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Record W3120542241 · doi:10.1111/ene.14727

Cerebral venous thrombosis and severe acute respiratory syndrome coronavirus‐2 infection: A systematic review and meta‐analysis

2021· review· en· W3120542241 on OpenAlexaboutno aff
Tommaso Baldini, Gian Maria Asioli, Michele Romoli, Mariana Carvalho Dias, Eva C. Schulte, Larissa Hauer, Diana Aguiar de Sousa, Johann Sellner, Andrea Zini

Bibliographic record

VenueEuropean Journal of Neurology · 2021
Typereview
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVenous thrombosisMeta-analysisConfidence intervalContext (archaeology)Internal medicineThrombosisIntracranial ThrombosisCohort studyPediatrics

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection predisposes patients to arterial and venous thrombosis. This study aimed to systematically review the available evidence in the literature for cerebral venous thrombosis (CVT) in association with coronavirus disease-2019 (COVID-19). METHODS: We searched MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases to identify cases of COVID-19-associated CVT. The search period spanned 1 January 2020 to 1 December 2020, and the review protocol (PROSPERO-CRD42020214327) followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Identified studies were evaluated for bias using the Newcastle-Ottawa scale. A proportion meta-analysis was performed to estimate the frequency of CVT among hospitalized COVID-19 patients. RESULTS: We identified 57 cases from 28 reports. Study quality was mostly classified as low. CVT symptoms developed after respiratory disease in 90%, and the mean interval was 13 days. CVT involved multiple sites in 67% of individuals, the deep venous system was affected in 37%, and parenchymal hemorrhage was found in 42%. Predisposing factors for CVT beyond SARS-CoV-2 infection were present in 31%. In-hospital mortality was 40%. Using data from 34,331 patients, the estimated frequency of CVT among patients hospitalized for SARS-CoV-2 infection was 0.08% (95% confidence interval [CI]: 0.01-0.5). In an inpatient setting, CVT accounted for 4.2% of cerebrovascular disorders in individuals with COVID-19 (cohort of 406 patients, 95% CI: 1.47-11.39). CONCLUSIONS: Cerebral venous thrombosis in the context of SARS-CoV-2 infection is a rare, although there seems to be an increased relative risk. High suspicion is necessary, because the diagnosis of this potentially life-threatening condition in COVID-19 patients can be challenging. Evidence is still scarce on the pathophysiology and potential prevention of COVID-19-associated CVT.

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)0.009
metaresearch head score (Gemma)0.026
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.028
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.124
GPT teacher head0.362
Teacher spread0.239 · 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

Citations170
Published2021
Admission routes1
Has abstractyes

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