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Record W2003301859 · doi:10.12968/bjca.2010.5.4.47419

Changing practice: A nurse and physiologist-led tilt-testing service

2010· article· en· W2003301859 on OpenAlexaff
Michael Sampson, Amy Lovegrove, Laura Gillam

Bibliographic record

VenueBritish Journal of Cardiac Nursing · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsOntario Stroke Network
Fundersnot available
KeywordsMedicineTest (biology)AuditService (business)Protocol (science)Medical emergencyOrthostatic vital signsIntensive care medicinePhysical therapyAlternative medicineBlood pressureInternal medicine

Abstract

fetched live from OpenAlex

Tilt testing is used to investigate syncope, dizziness and falls. It may also be used to test a diagnosis of epilepsy. This article discusses the rationale for tilt testing, and the method used. Practical considerations and recommended practice are outlined. Interpretation of results is also considered, and the common conditions for which tilt testing can aid diagnosis. These include reflex syncope, orthostatic hypotension and postural or thostatic tachycardia syndrome. This provides the background to the redesign of a tilt-testing service at a metropolitan hospital. The physician-led service was inefficient, with frequent delays, overruns and cancellations. Waiting times were long, and adherence to recognized test protocols was variable. The service was redesigned to be led by nurses and physiologists and the test protocol set out in a formal policy document. Test reporting was improved, and service capacity increased. An audit carried out after 12 months showed that the new service had reduced waiting times, increased adherence to the test protocol and increased patient satisfaction. Safety was not compromised by the removal of direct medical supervision.

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)0.001
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 score0.965
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.273
Teacher spread0.265 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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