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Record W4367296710 · doi:10.1212/wnl.0000000000204056

Stroke Hospitalization Administration & Monitoring: Routine Or Covid-19 Care (SHAMROCC) (P7-5.006)

2023· article· en· W4367296710 on OpenAlexaffabout
Timothé Langlois‐Thérien, Michel Shamy, Brian Dewar, Ronda Lun, Dar Dowlatshahi, Dylan Blacquière, Grant Stotts, Robert Fahed, Célina Ducroux

Bibliographic record

VenueNeurology · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineThrombolysisStroke (engine)Intensive care unitEmergency medicineComplicationIncidence (geometry)DemographicsMyocardial infarctionCoronavirus disease 2019 (COVID-19)Cerebral infarctionInternal medicineIschemiaDisease

Abstract

fetched live from OpenAlex

Objective: We aim to compare the incidence and timing of complications in stroke patients over the first 24 hours post-reperfusion therapies and their association to hospital unit in 2019, 2020 and 2021. Background: Monitoring stroke patients in critical-care units for 24 hours after thrombolysis or thrombectomy is considered standard of care but is not evidence-based. Due to the Covid-19 pandemic, our center modified its protocol in April 2021 with 24-hour critical-care monitoring no longer being guaranteed for stroke patients. Design/Methods: We retrospectively collected data from stroke patients treated with thrombolysis or thrombectomy at our center in 2019 (pre-Covid-19, standard of care), 2020 (during Covid-19, standard of care) and 2021 (during Covid-19, new protocol). Data extracted included demographics, the nature and timing of complications within the first 24 hours, and the unit at the time of complication. Major complications included symptomatic intracranial hemorrhage (sICH), recurrent stroke, myocardial infarction, systemic bleeding, RACE call, and death. Results: Three hundred forty-nine patients were included in our study: 156 patients in 2021, 115 patients in 2020, and 78 patients in 2019. In 2021, 54 (34.6%) patients had, at least, one complication within the first 24 hours compared to 39 (33.9%) in 2020 and 24 (30.8%) in 2019. Forty-eight (88.9%) of the complications in 2021 occurred in a critical-care unit compared to 37 (94.9%) in 2020 and 17 (70.8%) in 2019. Overall, 61.5% of complications and 50.0% of sICH occurred within 12h. In 2021, 74.1% of all complications and 100% of sICH occurred within 12h. Conclusions: Despite the change of protocol in April 2021, the incidence and timing of complications did not significantly change compared to prior years and was not associated to hospital units. Most complications occurred in the first 12 hours. Further research is required to evaluate the necessity of intensive care monitoring for 24 hours in this population. Disclosure: Mr. Langlois-Thérien has nothing to disclose. Dr. Shamy has nothing to disclose. Brian Dewar has nothing to disclose. Dr. Lun has nothing to disclose. Dr. Dowlatshahi has nothing to disclose. Dr. Blacquiere has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Roche. Dr. Blacquiere has a non-compensated relationship as a Board of Directors with Canadian Stroke Consortium that is relevant to AAN interests or activities. Dr. Blacquiere has a non-compensated relationship as a Advisory Board Member with Heart and Stroke Foundationof Canada Stroke Best Practice Recommendations that is relevant to AAN interests or activities. Dr. Stotts has nothing to disclose. Dr. Fahed has received personal compensation in the range of $50,000-$99,999 for serving as a Consultant for Stryker Neurovascular. Dr. Fahed has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Yocan Medical Systems. Dr. Ducroux has nothing to disclose.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0310.007

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 head0.043
GPT teacher head0.339
Teacher spread0.296 · 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
Published2023
Admission routes2
Has abstractyes

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