The proximal balloon occlusion together with direct thrombus aspiration (protect plus) technique: Experience at a tertiary comprehensive stroke center
Bibliographic record
Abstract
Background Timely restoration of cerebral blood flow using reperfusion therapy is the most effective maneuver for salvaging penumbra. We re-evaluated the previously described PROTECT (PRoximal balloon Occlusion TogEther with direCt Thrombus aspiration during stent retriever thrombectomy) Plus technique at a tertiary comprehensive stroke center. Methods We retrospectively analyzed all patients who underwent mechanical thrombectomy with stentrievers between May 2011 and April 2020. Patients were divided between those who underwent PROTECT Plus and those who did not (proximal balloon occlusion with stent retriever only). We compared the groups in terms of reperfusion, groin to reperfusion time, symptomatic intracranial hemorrhage (sICH), modified Rankin Scale (mRS) score at discharge. Results Within the study period, 167 (71.4%) PROTECT Plus and 67 (28.6%) non-PROTECT patients which met our inclusion criteria. There was no statistically significant difference in the number of patients with successful reperfusion (mTICI >2b) between the techniques (85.0% vs 82.1%; p = 0.58). The PROTECT Plus group had lower rates of mRS ≤2 at discharge (40.1% vs 57.6%; p = 0.016). The rate of sICH was comparable ( p = 0.35) between the PROTECT Plus group (7.2%) and the non-PROTECT group (3.0%). Conclusion The PROTECT Plus technique using a BGC, a distal reperfusion catheter and stent retriever is feasible for recanalization of large vessel occlusions. Successful recanalization, first-pass recanalization and complication rates are similar between PROTECT Plus and non-PROTECT stent retriever techniques. This study adds to an existing body of literature detailing techniques that use both a stent retriever and a distal reperfusion catheter to maximize recanalization for patients with large vessel occlusions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".