Abstract TP318: Hemorrhagic Transformation in Acute Ischemic Stroke: A Quantitative Systematic Review
Bibliographic record
Abstract
Objective: Hemorrhagic transformation (HT) is common in patients with acute ischemic stroke and is associated with poor outcome. However, the accurate prevalence and risk factors for HT are uncertain. We aim to characterize rates, risk factors and prognosis of HT. Methods: We conducted a systematic review and meta-analysis of all published English literature of patients with acute ischemic stroke and HT. Medline and EMBASE were searched between 1985 and 2017, 2,099 relevant publications were identified. To obtain comparable data we included only studies that used the ECASS-2 definitions of Hemorrhagic Transformation and Parenchymal Hematoma (PH). Patients treated with intravenous thrombolysis (IV-tPA) were compared with those who did not receive thrombolysis. Results: Eligible studies (n=65) with 17,259 patients in total were included in this analysis. The overall prevalence of HT was 27% (95% CI 23-30); Patients not treated with IV-tPA had a prevalence of 20% (95% CI 14-27) vs. 32% (95% CI 27-37) in those treated. The overall prevalence of PH was 9% (95% CI 8-11); in untreated patients prevalence was 5% (95% CI 4-7) vs. 12% (95% CI 10-15) in the IV-tPA treated patients. The risk of HT was higher with: history of atrial fibrillation (OR 2.94, CI 2-4), use of anticoagulants (OR 2.47, 95% CI 1.6-4), higher NIHSS score (Hedge’s G 0.96, 95% CI 0.5-1.4), DWI infarct volume (Hedge’s G 0.8, 95% CI 0.01-1.5) and glucose level (Hedge’s G 0.4, CI 0.16-0.6). LDL was negatively correlated with HT (Hedge’s G -0.3, 95% CI -0.12- -0.48). Interactions were explored for factors associated with HT and thrombolysis treatment. In patients treated with IV-tPA, risk of PH was associated with antiplatelet use (OR 3, 95% CI 1-7), statin treatment (OR 4, 95% CI 1-9) and history of hypertension (OR 1.5, 95% CI 1.1-2). Poor 90-day outcome (mRS 5-6) was associated with HT (OR 3) and PH (OR 8). Conclusion: HT is common, even in patients not treated with IV-tPA, and tends to occur in patients with large and severe strokes. HT, and PH in particular, are associated with poor outcomes. Risk factors for HT should be identified to reduce burden of disability and future high quality . Prospective Longitudinal studies are warranted.
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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 | 0.012 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".