Association of Cardiac Biomarkers in Combination With Cognitive Impairment After Acute Ischemic Stroke
Bibliographic record
Abstract
Background Poststroke cognitive impairment is a severe and common clinical complication that constitutes a substantial global health burden. We aimed to evaluate the association of 3 cardiac biomarkers in combination with poststroke cognitive impairment and their prognostic significance. Methods and Results This prospective study included 566 patients with ischemic stroke. Cardiac biomarkers, including sST2 (soluble suppression of tumorigenicity‐2 receptor), GDF‐15 (growth differentiation factor‐15), and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide), were measured. Cognitive impairment was defined as a Mini‐Mental State Examination score of <27 or a Montreal Cognitive Assessment score of <25 at 3 months after ischemic stroke. Odds of cognitive impairment 3 months after ischemic stroke increased with the number of elevated cardiac biomarkers (sST2, GDF‐15, and NT‐proBNP; P trend <0.001). The multivariable adjusted odds ratios (95% CIs) of cognitive impairment defined by the Mini‐Mental State Examination and Montreal Cognitive Assessment were 2.45 (1.48–4.07) and 1.86 (1.10–3.14) for the participants with ≥2 elevated cardiac biomarkers, respectively, compared with those without any elevated cardiac biomarker. Additionally, higher cardiac biomarker scores were associated with an increased risk of cognitive impairment ( P trend <0.05). Simultaneously adding all 3 cardiac biomarkers to the basic model with traditional risk factors significantly improved the risk prediction of Mini‐Mental State Examination‐defined cognitive impairment (net reclassification improvement=34.99%, P <0.001; integrated discrimination index=2.67%, P <0.001). Similar findings were observed using the Montreal Cognitive Assessment scores. Conclusions An increased number of elevated novel cardiac biomarkers were associated with an increased odds of poststroke cognitive impairment, suggesting that a combination of these cardiac biomarkers may improve the risk prediction of cognitive impairment. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01840072.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".