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Record W4301804787

EUREKA study – the evaluation of real-life use of a biophotonic system in chronic wound management: an interim analysis

2017· article· en· W4301804787 on OpenAlexaboutno aff
M Romanelli, A Piaggesi, G Scapagnini, V Dini, A Janowska, E Iacopi, C Scarpa, S Fauverghe, F Bassetto

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Ozone Research
Canadian institutionsnot available
Fundersnot available
KeywordsInterimInterim analysisMedicinePolitical scienceInternal medicineClinical trial
DOInot available

Abstract

fetched live from OpenAlex

Marco Romanelli,1 Alberto Piaggesi,2 Giovanni Scapagnini,3 Valentina Dini,1 Agata Janowska,1 Elisabetta Iacopi,2 Carlotta Scarpa,4 Stéphane Fauverghe,5 Franco Bassetto4 1Wound Healing Research Unit, Division of Dermatology, School of Medicine, University of Pisa, Pisa, 2Diabetic Foot Section, Department of Medicine, University of Pisa, Pisa, 3Department of Medicine and Health Sciences, School of Medicine, University of Molise, Campobasso, 4Clinic of Plastic and Reconstructive Surgery, Padova University-Hospital, Padova, Italy; 5KLOX Technologies Inc., Laval, QC, Canada Objective: Interest has grown regarding photobiomodulation (PBM) with low-level light therapy, which has been shown to positively affect the stages of the wound healing process. In a real-life context clinical setting, the objective of the EUREKA study was to investigate efficacy, safety, and quality of life associated with the use of a BioPhotonic gel (LumiHeal™) in the treatment of chronic wounds such as venous leg ulcers (VLUs), diabetic foot ulcers (DFUs), and pressure ulcers (PUs). This BioPhotonic gel represents a new, first-in-class emission spectrum of light, including fluorescence, to induce PBM and modulate healing.Design: The multicenter, prospective, interventional, uncontrolled, open-label study enrolled 100 patients in 12 wound centers in Italy. We performed an early interim analysis based on the first 33 subjects (13 VLU, 17 DFU, 3 PU) in seven centers who completed the study.Main results: Seventeen patients (52%) achieved total wound closure (full re-epithelialization for 2 weeks) during the study period. Two patients (6%) were considered “almost closed” (decrease of the wound area of more than 90% at study end) and three others (9%) were considered “ready for skin grafting”. No related serious adverse events were observed, and the compliance was excellent. After the treatment, the average time to “pain-free” was 11.9 days in the VLU group. Quality of life was improved with overall increase of 26.4% of the total score (Cardiff Wound Impact Schedule, p=0.001).Conclusion: The study revealed a positive efficacy profile of the BioPhotonic gel in promoting wound healing and reactivating the healing process in different types of chronic, hard-to-heal wounds. The treatment was shown to be safe and well tolerated by the patients, and a reduction of pain perception was also detected during the treatment period. The improvement of the quality of life was accompanied by a high level of clinician satisfaction. Keywords: photobiomodulation, fluorescence biomodulation, biophotonics, phototherapy, light, venous leg ulcers, VLUs, pressure ulcers, PUs, diabetic foot ulcers, DFUs, hard-to-heal 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)0.014
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.644
GPT teacher head0.650
Teacher spread0.005 · 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
Published2017
Admission routes1
Has abstractyes

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