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Record W4308915403 · doi:10.12968/jowc.2022.31.11.930

Clinical application of polylactic acid/gelatin nanofibre membrane in hard-to-heal lower extremity venous ulcers

2022· article· en· W4308915403 on OpenAlexaboutno aff
Hongrang Chen, Yun Shen, Haitao Zhang, Xiaoyan Long, Kunxue Deng, Tao Xu, Yongsheng Li

Bibliographic record

VenueJournal of Wound Care · 2022
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVenous leg ulcerSurgeryAnkleWound careProspective cohort studyWound healing

Abstract

fetched live from OpenAlex

Objective: To evaluate the safety and effectiveness of polylactic acid/gelatin nanofibre membranes (PGNMs) in treating hard-to-heal lower extremity venous ulcer wounds. Method: In this prospective study, patients with venous leg ulcers (VLUs) were treated with PGNMs or standard of care. Wounds were assessed once a week until the wound was fully healed. Results: The treatment group was comprised of 10 patients with VLUs, aged between 47–64 years, with an average age of 56.58±6.19 years. The wounds were located in the lower leg and/or ankle. Average wound area was 8.91±13.57cm 2 (range: 1.5–52.5cm 2 ). Average wound healing time was 18.75±16.36 days. Of the patients, nine (90%) rated their pain as lighter when removing the dressing, with an average pain value of 2.0±1.0 points. There was less secondary trauma to the wound surface, and less bleeding. At six months after the wound healing, the scar evaluation (using the Vancouver Scar Scale) result was 3.75±1.96 points. Conclusion: In this study, the PGNMs were safe and effective in treating hard-to-heal lower extremity VLUs.

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)0.001
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 score0.065
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.338
Teacher spread0.314 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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