P.107 Acute thrombectomy in patients of 80 years and older: a retrospective analysis of radiological and clinical outcomes with an intention to treat analysis
Bibliographic record
Abstract
Background: The safety and clinical outcomes of thrombectomy in the 80 years or older age group are not yet clear. Our aim is to provide data from clinical practice to assess the safety and efficacy of endovascular thrombectomy in this age group. Methods: We retrospectively reviewed consecutive patients of age ≥80 referred for thrombectomy procedures at our institutions from 01/01/2015 to 01/09/2015. We collected demographic data, risk factors, clinical and radiological findings, treatment details, clinical and radiological outcomes. Results: Data for 75 patients was included. Baseline clinical characteristics are similar to previous trials. There were MCA occlusions in 49% (37/75) and tandem occlusions in 15% (11/75) patients. 67% (50/75) patients received IVtPA. Good reperfusion (mTICI 2b/3) was achieved in 60% (45/75) patients within 224 minutes. Good clinical outcome (mRS 0-2) at 90 days was achieved in 31% (23/75) patients. Results are similar to HERMES data on patients of age ≥80 and differences will be discussed. Conclusions: Our study adds valuable evidence to the limited data on safety and clinical outcomes in patients 80 years of age and older who undergo thrombectomy. Our findings support the data from clinical trials and confirm that mechanical thrombectomy can be performed safely and in a timely fashion outside of trials with similar results.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".