MétaCan
Menu
← Back to cohort
Record W2914774033 · doi:10.1161/str.50.suppl_1.wp380

Abstract WP380: Hospital-Level Variability in Diagnostic Testing and Ischemic Stroke Subtype Documentation

2019· article· en· W2914774033 on OpenAlexaff
Shyam Prabhakaran, Steven R. Messé, Dawn Kleindorfer, Eric E. Smith, Gregg C. Fonarow, Xin Zhao, Barbara L. Lytle, Joaquin E. Cigarroa, Lee H. Schwamm

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineStroke (engine)DocumentationInternal medicineMedical recordIschemic strokeEmergency medicineCardiologyIschemia

Abstract

fetched live from OpenAlex

Objective: Documentation of ischemic stroke subtype has clinical and research implications. We aimed to assess hospital-level variability in subtype documentation and diagnostic testing patterns in the Get With The Guidelines (GWTG)-Stroke registry. Methods: We identified patients admitted with ischemic stroke to GWTG-Stroke participating hospitals between January 1, 2016 and September 30, 2017. Sites were instructed on use of the TOAST criteria for subtype documentation. We assessed hospital-level variability in TOAST subtype documentation and, among those with subtype documented, the performance of echocardiography, cerebrovascular imaging, and cardiac rhythm monitoring. Results: Among 607,563 patients with ischemic stroke from 1,906 sites, 348,715 (57.4%) had documented ischemic stroke subtype. Considerable hospital-level variability was observed in subtype documentation (Figure A). Patients with subtype documentation were more likely to be inter-facility transfers and treated at higher volume and academic centers, have complete medical history data, and have higher rates on achievement and quality measures. Carotid and intracranial vascular imaging (69.1% and 58.7%, respectively), echocardiography (74.3%), and cardiac rhythm monitoring (76.2%) were performed most frequently in cryptogenic stroke (CS) patients compared to other subtypes (Figure B; p<0.001 for each comparison). Among CS patients, short-term cardiac rhythm monitoring (65.7%) was most common with only 6.1% undergoing extended surface cardiac rhythm monitoring and 4.4% receiving extended implantable cardiac rhythm monitoring. Conclusions: In a large contemporary nationwide dataset of acute ischemic stroke hospitalizations, we observed that stroke subtype is documented in 57.4% of records, raising an important opportunity for quality improvement. Furthermore, diagnostic testing patterns suggest incomplete evaluation is common, even among patients with CS.

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)0.007
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueStroke→Same topicAcute Ischemic Stroke Management→French-language works237,207→