O-007 Bridging thrombolysis yields diminished benefit among elderly stroke patients treated with endovascular thrombectomy
Bibliographic record
Abstract
Background Endovascular thrombectomy (EVT) and intravenous thrombolysis (IVT) are both effective treatments for patients with large vessel occlusion (LVO) acute ischemic stroke, however, it is unclear whether intravenous thrombolysis (IVT) prior to endovascular thrombectomy (EVT), also termed bridging thrombolysis, is beneficial for all patients. Methods This was a large-scale cross-sectional study of the 2016-2020 National Inpatient Sample (NIS) database. Adult EVT patients presenting directly to thrombectomy centers without prior treatment were identified. Patient demographics, stroke risk factors, stroke etiology, medical comorbidities, and IVT treatment were recorded. Primary outcome was in-hospital mortality. Secondary outcomes include rates of discharge to home and hemorrhagic complications. Multivariable logistic regression models were used to account for possible confounders. Results 35,735 EVT patients were identified, of whom 32.5% (11,630 patients) were treated with IVT. Overall, bridging thrombolysis was significantly associated with lower rates of in-hospital mortality (8.8% vs. 11.2%, p<0.001) and higher rates of discharge to home (38.0% vs. 28.7%, p<0.001). Age stratified analyses revealed that IVT’s association with lower odds of in-hospital mortality was significantly attenuated with increasing age (interaction p=0.038), and that there is no significant association between IVT treatment with in-hospital mortality in elderly patients after multivariable adjustments (80-89 years old, OR 0.99 [95%CI 0.72-1.35], p=0.94). Similarly, older age significantly amplifies the hemorrhagic risk associated with bridging thrombolysis (interaction p=0.006). When considering only patients without hemorrhagic complications, age does not significantly modulate IVT’s association with in-hospital mortality (interaction p=0.61). Conclusions Bridging thrombolysis may be associated with better outcomes in a real-world setting; however, this association is diminished among elderly patients due to higher rates of hemorrhagic complications. Meta-analyses of trial data and future prospective studies are needed to fully elucidate the benefits and risks of bridging thrombolysis in the elderly population. Disclosures H. Chen: None. M. Khunte: None. M. Colasurdo: None. A. Malhotra: None. D. Gandhi: 1; C; National Institutes of Health, Focused Ultrasound Foundation, MicroVention, University of Calgary, University of Maryland Medical Center.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".