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Record W3162246812 · doi:10.1161/str.52.suppl_1.p141

Abstract P141: Global Impact of Covid-19 Pandemic on Acute Stroke and Mechanical Thrombectomy - An International Survey

2021· article· en· W3162246812 on OpenAlexaff
Dileep R. Yavagal, Vasu Saini, Violiza Inoa, Hannah Gardener, Sheila Cristina Ouriques Martins, Manav Fakey, Santiago Ortega‐Gutiérrez, Thomas Leung, Ashutosh P. Jadhav, Jennifer Potter‐Vig, PN Sylaja, Andrew M. Demchuk

Bibliographic record

VenueStroke · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineStroke (engine)PandemicCoronavirus disease 2019 (COVID-19)IntubationEmergency medicineAcute strokeSedationInternal medicineEmergency departmentSurgeryDiseaseNursing

Abstract

fetched live from OpenAlex

Introduction: The COVID-19 pandemic has strained the healthcare systems across the world but its impact on acute stroke care is just being elucidated. We hypothesized a major global impact of COVID-19 not only on stroke volumes but also on thrombectomy practice. Methods: A 19-item questionnaire survey aimed to identify the changes in stroke volumes and treatment practices seen during COVID-19 pandemic was designed using Qualtrics software. It was sent to stroke and neuro-interventional physicians around the world who are part of the executive committee of a global coalition, Mission Thrombectomy 2020 (MT2020) between April 5 th to May 15 th , 2020. Results: There were 113 responses across 25 countries. Globally there was a median 33% decrease in stroke admissions and a 25% decrease in mechanical thrombectomy (MT) procedures during COVID-19 pandemic compared to immediately preceding months (Figure 1A-B). This overall median decrease was despite a median increase in stroke volume in 4 European countries which diverted all stroke patients to only a few selected centers during the pandemic. The intubation policy during the pandemic for patients undergoing MT was highly variable across participating centers: 44% preferred intubating all patients, including 25% centers that changed their policy to preferred-intubation (PI) vs 27% centers that switched to preferred-conscious-sedation (PCS). There was no significant difference in rate of COVID-19 infection between PI vs PCS (p=0.6) or if intubation policy was changed in either direction (p=1). Low-volume (<10 stroke/month) compared with high-volume stroke centers (>20 strokes/month) are less likely to have neurointerventional suite specific written personal protective equipment protocols (74% vs 88%) and if present, these centers are more likely to report them to be inadequate (58% vs 92%). Conclusion: Our data provides a comprehensive snapshot of the impact on acute stroke care observed worldwide during the pandemic.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.128
GPT teacher head0.476
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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