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Record W2145760040 · doi:10.1002/mus.21118

Needlestick injuries among electromyographers

2008· article· en· W2145760040 on OpenAlexaff
Farrah J. Mateen, Ian Grant, Eric J. Sorenson

Bibliographic record

VenueMuscle & Nerve · 2008
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsHealth Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineNeedlestick injuryHuman immunodeficiency virus (HIV)Emergency medicinePhysical therapyPediatricsFamily medicine

Abstract

fetched live from OpenAlex

The objective of this study was to determine the self-reported prevalence of needlestick injuries among practicing electromyographers. In January 2008, an anonymous electronic survey was sent to all active members of the American Association for Neuromuscular and Electrodiagnostic Medicine (AANEM) who provided e-mail addresses to the Association. Eight hundred and eight members (56% neurologists, 43% physiatrists; 97% practicing physicians, 3% trainees) responded, with a response rate of 22% (808 of 3659). The mean number of years in practice, involving electromyography (EMG) at least 1 day per week, was 16 years. A majority of physicians (64%) reported at least one needlestick injury involving EMG, and 8% reported five or more injuries. Needlestick injuries involving patients with human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), hepatitis B, and/or hepatitis C occurred in 1 of every 11 electromyographers. Nearly half of all respondents (44%) who experienced a needlestick injury stated that they did not report at least one injury event to official centers. Injuries were most likely to occur during a routine procedure (45%) or when a patient moved (26%). The most common preventable reason for injury was a perceived lack of time.

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)0.000
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 score0.021
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.021
GPT teacher head0.267
Teacher spread0.246 · 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

Citations19
Published2008
Admission routes1
Has abstractyes

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