Quantifying candidate volume for endovascular therapy for acute ischemic stroke: a retrospective chart review
Bibliographic record
Abstract
BACKGROUND: Endovascular therapy is the new standard of care for certain patients with acute ischemic stroke. We aimed to determine whether procedural volumes at an academic health sciences centre in northeastern Ontario exceeded the minimum of 20 procedures annually to support establishment of an endovascular therapy centre and thus improve regional access to this type of care. METHODS: We conducted a retrospective chart review at Health Sciences North, a regional stroke centre for northeastern Ontario that currently does not offer endovascular therapy for patients with acute ischemic stroke. Medical records and neurovascular imaging results for patients with a discharge diagnosis of cerebral infarction who were seen by the stroke on-call team at Health Sciences North between May 1, 2016, and Apr. 30, 2017, were retrospectively examined in accordance with criteria of the ESCAPE trial to identify potential candidates for endovascular therapy. The number of candidates was extrapolated to include patients discharged with cerebral infarction from referral centres within a 2-hour transport radius from the study institution. RESULTS: Of 71 patients who met the inclusion criteria, 9 were identified as candidates. Of the 71 cases reviewed, 62 (87%) presented within the window for administration of recombinant tissue plasminogen activator of 4.5 hours from symptom onset, 66 (93%) within the endovascular therapy window of 6 hours and 69 (97%) within the extended endovascular therapy window of 12 hours. Expanding these estimates to include regional referral centres, we conservatively estimated that Health Sciences North has the potential to perform 22 or 23 procedures annually. INTERPRETATION: The projected annual number of procedures met the minimum requirement to maintain competency. Establishing Health Sciences North as a centre for endovascular therapy could be an important step in improving equity in stroke outcomes across northeastern Ontario.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".