Mortality Following Intracerebral Hemorrhage After Intravenous Alteplase in Acute Ischemic Stroke: A Decision Tree-Based Classification Approach
Bibliographic record
Abstract
Background: Intracerebral hemorrhage (ICH) after intravenous (IV) alteplase in acute ischemic stroke (AIS) can be assessed clinically as asymptomatic ICH (asICH) or symptomatic ICH (sICH) according to the European Cooperative Acute Stroke Study II (ECASS II) definition, and radiographically as hemorrhagic infarction types 1-2 (HI1-2) or parenchymal hematoma types 1-2 (PH1-2). Reported mortality in sICH ranges from 7.8% to 42.8%, with PH2 carrying the highest risk, up to 50%. Although some patients may benefit from neurosurgical intervention, the prognostic overlap between clinical and radiographic classifications remains unclear. A decision tree approach may clarify mortality risk across subgroups and aid early triage. Methods: This prognostic descriptive study employed a retrospective cohort design at the Stroke Center, Lampang Hospital. Patients aged ≥ 18 years with AIS who received IV alteplase between January 2017 and December 2024 were included. A decision tree framework was constructed to examine 7-day mortality, incorporating clinical classification, radiographic subtype, and neurosurgical intervention as decision nodes. Results: Among 94 patients, asICH occurred in 44 (46.8%) and sICH in 50 (53.2%). In the asICH group, HI2 was the predominant subtype (24/44, 54.6%) and all survived. In the sICH group, PH2 was the leading subtype (30/50, 60.0%). Mortality was influenced by surrogate compliance with neurosurgical advice: refusal of surgery after recommendation resulted in 100% mortality, whereas acceptance reduced mortality to 43.8% (P = 0.043). Conclusion: Post-alteplase ICH had a 7-day mortality of 27%. The decision tree framework offered a simple visualization for early risk stratification and may help support clinical decision-making.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".