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Record W3091927665 · doi:10.1016/j.cjco.2020.10.003

Rapid Response to Cytokine Storm Inhibition Using Anakinra in a Patient With COVID-19 Myocarditis

2020· article· en· W3091927665 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCJC Open · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersSiemens Healthineers
KeywordsAnakinraMedicineMyocarditisCytokine stormCardiogenic shockCardiologyInternal medicineHeart failureFulminantMyocardial infarctionInflammationCardiac magnetic resonance imagingEndothelin receptor antagonistImmunologyMagnetic resonance imagingGastroenterologyDiseaseAntagonistCoronavirus disease 2019 (COVID-19)ReceptorRadiologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

A 62-year-old woman with coronavirus disease 2019 developed acute respiratory failure and cardiogenic shock in the setting of a systemic hyperinflammatory state and apparent ST-elevation myocardial infarction. Cardiac magnetic resonance imaging showed fulminant acute myocarditis with severe left ventricular dysfunction. Treatment with the recombinant interleukin-1 receptor antagonist anakinra and dexamethasone resulted in rapid clinical improvement, reduction in serum inflammatory markers, and a marked recovery in cardiac magnetic resonance--based markers of inflammation and contractile dysfunction. The patient was subsequently discharged from the hospital. Emerging evidence supports use of anti-inflammatory therapies, including anakinra and dexamethasone, in severe cases of coronavirus disease 2019.

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.

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)0.037
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.115
GPT teacher head0.439
Teacher spread0.324 · 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