Validation Assessment of Risk Scores to Predict Postthrombolysis Intracerebral Haemorrhage
Bibliographic record
Abstract
BACKGROUND: Two clinical risk scores, the Haemorrhage After Thrombolysis and Multicentre Stroke Survey scores, have been proposed to predict the risk of intracerebral haemorrhage following thrombolysis in acute ischaemic stroke. AIMS: To validate Haemorrhage After Thrombolysis and Multicentre Stroke Survey scores as predictors of post-tissue plasminogen activator symptomatic intracerebral haemorrhage and asymptomatic intracerebral haemorrhage in an independent cohort. METHODS: Haemorrhage After Thrombolysis and Multicentre Stroke Survey scores were calculated for the cohort of tissue plasminogen activator-treated patients enrolled in the placebo arms of the SAINT-I and SAINT-II trials. The absolute risk of symptomatic intracerebral haemorrhage and asymptomatic intracerebral haemorrhage associated with each scoring system was determined. The overall predictive value was assessed using c-statistics. RESULTS: Symptomatic intracerebral haemorrhage occurred in 5.6% of 965 patients treated with tissue plasminogen activator in the SAINT cohorts. The risk of symptomatic intracerebral haemorrhage was modestly greater, with higher Haemorrhage After Thrombolysis scores (0: 4.1%, 1: 4.1%, 2: 8.8%, 3: 12.5%, 4: 0%, 5: no subjects). Similar results were seen with the Multicentre Stroke Survey score (0: 0%, 1: 4.8%, 2: 2.3%, 3: 7.3%, 4: 6.3%). In logistic regression, the Haemorrhage After Thrombolysis score was associated with the risk of symptomatic intracerebral haemorrhage (odds ratio = 1.41 per point, 95% confidence interval: 1.05-1.89, P = 0.021) and asymptomatic intracerebral haemorrhage (odds ratio = 1.59 per point, 95% confidence interval: 1.33-1.92, P< 0.001). The Multicentre Stroke Survey score was modestly associated with the risk of symptomatic intracerebral haemorrhage (odds ratio = 1.43 per point, 95% confidence interval: 0.95-2.15, P = 0.084) and asymptomatic intracerebral haemorrhage (odds ratio = 1.63 per point, 95% confidence interval: 1.27-2.08, P < 0.001). The c-statistic was 0.59 for predicting symptomatic intracerebral haemorrhage and 0.61 for asymptomatic intracerebral haemorrhage for both the Haemorrhage After Thrombolysis and the Multicentre Stroke Survey scores. CONCLUSIONS: While both the Haemorrhage After Thrombolysis and Multicentre Stroke Survey scores were associated with a risk of symptomatic intracerebral haemorrhage, discriminatory ability was limited.
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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 | 0.029 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".