Predictors of Catastrophic Outcome after Endovascular Thrombectomy in Elderly Patients with Acute Anterior Circulation Stroke
Bibliographic record
Abstract
Objective: Avoiding a catastrophic outcome may be a more realistic goal than achieving functional independence in the treatment of acute stroke in octogenarians.This study aimed to investigate predictors of catastrophic outcome in elderly patients after an endovascular thrombectomy with an acute anterior circulation large vessel occlusion (LVO).Materials and Methods: Data from 82 patients aged ≥ 80 years, who were treated with thrombectomy for acute anterior circulation LVO, were analyzed.The association between clinical/imaging variables and catastrophic outcomes was assessed.A catastrophic outcome was defined as a modified Rankin Scale score of 4-6 at 90 days.Results: Successful reperfusion was achieved in 61 patients (74.4%), while 47 patients (57.3%) had a catastrophic outcome.The 90-day mortality rate of the treated patients was 15.9% (13/82).The catastrophic outcome group had a significantly lower baseline diffusion-weighted imaging-Alberta stroke program early CT score (DWI-ASPECTS) (7 vs. 8, p = 0.014) and a longer procedure time (42 minutes vs. 29 minutes, p = 0.031) compared to the non-catastrophic outcome group.Successful reperfusion was significantly less frequent in the catastrophic outcome group (63.8% vs. 88.6%,p = 0.011) compared to the non-catastrophic outcome group.In a binary logistic regression analysis, DWI-ASPECTS (odds ratio [OR], 0.709; 95% confidence interval [CI], 0.524-0.960;p = 0.026) and successful reperfusion (OR, 0.242; 95% CI, 0.071-0.822;p = 0.023) were independent predictors of a catastrophic outcome.Conclusion: Baseline infarct size and reperfusion status were independently associated with a catastrophic outcome after endovascular thrombectomy in elderly patients aged ≥ 80 years with acute anterior circulation LVO.
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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 | 0.003 |
| 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) | 0.001 | 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".