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Record W4309998959 · doi:10.14740/jmc4008

Pembrolizumab-Induced Myasthenia Gravis and Myositis: Literature Review on Neurological Toxicities of Programmed Death Protein 1 Inhibitors

2022· article· en· W4309998959 on OpenAlexvenueno aff
A Schwab, Marc Assaad, Rachelle Hamadi, Juda Zurndorfer, Racha Abi Melhem, Jennifer Holtzbach, Jeffrey Loeffler, Muhammad Ibrahim

Bibliographic record

VenueJournal of Medical Cases · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMyasthenia gravisPembrolizumabMyositisRituximabPlasmapheresisAdverse effectWeaknessImmunotherapyInternal medicineSurgeryCancerAntibodyImmunologyLymphoma

Abstract

fetched live from OpenAlex

We present herein the case of an elderly male patient, who was receiving immunotherapy for his urothelial cancer and who presented to our facility with lower extremity weakness. The patient was diagnosed with myasthenia gravis, thyroiditis, myositis and myocarditis, which were considered as immune adverse events of pembrolizumab therapy. The patient received pyridostigmine, intravenous immunoglobulin, plasmapheresis, corticosteroids, and rituximab with mild improvement of his symptoms. The patient had some neurological recovery, was discharged to a nursing facility, however he was ventilator dependent. Of importance, our case is followed by review and discussion of the literature related to immunotherapy and its side effects.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.305
Teacher spread0.278 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations14
Published2022
Admission routes1
Has abstractyes

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