Pretreatment ASPECTS on DWI predicts 3-month outcome following rt-PA
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether the pretreatment Alberta Stroke Programme Early CT Score (ASPECTS) assessed using diffusion-weighted imaging (DWI) predicts stroke outcomes at 3 months following IV recombinant tissue-type plasminogen activator (rt-PA) therapy. METHODS: Stroke patients treated with rt-PA (0.6 mg/kg alteplase) in 10 stroke centers in Japan were retrospectively studied. ASPECTS was assessed on DWI just prior to rt-PA injection. The primary outcome was a modified Rankin Scale (mRS) score of 0-2 at 3 months. Secondary outcomes included death at 3 months and symptomatic intracerebral hemorrhage (sICH) within 36 hours. RESULTS: For the 477 patients (316 men, 71 +/- 11 years old) enrolled, the median NIH Stroke Scale score was 13 (interquartile range 7-18.5), the median ASPECTS on DWI was 8 (7-10), and sICH was identified in 15 patients (3.1%). At 3 months, 245 (51.4%) had an mRS score of 0-2, and 29 (6.1%) had died. Patients with an mRS score of 0-2 had higher median ASPECTS (9; interquartile range 8-10) than other patients (8; 6-9, p < 0.001). Using receiver operating characteristic curves, the optimal cutoff ASPECTS to predict an mRS score of 0-2 was > or =7. On multivariate regression analysis, ASPECTS > or =7 was related to an mRS score of 0-2 (odds ratio 1.85; 95% confidence interval 1.07-3.24), ASPECTS < or =4 was related to death (3.61; 1.23-9.91), and ASPECTS < or =5 was related to sICH (4.74; 1.54-13.64). CONCLUSION: ASPECTS on DWI was independently predictive of functional and vital outcomes at 3 months, as well as sICH within 36 hours, following rt-PA therapy for stroke patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".