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Tia Management in The Ed (Time) : One Stroke Center'S Efforts To Improve Access To Timely Secondary Stroke Prevention Services

2017· other· en· W6889726402 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)ReferralPopulationPresentation (obstetrics)Disease

Abstract

fetched live from OpenAlex

A transient ischemic attack (TIA) is a brief episode of neurological dysfunction typically lasting under 60 minutes. Patients presenting with TIA are at increased risk of recurrent stroke, particularly within the first week following initial event. Health Sciences North (HSN) is a Regional Stroke Centre, located in Sudbury, Canada. In 2016, 161 people presented to ED with presentation of TIA. Managed solely by the ED, the Stroke Program is not involved in the visit. Recent data shows 28% of ED TIA patients are discharged home without a referral to the secondary stroke prevention clinic. When necessary, TIA patients are admitted. HSNu2019s annual average length of stay (LOS) at HSN in 2016-17 was 4.5 days. The stroke prevention clinic has limited service availability, receiving 375 referrals annually. The average wait time for the clinic, for those at highest risk is 2.7 days. Only 10% are seen in the timely manner set out by Canadian Stroke Best Practice Recommendations. The eight month pilot study TIME began January 1st 2018 whereby the Stroke Programu2019s Medical Lead physician will respond to all TIA presentations to ED to establish the TIA diagnosis, identify stroke mimics, facilitate best practice work-up, admit when very high risk features warrant, initiate secondary stroke prevention medications, dispense education package and refer to prevention clinic. Our hypothesis is that TIME will have a positive impact on % referrals to clinic at ED discharge; TIA admission rate; TIA inpatient LOS; wait time to clinic. Pilot evaluation will yield early results in October 2018.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0340.013
Science and technology studies0.0010.000
Scholarly communication0.0230.027
Open science0.0320.035
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0290.038

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 head0.056
GPT teacher head0.363
Teacher spread0.307 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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