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Record W4220783531 · doi:10.36922/an.v1i1.28

Clinical characteristics and outcomes of acute ischemic stroke in patients with COVID-19: A systematic review and meta-analysis of global data

2022· review· en· W4220783531 on OpenAlexaboutno aff
Zhelv Yao, Lili Huang, Yue Cheng, Ruowen Qi, Biyun Xu, Qingxiu Zhang, Liqun Zhang

Bibliographic record

VenueAdvanced Neurology · 2022
Typereview
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConfidence intervalMeta-analysisOdds ratioStroke (engine)Internal medicineCoronavirus disease 2019 (COVID-19)Publication biasDisease

Abstract

fetched live from OpenAlex

Objective. There is increased concern regarding acute ischemic stroke (AIS) in patients with coronavirus disease 2019 (COVID-19). The aim of this study was to depict the manifestations and outcomes of COVID-19-associated AIS. Methods. We systematically searched for eligible studies describing AIS in patients with COVID-19 using PubMed, Embase, and Web of Science up to November 29, 2021. We complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and used the Newcastle–Ottawa Scale to assess data quality. The data were pooled using fixed- and random-effects models. Results. Thirty-eight eligible studies involving 76,894 participants were included in this meta-analysis. Compared with AIS patients who did not have COVID-19, patients with COVID-19 were more likely to have anterior circulation stroke (odds ratio [OR]: 2.29, 95% confidence interval [CI]: 1.03 – 5.10; I2: 37%), particularly involving the internal carotid artery (OR: 1.85, 95% CI: 1.19 – 2.88; I2: 0); more severe neurological deficit (National Institutes of Health Stroke Scale [NIHSS]) (weighted mean difference [WMD]: 3.21, 95% CI: 2.13 – 4.29; I2: 64%); higher proportion of cryptogenic stroke (OR: 1.83, 95% CI: 1.24 – 2.70; I2: 62%), large vessel occlusion (OR: 1.68, 95% CI: 1.10 – 2.57; I2: 75%), and multi-territory involvement (OR: 2.64, 95% CI: 1.62 – 4.29; I2: 0%); higher C-reactive protein levels (WMD: 55.90, 95% CI: 33.32 – 78.49; I2: 67%), and D-dimer levels (standardized mean difference: 0.81, 95% CI: 0.52 – 1.10; I2: 59%). The proportion of poor outcomes were higher among patients with COVID-19, including increased risk of in-hospital death (OR: 3.70, 95% CI: 2.73 – 5.02; I2: 64%) and lower possibility of favorable discharge (OR: 0.49, 95% CI: 0.39 – 0.61; I2: 0). However, COVID-19 did not increase the risk of hemorrhagic transformation (OR: 1.34, 95% CI: 0.91 – 1.98; I2: 39%) and symptomatic intracerebral hemorrhage (OR: 1.46, 95% CI: 0.81 – 2.62; I2: 0). Conclusion. AIS patients with COVID-19 seem to display a pattern of large vessel occlusion and multi-territory infarcts. These patients have high inflammatory marker levels and increased D-dimer levels, which implies that thrombosis and/or thromboembolism might be the underlying mechanism. These patients tend to have worse prognosis regardless of whether they receive reperfusion treatment.

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)0.016
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.038
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.045
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.083
GPT teacher head0.437
Teacher spread0.354 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations3
Published2022
Admission routes1
Has abstractyes

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