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Record W4324332985 · doi:10.34119/bjhrv6n2-010

Impacto del Tocilizumab sobre la Depresión en pacientes con Artritis Reumatoide

2023· article· es· W4324332985 on OpenAlexaff
Paula Michelle Orellana Romero, Miguel Esteban Carrillo Uguña, Diego Fernando Chalco

Bibliographic record

VenueBrazilian Journal of Health Review · 2023
Typearticle
Languagees
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsImpact
Fundersnot available
KeywordsMedicineHumanitiesTocilizumabRheumatoid arthritisPhilosophyInternal medicine

Abstract

fetched live from OpenAlex

La depresión es un trastorno del estado de ánimo que muy frecuentemente se produce debido a patologías que interfieren en la vida diaria del paciente. El objetivo del presente trabajo es revisar bibliografía sobre el impacto del tratamiento con tocilizumab, un antagonista de la Interleucina-6, sobre la depresión en pacientes con Artritis Reumatoide. Se encontró que todos los pacientes que presentan esta enfermedad autoinmune en cualquier momento desarrollarán depresión. En cuanto a la asociación de la Artritis reumatoide con la depresión, se han establecido procesos biológicos que aún no se encuentran completamente esclarecidos. Sin embargo, el avance de la ciencia ha podido identificar que los efectos sobre la estructura y función cerebral que producen las alteraciones inmunitarias están presentes en ambas afecciones, en donde estos cambios se correlacionan con síntomas neuropsiquiátricos. Este estudio ha demostrado que la terapia con Tocilizumab tiene un efecto favorable en los criterios que evidencian la gravedad de la depresión en pacientes con Artritis Reumatoide.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.384
Teacher spread0.346 · 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 designObservational
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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Same venueBrazilian Journal of Health ReviewSame topicFibromyalgia and Chronic Fatigue Syndrome ResearchFrench-language works237,207