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Complicaciones neurológicas post-vacuna COVID.

2023· article· es· W4388398811 on OpenAlexaff
Emilio Martínez-Maruri, Germán Mauricio Azcárraga-Hurtado

Bibliographic record

VenueRevista Ecuatoriana de Neurologia · 2023
Typearticle
Languagees
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsGlenrose Rehabilitation Hospital
Fundersnot available
KeywordsMedicineHumanitiesCoronavirus disease 2019 (COVID-19)PhilosophyInternal medicine

Abstract

fetched live from OpenAlex

Las complicaciones neurológicas post-vacuna SARS-CoV-2 son infrecuentes. No obstante, debido a la pandemia del SARS-CoV-2, se ha realizado una vacunación masiva mundial, por lo que hemos visto un mayor reporte de efectos adversos neurológicas post vacunales. Presentamos 4 casos, que tras recibir la vacuna SARS-CoV-2 presentaron 4 patologías neurológicas distintas en el Hospital Comarcal de Vinaroz durante el año 2021. Se observa una relación entre la vacunación y el inicio de los síntomas neurológicos. Tres pacientes presentaron manifestaciones clínicas en relación con la vacuna BNT162b2. La primera paciente tras la administración de la primera dosis de la vacuna BNT162b2 presento diplopía y ptosis palpebral, cuadro compatible con Miastenia gravis ocular. El segundo paciente tuvo un cuadro de polineuropatía motora axonal sensitiva aguda tras la tercera dosis. La tercera paciente, que tras la tercera dosis de BNT162b2 presentó encefalopatía letárgica. La cuarta paciente presenta un cuadro compatible meningitis aséptica después de la vacunación AZD1222 y mRNA-1273 Debido a la campaña de vacunación masiva a nivel mundial están surgiendo informes de complicaciones neurológicas relacionadas accidentalmente o vinculadas causalmente. Estas son muy variadas, podrían estar en relación con mecanismos inmunológicos y/o tóxicos. Los médicos debemos estar atentos a estos posibles efectos adversos y descartar otras causas. Se deben realizar estudios que nos permitan poder esclarecer los mecanismos patológicos en relación con las complicaciones post vacunales.

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 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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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