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Record W3207178171 · doi:10.14745/ccdr.v47i78a04

Ivermectin treatment for Strongyloides infection in patients with COVID-19

2021· article· en· W3207178171 on OpenAlexaffvenueabout

Bibliographic record

VenueCanada Communicable Disease Report · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsNorth York General HospitalUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsIvermectinMedicineStrongyloides stercoralisStrongyloidiasisStrongyloidesIntensive care medicineAntiparasitic agentDiseaseImmunologyParasitic diseaseInternal medicinePharmacology

Abstract

fetched live from OpenAlex

Ivermectin, an antiparasitic agent, is not recommended for prophylaxis or treatment of coronavirus disease 2019 (COVID-19). Inappropriate use of ivermectin for treatment of COVID-19 may make it less available for patients with serious parasitic infections who could benefit from its use and worsen the current shortage of ivermectin in Canada. However, patients with COVID-19 who are candidates to receive immunomodulatory therapies (e.g. corticosteroids and interleukin-6 inhibitors) may be at risk of hyperinfection syndrome and disseminated disease from Strongyloides stercoralis. These complications can be severe and even fatal. It is important to recognize and screen patients who may be at risk of strongyloidiasis, as these patients may require treatment with ivermectin to avoid the potential for a hyperinfection syndrome and disseminated disease, which is frequently deadly. Clinicians should follow evidence-based recommendations to screen and treat for Strongyloides infection in patients with COVID-19 who are under consideration to receive specific COVID-19 therapies that alter immune response and may lead to hyperinfection syndrome or disseminated disease.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.295
Teacher spread0.274 · 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.

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

Citations5
Published2021
Admission routes3
Has abstractyes

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