Age disparity in diagnostic evaluation of stroke patients: Embolic Stroke of Undetermined Source Global Registry Project
Bibliographic record
Abstract
Abstract Introduction Incomplete evaluation of stroke patients may result in an unclear diagnosis. Our objective was to determine if older stroke patients more often undergo incomplete diagnostic evaluations versus younger patients in an international cohort. Patients and methods The Embolic Stroke of Undetermined Source Global Registry was a retrospective cohort of consecutive stroke patients evaluated at 19 stroke centers in 19 countries. Diagnostic evaluation was considered as complete if the patient had, at a minimum, brain computed tomography or magnetic resonance imaging with evidence of infarction, extracranial and intracranial vascular imaging, electrocardiography, ≥24 h of cardiac rhythm monitoring, and echocardiography. Patients were diagnosed with Embolic Stroke of Undetermined Source if brain imaging confirmed a nonlacunar infarction and no stroke etiology was determined after complete evaluation. Completeness of evaluation was compared between patients ≥75 versus <75 years old. Results The registry included 2132 patients with recent ischemic stroke during 2013–2014, of which 349 were diagnosed with Embolic Stroke of Undetermined Source. Embolic Stroke of Undetermined Source patients ≥75 years were less likely to undergo brain magnetic resonance imaging (74% versus 89%, p = 0.001), transesophageal echocardiography (22% versus 39%, p = 0.005), and combination transthoracic and transesophageal echocardiography (16% versus 32%, p = 0.005) compared with Embolic Stroke of Undetermined Source patients <75 years. Discussion Our study has identified an international age disparity in fundamental diagnostic testing for older patients with stroke of unknown etiology. Some testing biases were affected by geographic location (e.g., brain MRI was less frequently used in European ESUS patients), whereas other testing was implemented less frequently in the elderly regardless of location (e.g., transesophageal echocardiogram). Conclusion Older patients in this international cohort had less sophisticated diagnostic testing for stroke, despite advanced age being well established as an independent risk factor for recurrent stroke. This was a global problem and further investigations are warranted to explore the cause.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".