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Record W2892630616 · doi:10.1589/jpts.30.1227

Effect of orange polarized light on post burn pediatric scar: a single blind randomized clinical trial

2018· article· en· W2892630616 on OpenAlexaboutno aff
Nesrein A. Abd Elrashid, Doaa Ahmed Sanad, Noha F. Mahmoud, Hamada A. Hamada, Alshaimaa M. Abdelmoety, Ahmed M. Kenawy

Bibliographic record

VenueJournal of Physical Therapy Science · 2018
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHypertrophic scarRandomized controlled trialSurgeryConcomitantSignificant differenceInternal medicine

Abstract

fetched live from OpenAlex

[Purpose] This study was carried out to investigate the effect of orange filtered polarized polychromatic light on post burn pediatric scar. [Participants and Methods] Thirty children with post burn scar in wrist and hands participated in this study. They were between 3 to 7 years old, having hypertrophic burn scar ≥2 months post healing, free from concomitant skin disease and keloids. They were randomly assigned into two groups. The control group (A) (n=15) received Scar Standard Management (SSM) protocol and the study group (B) (n=15) received SSM protocol along with 15 min/area polarized light with medical range filter followed by 15 min/area orange filtered polarized light. All children received the study protocol once a day, 3 times/week for one month. Scar assessment was done before and after the study protocol by using Vancouver Scar Scale (VSS). [Results] All participated children were analyzed. Comparison of post treatment results between groups revealed significant improvement of post burn scar for both groups with significant difference in favor to the study group. [Conclusion] Ultimately it was revealed that Orange filtered polarized light has a special and beneficial effect on decreasing post burn pediatric scar.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.035
GPT teacher head0.410
Teacher spread0.375 · 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 designRandomized 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

Citations10
Published2018
Admission routes1
Has abstractyes

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