. All donor sites healed without any visible scarring. The authors were able to conclude that epidermal grafting may represent a viable reconstructive option for patients in resource-poor countries.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.567

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 head0.055
GPT teacher head0.330
Teacher spread0.275 · 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

Citations38
Published2015
Admission routes1
Has abstractyes

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