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The effect of the terumo band used for hemostasis after transradial angiography on extremity pain

2025· article· tr· W7117745291 on OpenAlexaboutno aff
Atiye Erbaş, İsmail Aşatır, Osman Kayapinar

Bibliographic record

VenueAdıyaman Üniversitesi Sağlık Bilimleri Dergisi · 2025
Typearticle
Languagetr
FieldMedicine
TopicVascular Procedures and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsHemostasisPain scoreAngiographyPsychological interventionNursing Interventions ClassificationPain assessment

Abstract

fetched live from OpenAlex

Aim: This study aimed to evaluate pain associated with the use of the Terumo band pneumatic compression device in patients undergoing transradial angiography. Materials and Methods: This descriptive study was conducted with 100 patients between October 2022 and October 2023. Data was collected using a demographic data form, the Short Form McGill Pain Questionnaire, and a Pain Assessment Form. Descriptive statistics, independent samples t-test, and ANOVA were used for data analysis. Results: The mean pain score was 6.74 ± 6.99 one hour after application of the Terumo band and 3.81 ± 4.63 one hour after removal (t = 6.716; p = 0.001). Conclusion: Patients experienced pain both during and after the application of the Terumo band. As a recommendation for nursing practice, it is suggested that nurses continue pain assessment following transradial angiography and employ evidence-based interventions such as finger exercises, hot/cold application, and elevation to manage pain.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.230
Teacher spread0.226 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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