Supplementary Material for: Validation of the Canadian TIA Score to Predict Subsequent Stroke Risk in Chinese TIA Patients
Bibliographic record
Abstract
Background and Objectives: The Canadian TIA Score has been verified as a good predictive tool for subsequent stroke risk in Caucasian patients; however, it had insufficient external verification of other races. We aimed to validate the Canadian TIA Score in Chinese patients and compared it with ABCD2 for subsequent stroke risk after transient ischemic attack (TIA). Methods: The Third China National Stroke Registry (CNSR-III) was a nationwide, multicenter prospective registry recruiting consecutive patients with acute ischemic stroke or TIA within 7 days of the onset from August 2015 to March 2018. The Canadian TIA Score was verified in patients diagnosed with TIA from the CNSR-III (N = 1,184). The outcomes were subsequent stroke at 7 days, 14 days/discharge, 3 months, and 1 year. Outcomes were recorded by face-to-face assessment or telephone interview. The prognostic performance of the scoring system was assessed by the area under the receiver operator characteristic curve (AUC). Results: Of 1,184 TIA patients (mean [IQR] age, 61.00 [53.00–69.00] years; 413 women [34.88%]), there were 40 patients (3.38%) having subsequent stroke within 7 days, 45 (3·80%) within 14 days/hospitalization, 66 (5·57%) within 3 months, and 100 (8·45%) within 1 year. The Canadian TIA Score (AUC 0 63–0·68) seemed to be a better prognostic score of stroke risk than the ABCD2 score (AUC 0·61–0·62), although no significant differences were noted. In the subgroup of atypical TIA, the Canadian TIA Score showed significantly stronger predictivity than the ABCD2 score within 7 days (0.80 [0.62–0.98] vs. 0.52 [0.30–0.73]; difference in AUC, 0.28 [0.03–0.53]; p, 0.026), and marginal significantly stronger predictivity within 1 year (0.71 [0.61–0.80] vs. 0.58 [0.48–0.68]; difference in AUC, 0.12 [−0.01 to 0.25]; p, 0.06). Conclusion: The Canadian TIA Score might be a better prognostic score than the ABCD2 score for post-TIA stroke risk, especially in patients with atypical TIA.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.709 | 0.153 |
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".