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Record W2085085652 · doi:10.12927/cjnl.2013.23361

The Effectiveness of Superficial Subcutaneous Lidocaine Administration Prior to Femoral Artery Sheath Removal

2013· review· en· W2085085652 on OpenAlexfundvenueno aff
Laura Davison, Anne McVety, Tara Oke

Bibliographic record

VenueNursing leadership · 2013
Typereview
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsnot available
FundersLondon Health Sciences CentreUniversity of OttawaHamilton Health Sciences
KeywordsMedicineLidocaineAnesthesiaConventional PCISurgeryInternal medicineMyocardial infarction

Abstract

fetched live from OpenAlex

The dynamic world of healthcare requires continuous review of practice to ensure that patient care aligns with current evidence and best practice. Superficial subcutaneous lidocaine injection has been an order option at London Health Sciences Centre-University Hospital (LHSC-UH) for use in post-percutaneous coronary intervention (PCI) prior to femoral artery sheath removal (FASR). The purpose of administering lidocaine is to reduce pain during FASR, subsequently enhancing the patient's experience. A critical appraisal was performed by the Continuous Quality Improvement-Cardiac Care Council (CQI-CCC) at LHSC-UH, evaluating the effectiveness of superficial subcutaneous lidocaine for use in patients undergoing FASR. This paper details the process followed to evaluate this practice and reports on the subsequent findings and recommendations. A literature review, a retrospective chart audit, a blinded online survey and peer hospital polling were compiled, and a summary of findings was shared with the cardiac interventionists, with subsequent polling. No significant evidence for pain reduction was identified when lidocaine injections were administered prior to FASR. As such, a unanimous decision was reached to remove lidocaine from the LHSC Coronary Angioplasty Clinical Pathway order form.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.194
GPT teacher head0.364
Teacher spread0.169 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2013
Admission routes2
Has abstractyes

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