Etiologic Classification of TIA and Minor Stroke by A-S-C-O and Causative Classification System as Compared to TOAST Reduces the Proportion of Patients Categorized as Cause Undetermined
Bibliographic record
Abstract
BACKGROUND: The assortment of patients based on the underlying pathophysiology is central to preventing recurrent stroke after a transient ischemic attack and minor stroke (TIA-MS). The causative classification of stroke (CCS) and the A-S-C-O (A for atherosclerosis, S for small vessel disease, C for Cardiac source, O for other cause) classification schemes have recently been developed. These systems have not been specifically applied to the TIA-MS population. We hypothesized that both CCS and A-S-C-O would increase the proportion of patients with a definitive etiologic mechanism for TIA-MS as compared with TOAST. METHODS: Patients were analyzed from the CATCH study. A single-stroke physician assigned all patients to an etiologic subtype using published algorithms for TOAST, CCS and ASCO. We compared the proportions in the various categories for each classification scheme and then the association with stroke progression or recurrence was assessed. RESULTS: TOAST, CCS and A-S-C-O classification schemes were applied in 469 TIA-MS patients. When compared to TOAST both CCS (58.0 vs. 65.3%; p < 0.0001) and ASCO grade 1 or 2 (37.5 vs. 65.3%; p < 0.0001) assigned fewer patients as cause undetermined. CCS had increased assignment of cardioembolism (+3.8%, p = 0.0001) as compared with TOAST. ASCO grade 1 or 2 had increased assignment of cardioembolism (+8.5%, p < 0.0001), large artery atherosclerosis (+14.9%, p < 0.0001) and small artery occlusion (+4.3%, p < 0.0001) as compared with TOAST. Compared with CCS, using ASCO resulted in a 20.5% absolute reduction in patients assigned to the 'cause undetermined' category (p < 0.0001). Patients who had multiple high-risk etiologies either by CCS or ASCO classification or an ASCO undetermined classification had a higher chance of having a recurrent event. CONCLUSION: Both CCS and ASCO schemes reduce the proportion of TIA and minor stroke patients classified as 'cause undetermined.' ASCO resulted in the fewest patients classified as cause undetermined. Stroke recurrence after TIA-MS is highest in patients with multiple high-risk etiologies or cryptogenic stroke classified by ASCO.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".