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Record W4399785502 · doi:10.1177/02683555241258308

Photoplethysmography-based assessment of varicose vein-related risk factors, exercise health beliefs, and venous refill time in healthcare professionals working in operating rooms and outpatient clinics

2024· article· en· W4399785502 on OpenAlexaboutno aff
Gökçe Şirin, Selda Karaveli̇ Çakır, Sinem Eryiğit, Hasan Toz, Osman Pirhan, Semra Erpolat Taşabat, İlknur Çalışkan

Bibliographic record

VenuePhlebology The Journal of Venous Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and Treatment of Venous Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSittingVaricose veinsPhotoplethysmogramHealth carePhysical therapyHealth professionalsOutpatient clinicMedical emergencyEmergency medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACGROUND: Impaired venous return is observed in healthcare professionals who spend long periods standing and sitting. This descriptive cross-sectional study was conducted to evaluate varicose vein-related risk factors, exercise health beliefs, and venous refill time in healthcare professionals working in operating rooms and outpatient clinics by photoplethysmography. METHOD: The study sample consisted of 100 healthcare professionals without a diagnosis of peripheral venous insufficiency. Data were collected using a descriptive characteristics form, the Health Belief Model Scale for Exercise, the Short-Form McGill Pain Questionnaire, and photoplethysmography. RESULT: This study found that OR nurses had shorter venous refill times and experienced more pain due to prolonged standing, despite their high health beliefs about exercise. CONCLUSION: Healthcare professionals working in operating rooms should be screened for venous insufficiency and trained regarding the practices to prevent venous insufficiency, such as lying down, elevating legs, and using elastic stockings.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.336
Teacher spread0.321 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePhlebology The Journal of Venous DiseaseSame topicDiagnosis and Treatment of Venous DiseasesFrench-language works237,207