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Record W4391723309 · doi:10.1002/jbio.202300348

Effectiveness of 780 nm photobiomodulation as adjunct treatment for bone exposed fractures: A pilot study on radiograph, pain, and cytokines analysis

2024· article· en· W4391723309 on OpenAlexaboutno aff
Deivison Santos Bonfim, Micaela Leite Fernandes, Igor Pereira Ribeiro Muniz, Ítalo Sousa Pereira, Robson Amaro Augusto da Silva, Francine Cristina da Silva, Gabriel Pinto de Oliveira Santos, Luciano Pereira Rosa

Bibliographic record

VenueJournal of Biophotonics · 2024
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMedicineBone healingLow level laser therapyDentistryAdjuvantVisual analogue scaleSurgeryInternal medicineLaser therapyLaser

Abstract

fetched live from OpenAlex

Abstract The aim of this study was to evaluate the effectiveness of photobiomodulation with a 780 nm laser as an adjunct to surgical treatment in the regeneration of bone fractures. Twenty patients diagnosed with open fractures in the lower limbs were selected and randomly divided into two groups: control and LLLT. LLLT parameter: 780 nm, 0.04 cm 2 of light beam diameter, 40 mW of power, 10 s per point, 0.4 J of energy, fluence of 10 J/cm 2 and irradiance of 1 W/cm 2 . The evaluated data were: pain, using McGill scale, use of analgesics and anti‐inflammatories, levels of cytokines TNF‐α, IFN‐γ, IL‐1β, IL‐10, and IL‐17, and bone level regeneration. Data were analyzed using Wilcoxon and Mann–Whitney tests (5%). We can conclude that LLLT was effective as an adjuvant in the bone fracture regeneration process, altered IL‐1β levels, reduced the use of analgesics and anti‐inflammatories, reducing the pain pattern throughout the sessions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.344
Teacher spread0.319 · 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 designBench or experimental
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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

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