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Effect of local application of cold or heat for relief of pricking pain

2002· article· en· W1984102668 on OpenAlexfundno aff
Yuka Saeki

Bibliographic record

VenueNursing and Health Sciences · 2002
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsnot available
FundersMcGill University
KeywordsPain sensationSensationPain reliefMedicineStimulationBurning SensationAnesthesiaSkin temperatureVisual analogue scaleThermal sensationSurgeryPsychologyInternal medicineDermatologyThermal comfort

Abstract

fetched live from OpenAlex

The present study was designed to determine the effect of the application of cold or heat on the sensation of pricking pain based on autonomic responses. Electrical stimulation was applied to the antebrachium or brachium of subjects as an artificial pricking pain, and skin blood flow (BF) and skin conductance level (SCL) at the fingertip were measured. Pain sensation was evaluated using the visual analog scale. Pain stimulation produced a significant increase in SCL and a significant decrease in BF at both the antebrachium and brachium. Application of cold to the stimulation site using an ice-water pack reduced BF and SCL responses and pain sensation. Application of heat using a hot water bottle caused a significant increase in pain sensation and enhancement of BF and SCL responses. These results suggest that application of cold promotes relief of pricking pain sensation and suppression of autonomic responses, and that application of heat has no such effect. It is important that nurses ascertain the type of pain or source of pain and take proper measures for its relief.

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)0.000
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.391
Teacher spread0.343 · 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 designNon-randomized 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

Citations43
Published2002
Admission routes1
Has abstractyes

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