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Record W3209260658 · doi:10.14740/jnr.v0i0.700

Cerebral Coagulation Complications Following COVID-19 Adenoviral Vector Vaccines: A Systematic Review

2021· review· en· W3209260658 on OpenAlexvenueno aff
Sara Aghabaklou, Seyed‐Mostafa Razavi, Pegah Mohammadi, Sharareh Gholamin, Ashkan Mowla

Bibliographic record

VenueJournal of Neurology Research · 2021
Typereview
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVaccinationCase fatality rateInternal medicineImmunologyIntensive care medicineEpidemiology

Abstract

fetched live from OpenAlex

Emergence of the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak identified in late 2019 in Wuhan, China, was declared a pandemic in March 2020. High fatality rate in afflicted patients prompted scientists and physicians to develop various vaccines against the virus. While administration of millions of doses of the adenoviral vector vaccines (e.g., Oxford-AstraZeneca (ChAdOx1 nCoV-19) and Janssen/Johnson & Johnson (Ad26.COV2. S)) has helped control the disease, numerous cases of cerebral venous sinus thrombosis (CVST) with thrombocytopenia have been reported in vaccinated individuals. In this article, we aim to review the cases reported thus far and further discuss the association between the vaccine administration and subsequent cerebral thromboembolic events. Our study was performed and reported based on the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). PubMed, Google Scholar and Norris Medical Library databases were searched using the following terms: coronavirus disease 2019 (COVID-19) vaccines (“AstraZeneca” or “AZD1222 COVID vaccine” or “ChAdOx1 nCoV-19 COVID-19 vaccine” or “Janssen” or “Johnson & Johnson COVID vaccine” or “Ad26.COV2 COVID vaccine”), coagulopathy (“cerebral venous sinus thrombosis (CVST)” and “vaccine-induced immune thrombotic thrombocytopenia (VITT)” or “cerebral venous thrombosis (CVT)”) and thrombocytopenia. All the relevant studies within the English literature up to August 1, 2021, were included. Fourteen most recent articles reporting on 66 patients with CVST and VITT after adenoviral vector vaccination were reviewed by two independent authors. Age of the patients ranged from 18 to 60 years. The majority of cases were women (43 females versus 14 males). Platelet count was between 5 and 127 × 10 9 /L. Above-normal D-dimer was found in 86% of the patients. A total of 68% of the patients had positive platelet factor 4 IgG assay in the absence of prior exposure to heparin. Among CVST cases following COVID vaccination, 44% succumbed to death. Early diagnosis and treatment of CVST plays a fundamental role in decreasing morbidity and mortality. Health care professional should be familiar with this rare complication post vaccination against COVID-19. Given the rarity of CVST after the COVID-19 vaccine, the benefit of vaccination outweighs the potential harm. J Neurol Res. 2021;11(5):69-76 doi: https://doi.org/10.14740/jnr700

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)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0060.006
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.343
GPT teacher head0.530
Teacher spread0.187 · 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 designSystematic review
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

Citations1
Published2021
Admission routes1
Has abstractyes

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