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ULTRAPHONOPHORESIS OF ENZYME DRUGS IN TREATMENT OF POSTACNE SCARS

2017· article· en· W3093977755 on OpenAlexaboutno aff
A. P. Talybova, Л. С. Круглова, Anna Germanovna Sten’ko

Bibliographic record

VenueRussian Journal of Physiotherapy Balneology and Rehabilitation · 2017
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsScarsHyaluronidaseMedicineItchingDermatology Life Quality IndexDermatologyQuality of life (healthcare)SurgeryEnzymeNursingPsoriasis

Abstract

fetched live from OpenAlex

The most effective medication for aesthetic correction of skin scars is ultraphonophoresis of enzyme preparations. Under our supervision there were 20 patients aged 17.2 ± 2.4 years with a symptomatic complex who received a course of ultraphonophoresis of hyaluronidase cream (15 procedures performed every other day). Efficacy was assessed taking into account clinical high-grade indices: Vancouver scale, POSAS, Dermatological Life Quality Index. Efficacy according to the Vancouver scale was 100% for pain, itching decreased by 75% after 2 months and completely stopped after 6 months, color of the scar improved by 50%, stiffness decreased by 67%, thickness of scar deformation decreased by 50%. Ultraphonophoresis of hyaluronidase cream is a highly effective method of correction of the scars of the symptom complex postacne, which also determines the improvement in the quality of life of this category of patients according to the dynamics of the dermatological quality of life index. This method can be recommended for use in clinical practice.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.340
Teacher spread0.331 · 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 designNon-randomized 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

Citations9
Published2017
Admission routes1
Has abstractyes

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Same venueRussian Journal of Physiotherapy Balneology and RehabilitationSame topicDermatologic Treatments and ResearchFrench-language works237,207