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Record W4282946024 · doi:10.1016/j.cnc.2022.02.009

Setting a Benchmark for Quality of Care

2022· review· en· W4282946024 on OpenAlexaff
Sandra Lauck, Gemma McCalmont, Amanda Smith, Bettina Højberg Kirk, Marjo de Ronde-Tillmans, Steffen Wundram, Nassim Adhami

Bibliographic record

VenueCritical Care Nursing Clinics of North America · 2022
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of British ColumbiaHamilton Health SciencesSt. Paul's Hospital
Fundersnot available
KeywordsMedicineReferralValve replacementQuality managementQuality (philosophy)valvular heart diseaseStenosisBenchmark (surveying)Intensive care medicineHealth careClinical PracticeNursingMedical emergencyOperations managementCardiology

Abstract

fetched live from OpenAlex

Transcatheter aortic valve replacement (TAVR) is an established therapy for the treatment of severe aortic stenosis. The evolution of technology and procedural approaches has facilitated the development of streamlined clinical pathways to optimize patient care and improve outcomes. The revision of historical practices and the adoption of contemporary best practices throughout patients' journey from referral to discharge create opportunities to drive quality improvement. Nursing expertise and leadership are essential to recalibrate preprocedure, periprocedure, and postprocedure practice to transform the way we care for TAVR, achieve excellent outcomes, and promote high-performing health services for the treatment of valvular heart disease.

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)0.018
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0070.007
Open science0.0020.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0070.002

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 head0.101
GPT teacher head0.536
Teacher spread0.436 · 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 designNot applicable
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

Citations14
Published2022
Admission routes1
Has abstractyes

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