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Record W2096824442 · doi:10.12968/bjca.2015.10.3.145

What is the value of a nurseled clinic for patients with replacement heart valves?

2015· article· en· W2096824442 on OpenAlexaff
Denise Parkin, John B. Chambers

Bibliographic record

VenueBritish Journal of Cardiac Nursing · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineSonographerMedical emergencyMultidisciplinary teamValve replacementNurse practitionersEmergency medicineCardiologySurgeryNursingHealth careUltrasonography

Abstract

fetched live from OpenAlex

Background: Long-term regular specialist surveillance is recommended to reduce the risks of complications arising after heart valve surgery. This could be delivered by a nurse-led valve clinic. Aims: To determine how often clinical events are detected within a nurse-led valve clinic and how often a cardiologist or sonographer is required. Methods: Nurse-led valve clinic outcomes and events were analysed over 48 months from 2010 to 2013. An endpoint was any new symptom or event or the need for an unscheduled echocardiogram. Results: There were 544 visits in 206 patients. Endpoints were found in 178 visits (33%). A cardiologist was required in 100 visits (18%) to see the patient in 27 and give advice in 73. Another clinician was needed in 8 visits. Unscheduled echocardiography was required in 70 (13%) visits. Conclusion: A nurse-led valve clinic is feasible. Clinical endpoints are detected frequently and enhanced long-term care can be safely provided. Review or discussion with a cardiologist or unscheduled echocardiography is sometimes required which supports the model of a multidisciplinary clinic.

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)0.001
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 score0.301
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
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 head0.016
GPT teacher head0.347
Teacher spread0.330 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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