Abstract TP223: Association Between Stroke Severity And Cardiac Troponins In Acute Stroke
Bibliographic record
Abstract
Introduction: Cardiac troponins are often elevated in patients with acute stroke and have been associated poor outcomes. Whether the elevation in cardiac troponins, a marker of acute myocardial injury, is due to neurogenic mechanisms or the underlying cardiac risk factors is unknown. We evaluated the association between stroke severity and serum cardiac troponin levels in people with acute stroke. Methods: We conducted a retrospective study of adults (≥ 40 years) with a discharge diagnosis of imaging confirmed stroke admitted to a quaternary stroke centre in Toronto, Canada between January 1, 2018 and December 31, 2018. We collected demographic and clinical information, including stroke severity using the National Institutes of Health Stroke Scale [NIHSS], modelled as a continuous variable. We recorded serum cardiac troponin levels on admission. We modelled serum troponin level both as a continuous and a categorical variable (normal vs. high, ≥ 15 ng/L). We evaluated the association between admission NIHSS and serum troponin level using multivariable negative binomial models and logistic regression models, adjusting for demographics (age and sex) and comorbidities [history of congestive heart failure or stroke, stroke type (ischemic vs. hemorrhagic), ST elevation on ECG, and creatinine levels]. Results: We included 218 patients with acute stroke (median age 76 years, 48.6% women), of whom 190 (87.2%) had an ischemic stroke. Median NIHSS was 6 (Q1-Q3, 2-14), and median cardiac troponin level was 17 ng/L (Q1-Q3, 9-30), with 108 (53.2%) patients having higher than normal levels. A one-point increase in NIHSS (stroke severity) was associated with a higher serum troponin level in age- and sex- (RR 1.03; 1.00-1.05) and multivariable- (RR 1.03; 1.01-1.05) adjusted models. However, stroke severity was not associated with the odds of having high troponin levels in adjusted models (OR 1.03; 0.98-1.08). Conclusions: The modest, yet independent, association between greater stroke severity and higher cardiac troponins in patients with acute stroke could suggest a neurogenic basis for mild cardiac injury in patients with acute stroke. Future work on the association between elevated troponin and poor stroke outcomes should account for stroke severity on admission.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".