Abstract WP20: Pre-Notification of Large Vessel Occlusion Reduces Transfer Time for Endovascular Procedures
Bibliographic record
Abstract
Introduction: The American Heart and American Stroke Associations’ revised guidelines for acute ischemic stroke recommend rapid transfer of patients with large vessel occlusions (LVO) eligible to receive mechanical endovascular procedures (MEP) if initial receiving facility does not offer MEP. Initiating the transfer process to MEP capable facilities is often delayed until LVO is confirmed on imaging. Hypothesis: We hypothesized that initiating a pre-notification process (PNP) by which emergency medical system (EMS) is notified of patients arriving to the emergency department (ED) with symptoms of LVO would reduce transfer turn-around-times (TATs). Methods: A pre- and post-interventional study involving 735 patients presenting to 2 EDs in a 5 campus hospital system from January 2014-June 2015. Both EDs began a PNP to alert EMS of potential MEP candidates. EMS then dispatched a critical care transport (CCT) ambulance with a CCT nurse to the ED to await transfer decision. Transfer TATs pre- and post-process change were reviewed. Inclusion criteria: patients with stroke code (SC) initiations in the ED who were transferred for possible MEP, or had PNP to EMS initiated. Exclusion criteria: patients with SC initiations that were not transferred or did not have PNP initiated. Results: Sixty patients met inclusion criteria; 52 were transferred pre-process change, and 8 were transferred post-process change with PNP initiated. Median time from decision to EMS arrival in the ED decreased from 22.5 minutes to -1 minute, with ambulance arriving to ED prior to decision. Median time of decision to EMS departure from ED decreased from 56 to 39 minutes, and overall median transfer TATs to MEP capable facility decreased from 78 to 69.5 minutes. Of the 8 patients with PNP to EMS, 6 (75%) were transferred to MEP capable facility. Conclusions: Pre-notification from ED to EMS of patients arriving with symptoms of LVO can reduce transfer times to an MEP capable facility. This study highlights the importance of early EMS involvement upon initial recognition of potential LVO patients, and implementation of rapid transfer protocols. Additional opportunities may exist to streamline care within the ED to further reduce transfer TATs.
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.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".