Changes in ischemic stroke presentations and associated workflow during the first wave of the COVID-19 pandemic: A population study in Alberta, Canada
Bibliographic record
Abstract
ABSTRACT Background Pandemics may promote hospital avoidance among patients with emergencies, and added precautions may exacerbate treatment delays. There is a paucity of population-based data on these phenomena for stroke. We examined the effect of the COVID-19 pandemic on the presentation and treatment of ischemic stroke in an entire population. Methods We used linked provincial administrative data and data from the Quality Improvement and Clinical Research Alberta Stroke Program – a registry capturing stroke-related data on the entire population of Alberta(4.3 million)– to identify all patients presenting with stroke in the pre-pandemic(1-January-2016 to 27-February-2020, n=19,531) and pandemic(28-February-2020 to 30-August-2020, n=2,255) periods. We examined changes in thrombolysis and endovascular therapy(EVT) rates, workflow, and in-hospital outcomes. Results Hospitalizations/presentations for ischemic stroke dropped (weekly adjusted-incidence-rate-ratio[aIRR]:0.48, 95%CI:0.46-0.50, adjusted for age, sex, comorbidities, pre-admission care needs), as did population-level incidence of thrombolysis(aIRR:0.49,0.44-0.56) or EVT(aIRR:0.59,0.49-0.69). However, the proportions of presenting patients receiving acute therapies did not decline (e.g. thrombolysis:11.7% pre-pandemic vs 13.1% during-pandemic, aOR:1.02,0.75-1.38). Onset-to-door times were prolonged; EVT recipients experienced longer door-to-reperfusion times (median door-to-reperfusion:110-minutes, IQR:77-156 pre-pandemic vs 132.5-minutes, 99-179 during-pandemic; adjusted-coefficient:18.7-minutes, 95%CI:1.45-36.0). Hospitalizations were shorter but stroke severity and in-hospital mortality did not differ. Interpretation The first COVID-19 wave was associated with a halving of presentations and acute therapy utilization for ischemic stroke at a population level, and greater pre-hospital and in-hospital treatment delays. Our data can inform public health messaging and stroke care in current and future waves. Messaging should encourage attendance for emergencies and stroke systems should re-examine “code stroke” protocols to mitigate inefficiencies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".