Does Clinical-CT ‘Mismatch’ Predict Early Response to Treatment with Recombinant Tissue Plasminogen Activator?
Bibliographic record
Abstract
BACKGROUND: We hypothesized that patients with clinically severe strokes but less severe early ischemic changes on brain CT (i.e., clinical-CT mismatch) may respond better to intravenous recombinant tissue plasminogen activator (i.v. rt-PA) within 3 h of symptom onset. METHODS: In this secondary analysis of the CLOTBUST data, patients with middle cerebral artery occlusions on transcranial Doppler (TCD) were treated with i.v. rt-PA. Alberta Stroke Program Early CT Scores were obtained with raters blinded to the NIH Stroke Scale and TCD results. Two mismatch criteria and three criteria of response to therapy were explored. RESULTS: Of 126 patients, 67% had a mismatch type 1 and 74% had a mismatch type 2. The presence of clinical-CT mismatch by either definition did not correlate with any of the three criteria of response to rt-PA. Recanalization was a strong determinant of response, whether or not mismatch was present. CONCLUSIONS: Mismatch between severity of neurological deficit and CT findings is common but does not predict response to rt-PA therapy given within 3 h.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".