Abstract Number ‐ 109: Mechanical Thrombectomy Hands‐on Skill Workshop for MT2020+ in the Caribbean
Bibliographic record
Abstract
Introduction While mechanical thrombectomy (MT) is proven to be lifesaving and disability‐sparing, there remains disparities in access in low‐ to middle‐income countries (LTMICs), including the Caribbean. We hypothesized that team‐oriented MT workshops would improve MT skills and change practice patterns for MT services in this region. Methods We designed a 22‐hour MT workshop which was conducted as two identical events: in English (Jamaica, January 2022), and in Spanish (Dominican Republic, May 2022). The workshops included neurointerventional teams (practicing neurointerventionalists, neuroIR nurses and technicians), focused on patient selection, acutetreatment and post‐MT care of patients with stroke due to large vessel occlusion. MT skills, procedure duration and potential harmful techniques were recorded before and after by independent evaluators utilizing flow models under fluoroscopy. Overall course evaluation was performed. Press conferences were included to raise stroke awareness and emphasize the importance of early stroke presentation. Results Twenty‐two physicians and their teams from eight countries across the Caribbean completed the didactic and hands‐on training. Eighteen groups completed both pre‐ and post‐MT hands‐on testing and were included in the final analysis. Pre‐ and post‐course hands‐on assessment showed that the course effectively reduced the total time to complete a simulated MT procedure from 36.5 to 21.1 min (Figure 1; p< 1.0×10‐7). All groups showed an improvement in measures of good MT techniques, which resulted in a 39% improvement in complete reperfusion (8/18 groups achieved a TICI 3 score on pre‐course vs. 15/18 groups on post‐course). There was a significant reduction in total potentially dangerous maneuvers by 82% (p< 0.002), with 12/18 groups performing an average 2 dangerous maneuvers on pre‐course simulation vs. only 4/18 groups performing an average 1 dangerous maneuver after completing the course. Participants also demonstrated increased knowledge of stroke treatment and stroke system of care. Utilizing a basic stroke knowledge questionnaire, we found 28% respondents did not have a baseline passing grade vs 100% passed after the workshop. The average post‐workshop knowledge score was 80%. Universally the workshop was rated as very satisfactory and likely to change practice in 93% of the Dominican Republic participants and 75% among Jamaican participants. Conclusions A team‐based approach to MT training is novel, effective in reducing time to reperfusion and harmful techniques, and improves competencies. Team members independently demonstrated advanced stroke learning post‐training. To our knowledge, this is the first workshop of its kind; it is feasible, practice‐changing and creates a pathway for increasing access to MT in LTMICs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".