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Record W3100237528 · doi:10.1002/ana.25967

The Impact of <scp>SARS‐CoV</scp>‐2 on Stroke Epidemiology and Care: A Meta‐Analysis

2020· review· en· W3100237528 on OpenAlex
Aristeidis H. Katsanos, Lina Palaiodimou, Ramin Zand, Shadi Yaghi, Hooman Kamel, Babak B. Navi, Guillaume Turc, Michele Romoli, Vijay K. Sharma, Dimitris Mavridis, Shima Shahjouei, Luciana Catanese, Ashkan Shoamanesh, Κonstantinos Vadikolias, Konstantinos Tsioufis, Παγώνα Λάγιου, Andrei V. Alexandrov, Sotirios Tsiodras, Georgios Tsivgoulis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of Neurology · 2020
Typereview
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineOdds ratioStroke (engine)Internal medicineMeta-analysisConfidence intervalCohort studyEpidemiologyCohortThrombolysisDiabetes mellitusMyocardial infarction

Abstract

fetched live from OpenAlex

Objective Emerging data indicate an increased risk of cerebrovascular events with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and highlight the potential impact of coronavirus disease (COVID‐19) on the management and outcomes of acute stroke. We conducted a systematic review and meta‐analysis to evaluate the aforementioned considerations. Methods We performed a meta‐analysis of observational cohort studies reporting on the occurrence and/or outcomes of patients with cerebrovascular events in association with their SARS‐CoV‐2 infection status. We used a random‐effects model. Summary estimates were reported as odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Results We identified 18 cohort studies including 67,845 patients. Among patients with SARS‐CoV‐2, 1.3% (95% CI = 0.9–1.6%, I 2 = 87%) were hospitalized for cerebrovascular events, 1.1% (95% CI = 0.8–1.3%, I 2 = 85%) for ischemic stroke, and 0.2% (95% CI = 0.1–0.3%, I 2 = 64%) for hemorrhagic stroke. Compared to noninfected contemporary or historical controls, patients with SARS‐CoV‐2 infection had increased odds of ischemic stroke (OR = 3.58, 95% CI = 1.43–8.92, I 2 = 43%) and cryptogenic stroke (OR = 3.98, 95% CI = 1.62–9.77, I 2 = 0%). Diabetes mellitus was found to be more prevalent among SARS‐CoV‐2 stroke patients compared to noninfected historical controls (OR = 1.39, 95% CI = 1.00–1.94, I 2 = 0%). SARS‐CoV‐2 infection status was not associated with the likelihood of receiving intravenous thrombolysis (OR = 1.42, 95% CI = 0.65–3.10, I 2 = 0%) or endovascular thrombectomy (OR = 0.78, 95% CI = 0.35–1.74, I 2 = 0%) among hospitalized ischemic stroke patients during the COVID‐19 pandemic. Odds of in‐hospital mortality were higher among SARS‐CoV‐2 stroke patients compared to noninfected contemporary or historical stroke patients (OR = 5.60, 95% CI = 3.19–9.80, I 2 = 45%). Interpretation SARS‐CoV‐2 appears to be associated with an increased risk of ischemic stroke, and potentially cryptogenic stroke in particular. It may also be related to an increased mortality risk. ANN NEUROL 2021;89:380–388

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.724
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.006
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.201
GPT teacher head0.469
Teacher spread0.268 · 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