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Record W4386929190 · doi:10.4314/tjpr.v22i8.25

A comparative study of the efficacy and safety of pure silica gel and chitosan quaternary ammonium salt silica gel in hypertrophic scar treatment

2023· article· en· W4386929190 on OpenAlexaboutno aff
Shenglin Wu, Yuan Jiang

Bibliographic record

VenueTropical Journal of Pharmaceutical Research · 2023
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsScarsChitosanMedicineItchingClinical efficacyHypertrophic scarAdverse effectSurgeryInternal medicineChemistryBiochemistry

Abstract

fetched live from OpenAlex

Purpose: To compare clinical efficacy of pure silica gel and chitosan quaternary ammonium salt silica gel (SQASC) in treatment of hypertrophic scars.Methods: Eighty-four patients with hypertrophic scars, who were admitted to hospital, were randomly divided into study group and control group with 42 patients in each group. Study group was treated with SQASC while control group was treated with pure silica gel. Scar scores (Vancouver scar score, VSS), scar aesthetics (Patient and observer scar assessment scale, POSAS), symptom improvement and adverse reactions were compared between groups before and after treatment.Results: Before treatment, there were no differences in VSS and POSAS scores for each aspect between groups. After treatment, VSS and POSAS scores for each aspect in study group were significantly lower than those in control group (p < 0.05). Congestion, itching, pain disappearance and thickness reduction occurred significantly earlier in study group than in control group (p < 0.05). Incidence of adverse reactions in study group was 4.76 %, which was significantly lower than 19.05% in control group (p < 0.05).Conclusion: Compared with pure silica gel, SQASC effectively alleviates symptoms of hypertrophic scars and aesthetics with fewer adverse effects. In future studies, sample size will be increased and study duration will be extended appropriately.

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 score0.123
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.196
GPT teacher head0.490
Teacher spread0.295 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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