The Utility of Echocardiogram in the Workup of Ischemic Stroke Patients
Bibliographic record
Abstract
ABSTRACT: Background: Cardiac sources of emboli can be identified by transthoracic echocardiogram (TTE). The Canadian Best Practice Guidelines recommend routine use of TTE in the initial workup of ischemic stroke when an embolic source is suspected. However, TTEs are commonly ordered for all patients despite insufficient evidence to justify cost-effectiveness. We aim to evaluate the TTE ordering pattern in the initial workup of ischemic stroke at a regional Stroke Center in Central South Ontario and determine the proportion of studies which led to a change in management and affected length of stay (LOS). Methods: Hospital records of 520 patients with a discharge diagnosis of TIA or ischemic stroke between October 2016 and June 2017 were reviewed to gather information Results: 477 patients admitted for TIA or ischemic stroke met inclusion criteria. 67.9% received TTE, out of which 6.0% had findings of cardiac sources of emboli including left ventricular thrombus, atrial septal aneurysm, PFO, atrial myxoma, and valvular vegetation. 2.5% of all TTE findings led to change in medical management. The median LOS of patients who underwent TTE was 2 days longer (p < 0.00001). Conclusion: TTE in the initial workup of TIA or ischemic stroke remains common practice. The yield of TTEs is low, and the proportion of studies that lead to changes in medical management is minimal. TTE completion was associated with increased LOS and may result in increased healthcare spending; however, additional factors prolonging the LOS could not be excluded.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".