Bridging May Increase the Risk of Symptomatic Intracranial Hemorrhage in Thrombectomy Patients With Low Alberta Stroke Program Early Computed Tomography Score.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE Whether intravenous thrombolysis (IVT) increases the risk for symptomatic intracranial hemorrhage (sICH) in patients treated with mechanical thrombectomy (MT) is a matter of debate. Purpose of this study was to evaluate the extent of early ischemia as a possible factor influencing the risk for sICH after IVT+MT versus direct MT. METHODS An explorative analysis of the BEYOND-SWIFT (Bernese-European Registry for Ischemic Stroke Patients Treated Outside Current Guidelines With Neurothrombectomy Devices Using the SOLITAIRE FR With the Intention for Thrombectomy) multicenter cohort was performed. We hypothesized that the sICH risk between IVT+MT versus direct MT differs across the strata of Alberta Stroke Program Early Computed Tomography Scores (ASPECTS). For this purpose, all patients with ICA, M1, and M2 vessel occlusions and available noncontrast computed tomography or diffusion-weighed imaging ASPECTS (n=2002) were analyzed. We used logistic regression analysis in subgroups, as well as interaction terms, to address the risk of sICH in IVT+MT versus direct MT patients across the ASPECTS strata. RESULTS In 2002 patients (median age, 73.7 years; 50.7% women; median National Institutes of Health Stroke Scale score, 16), the overall rate of sICH was 6.5% (95% CI, 5.5%-7.7%). Risk of sICH differed across ASPECTS groups (9-10: 6.3%; 6-8: 5.6% and ≤5 9.8%; P=0.042). With decreasing ASPECTS, the risks of sICH in the IVT+MT versus the direct MT group increased from adjusted odds ratio of 0.61 ([95% CI, 0.24-1.60] ASPECTS 9-10), to 1.72 ([95% CI, 0.69-4.24] ASPECTS 6-8) and 6.31 ([95% CI, 1.87-21.29] ASPECTS ≤5), yielding a positive interaction term (1.91 [95% CI, 1.01-3.63]). Sensitivity analyses regarding diffusion-weighed imaging versus noncontrast computed tomography ASPECTS did not alter the primary observations. CONCLUSIONS The extent of early ischemia may influence relative risks of sICH in IVT+MT versus direct MT patients, with an excess sICH risk in IVT+MT patients with low ASPECTS. If confirmed in post hoc analyses of randomized controlled trial data, IVT may be administered more carefully in patients with low ASPECTS eligible for and with direct access to MT.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".