Management of Thrombolysis-Associated Symptomatic Intracerebral Hemorrhage
Bibliographic record
Abstract
BACKGROUND: Symptomatic intracerebral hemorrhage (sICH) is the most devastating complication of thrombolytic therapy for acute stroke. It is not clear whether patients with sICH continue to bleed after diagnosis, nor has the most appropriate treatment been determined. METHODS: We performed a retrospective analysis of our prospectively collected Get With the Guidelines-Stroke database between April 1, 2003, and December 31, 2007. Radiologic images and all procoagulant agents used were reviewed. Multivariable logistic regression was performed to identify factors associated with in-hospital mortality. RESULTS: Of 2362 patients with acute ischemic stroke during the study period, sICH occurred in 19 of the 311 patients (6.1%) who received intravenous tissue plasminogen activator and 2 of the 72 (2.8%) who received intra-arterial thrombolysis. In-hospital mortality was significantly higher in patients with sICH than in those without (15 of 20 [75.0]% vs 56 of 332 [16.9%], P < .001). Eleven of 20 patients (55.0%) received therapy for coagulopathy: 7 received fresh frozen plasma; 5, cryoprecipitate; 4, phytonadione (vitamin K(1)); 3, platelets; and 1, aminocaproic acid. Independent predictors of in-hospital mortality included sICH (odds ratio, 32.6; 95% confidence interval, 8.8-120.2), increasing National Institutes of Health Stroke Scale score (1.2; 1.1-1.2), older age (1.3; 1.0-1.7), and intra-arterial thrombolysis (2.9; 1.4-6.0). Treatment for coagulopathy was not associated with outcome. Continued bleeding (>33% increase in intracerebral hemorrhage volume) occurred in 4 of 10 patients with follow-up scans available (40.0%). CONCLUSIONS: In many patients with sICH after thrombolysis, coagulopathy goes untreated. Our finding of continued bleeding after diagnosis in 40.0% of patients suggests a powerful opportunity for intervention. A multicenter registry to analyze management of thrombolysis-associated intracerebral hemorrhage and outcomes is warranted.
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 | 0.000 |
| 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".