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Record W2010779023 · doi:10.1155/2013/346852

Near-Infrared Spectroscopy for Objectifying Cerebral Effects of Laser Acupuncture in Term and Preterm Neonates

2013· article· en· W2010779023 on OpenAlexaff
Wolfgang Raith, Iris Sapetschnig, Alexander Avian, Constanze Sommer, Nariae Baik‐Schneditz, Martin Köestenberger, Georg M. Schmölzer, Berndt Urlesberger

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineAnesthesiaOxygenationOxygen saturationAcupunctureHeart rateElectroacupunctureCerebral blood flowOxygenInternal medicineChemistryBlood pressurePathology

Abstract

fetched live from OpenAlex

Laser acupuncture (LA) becomes more and more relevant in neonates and infants. With near-infrared spectroscopy (NIRS), a continuous and noninvasive measurement of tissue oxygenation is possible. Aim was to investigate, whether the application of LA was associated with any changes in regional cerebral oxygen saturation (rcSO2) in term and preterm neonates. The study included 20 neonates (12 males, 8 females). The Large Intestine 4 acupuncture point (LI 4, Hegu) was stimulated by a microlaser needle (10 mW, 685 nm laser needle EG GmbH, Germany) for 5 minutes, bilaterally. All neonates underwent polygraphic recording during undisturbed daytime sleep, including heart rate (HR), peripheral oxygen saturation (SpO2), and measurement of nasal flow. Using NIRS, rcSO2 was measured continuously. Cerebral fractional tissue oxygen extraction (cFTOE) was calculated. We did not observe any significant changes in SpO2 and HR values during the whole observation period. However, there was a significant decrease in rcSO2 (P = 0.003) within postintervention period, accompanied by a significant increase in cFTOE (P = 0.010) in postintervention period.

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)0.000
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 score0.172
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.044
GPT teacher head0.347
Teacher spread0.303 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

Explore more

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