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Record W3212053975 · doi:10.1097/nan.0000000000000446

Infusion Center Guidelines for Teprotumumab Infusions: Informed Consent, Safety, and Management of Side Effects

2021· article· en· W3212053975 on OpenAlexaff

Bibliographic record

VenueJournal of Infusion Nursing · 2021
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsRegistered Nurses' Association of Ontario
FundersNational Eye Institute
KeywordsFood and drug administrationDiseaseThyroidMEDLINEThyroid diseaseDrugAutoimmune diseaseDrug administration

Abstract

fetched live from OpenAlex

Teprotumumab was the first and only medication approved by the US Food and Drug Administration for the treatment of thyroid eye disease in January 2020. Thyroid eye disease is a complex autoimmune inflammatory disease that can be sight-threatening, debilitating, and disfiguring to affected patients. Although biologic therapies are a preferred treatment option for many complex immunologic and oncologic conditions, their use in ophthalmology and endocrinology may be more novel. The goals of this article are to introduce this new therapeutic option; discuss its mechanism of action, indications for use, administration protocol, infusion precautions, and informed consent; and review common side effects and management.

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)0.028
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.064
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0230.017

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 head0.053
GPT teacher head0.393
Teacher spread0.339 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations6
Published2021
Admission routes1
Has abstractyes

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