Abstract WP197: Autonomic Nervous System Parameters to Predict the Occurrence of Ischemic Events After Transient Ischemic Attack or Minor Stroke
Bibliographic record
Abstract
Background: Stress response is tightly regulated by the autonomic nervous system (ANS) which can be measured by heart rate variability (HRV). Traditional risk factors and acute triggers for ischemic stroke and transient ischemic attack (TIA) are considered as chronic and acute stressors, respectively. These risk factors all contribute to the recurrent ischemic events and are related to ANS dysfunction. The moderate predictive value of ABCD2 score may be due to assessing a limited number of stressors. Aims, Objectives and Hypotheses: We proposed to 1) assess whether HRV parameters, as markers of ANS function and stress, can predict secondary ischemic events after TIA or minor stroke, and 2) compare the HRV-based predictive tools with ABCD2 score. We expected that using HRV indicators can enhance the prediction of ischemic events. Methods: This is a prospective observational study. Patients developed TIA or minor stroke within 48 hours were eligible. The main study variables included: ABCD2 score, HRV assessment from 24-hour Holter recording, and psychological stress. HRV measurement included calculations of both absolute values and changes of HRV frequency-domain parameters: high frequency (HF), normalized HF, HF +low frequency, and total power. Patients were followed for 90 days to assess the development of outcome events. Logistic regression was employed for data analyses. Area under the curve (AUC) and diagnostic tests were used to assess models’ predictive power. Results: Final analyses include data collected from 201 patients. The most useful HRV predictors were Daytime HF changes (AUC=0.70) and Morning HF value (AUC=0.61). AUCs for the Best Stress Model and the Most Practical Model were 0.82 and 0.76, respectively, which were significantly higher than AUC of ABCD2 score (AUC=0.63), p <0.05. The optimal cut-off points for Daytime HF changes and Morning HF might be increase of 12.5% and 50 ms 2 , respectively. The exploratory models that involved both values and changes of HF had AUCs ≥0.82. Conclusions: Assessing the effects of stress on ANS may be an innovative way to stratify the risk of TIA or minor stroke. Models using HRV parameters, especially HF, provide superior predictive values to ABCD2 score. Future research is needed to validate these results.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".