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Record W2153734610 · doi:10.1016/s1474-5151(10)60025-4

43 Oral Deficiencies in Nurses Knowledge and Substandard Practice Related to ECG Monitoring: Baseline Results of the Pulse Trial

2010· article· en· W2153734610 on OpenAlexaboutno aff
Marjorie Funk, C.G. Winker, Jeanine May, Kimberly Stephens, Kristopher Fennie, Shelli L. Feder, Margaret Laragy, Leonie Rose, Yasemin Turkman, Barbara J. Drew

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBaseline (sea)Intensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Purpose: Although ECG monitoring is the cornerstone of care in hospital cardiac units, no studies have evaluated its quality. The purpose of our study is to examine: (1) nurses' knowledge of ECG monitoring; and (2) the quality of ECG monitoring (electrode placement; accuracy of rhythm interpretation; and use of arrhythmia, ischemia and QTc interval monitoring). Method: We analyzed baseline data from the PULSE Trial, a 5-year multi-site randomized clinical trial evaluating the effect of implementing American Heart Association practice standards for ECG monitoring on nurses' knowledge, quality of care, and patient outcomes. To evaluate knowledge, 1,739 nurses working on cardiac units at 17 hospitals (15 in the US, 1 in Canada, 1 in China) completed an online ECG monitoring knowledge test that covered essentials of ECG monitoring and arrhythmia, ischemia, and QTc interval monitoring. Scores can range from 0 to 100, with higher scores indicating greater knowledge. To evaluate the quality of ECG monitoring, 3 research nurses observed 1,821 patients on the cardiac units. They reviewed current medical records, observed patients for electrode placement, and compared arrhythmias stored in the monitor's memory with documentation by unit nurses.

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)0.007
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.326
Teacher spread0.299 · 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 designOther design
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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

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