Selected abstracts from the 24th Annual Meeting of the Society in Europe for the Simulation Applied to Medicine
Bibliographic record
Abstract
Ethics statement: \nThe authors declare that they have followed the guidelines for scientific integrity and professional ethics. The article does not contain any studies with human or animal subjects. \n \nIntroduction & Aim: \nStroke is one of the leading causes of morbidity and mortality worldwide. In eligible patients with acute ischemic stroke, early treatment with intravenous thrombolysis is crucial for a good patient outcome. We introduced simulation training sessions in conjunction with an improved treatment protocol as part of a quality improvement project to reduce door-to-needle times in stroke thrombolysis. \n \nMethods: \nA questionnaire assessing our preexisting treatment protocol was sent to all members of the stroke team. A panel of experts reviewed the responses and suggested potential changes to streamline the treatment protocol. In February 2017, we introduced the new protocol along with weekly videotaped in-situ scenario based simulation sessions with all stroke team members as participants. Previous stroke patients acted as markers. Kirkpatrick’s four-level training evaluation model was used for assessment. Here we present 1) Participant reactions (level 1) on a Likert item from 0-10, and 2) Median door-to-needle times in stroke thrombolysis, a measure of clinical behavioral change (level 3), using a statistical process control method. Simulated performance and long term patient outcomes will be assessed in future analysis. \n \nResults & Discussion: \nParticipant reactions were predominantly positive. Self-perceived learning scored a median of 8 (IQR 7-9). We compared door-to-needle times for 478 prospectively included patients with acute ischemic stroke treated with intravenous thrombolysis at our hospital from January 2014 – July 2017. There was a significant reduction in median door-to-needle time from 27 (IQR 19-41) to 13 minutes (IQR 9-21, p<0.001) for the 78 patients in the post-intervention group. The results remained significant regardless of time of admission. There were no significant changes in the rate of stroke mimics, prehospital time or fatal intracranial hemorrhage. \n \nSimulation training in conjunction with protocol improvement led to an immediate and significant reduction of median door-to-needle time in stroke thrombolysis (Fig. 1). To our knowledge, no other published data have shown lower median treatment times. Combining simulation training with protocol change holds promise as a method both for effective implementation and significant results in attempts to reduce in-hospital delays in stroke thrombolysis. Effects on non-technical skills, provider variability and long term patient outcomes are yet to be evaluated.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.187 | 0.059 |
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".