Outcomes of mechanical thrombectomy after recent cardiovascular procedures: a multicenter descriptive cohort
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Large vessel occlusions (LVOs) in ischemic stroke represent a critical challenge, particularly in the peri-procedural setting of cardiovascular procedures (CVPs). Mechanical thrombectomy (MT) is a well-established treatment for LVOs; however, its outcomes in patients following recent CVPs remain unclear. OBJECTIVE: This multicenter retrospective cohort study aimed to evaluate the outcomes of MT in patients with ischemic stroke occurring within 30 days of CVPs. METHODS: We analyzed data from four centers, including patients aged ≥18 years who underwent MT for LVO within 30 days of CVPs. CVPs included both surgical (e.g. CABG, valve replacement) and minimally invasive procedures (e.g. TAVR, PCI). Baseline characteristics, procedural metrics, and outcomes, including NIHSS and mRS scores, were collected. Statistical analyses were performed using R software. RESULTS: Of 8,947 screened stroke patients, 27 met the inclusion criteria. The median age was 69 years (IQR 60-83), and 56% were male. Anterior circulation occlusions were present in 93% of cases, with a median baseline NIHSS score of 18 (IQR 14-21). Successful reperfusion (TICI ≥2b) was achieved in 85% of cases, with a median of one thrombectomy pass. At 90 days, 30% of patients achieved functional independence (mRS 0-2), while the mortality rate was 44%. Procedural complications were rare (3.7%). CONCLUSION: MT in patients with peri-procedural LVO after CVPs demonstrates success but poor functional recovery compared with baseline. These findings highlight the need for prospective studies to identify patients who may benefit most from MT in this high-risk population.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it