MétaCan
Menu
Back to cohort
Record W2901046611 · doi:10.5812/aapm.84195

The Effect of Low-Level Laser on Postoperative Pain After Elective Cesarean Section

2018· article· en· W2901046611 on OpenAlexaff
Sara Poursalehan, Sholeh Nesioonpour, Reza Akhondzadeh, Soheila Mokmeli

Bibliographic record

VenueAnesthesiology and Pain Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsCanadian Sport Centre Pacific
Fundersnot available
KeywordsMedicineSection (typography)Elective cesarean sectionPostoperative painAnesthesiaPregnancy

Abstract

fetched live from OpenAlex

BACKGROUND: Postoperative pain is one of the major concerns about a cesarean in pregnant women that can lead to serious complications and delayed recovery for patients. OBJECTIVES: The objective is to investigate the effect of low power laser on acute pain after elective cesarean. METHODS: In this randomized, double-blind clinical trial, 80 candidates for an elective cesarean were divided randomly into two groups, control and laser. The type of surgery was the same for both groups, which contained the spinal anesthesia technique. At the end of surgery, the surgical incision in patients who were treated with laser, (GaAlAs: 804 nm and GaAlInp: 650 nm) was irradiated by laser. The control group also received laser off by the same method. Patients were monitored for 24 hours to assess the severity of postoperative pain by VAS, the first request for analgesic and the total consumption of analgesic. RESULTS: The results demonstrated significant reduction of pain in the laser group 1, 4, 8, 12, 16, 24 hours after surgery, compared with the control group (P value < 0.05). Additionally, the average of total received analgesic in the group laser was less than the controls (P value = 0.006). The first request for analgesic in the laser received group was significantly longer than the controls (P value = 0.005). CONCLUSIONS: Low power laser therapy is a good method to reduce postoperative pain due to the fact that it is a safe and non-invasive method which is also accepted by patients.

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)0.006
metaresearch head score (Gemma)0.001
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 score0.080
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.253
Teacher spread0.244 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAnesthesiology and Pain MedicineSame topicAnesthesia and Pain ManagementFrench-language works237,207