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Record W4413282660 · doi:10.3390/curroncol32080469

Pembrolizumab-Induced Simultaneous and Refractory Systemic Capillary Leak and Cytokine Release Syndromes: A Case Report

2025· article· en· W4413282660 on OpenAlexaffvenue
Eugénie Roberge-Maltais, Éric Lévesque, Vincent Castonguay, Nicolas Marcoux, Louis-Philippe Grenier, Martin Veilleux

Bibliographic record

VenueCurrent Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicMuscle and Compartmental Disorders
Canadian institutionsHôtel-Dieu de QuébecUniversité Laval
Fundersnot available
KeywordsMedicinePembrolizumabAnasarcaAdverse effectInternal medicineTocilizumabNivolumabCancerImmunotherapyDisease

Abstract

fetched live from OpenAlex

Systemic Capillary Leak Syndrome (SCLS) and Cytokine Release Syndrome (CRS) have both been described as rare but severe adverse reactions induced by Programmed cell death protein 1 (PD-1) inhibitors such as pembrolizumab. We report the case of a 40-year-old woman undergoing treatment with pembrolizumab for a stage 4 cervical squamous cell carcinoma who presented with anasarca, hypotension, hemoconcentration and signs of multisystemic inflammation. After elimination of alternative causes such as nephrotic syndrome, cardiac dysfunction and cirrhosis, she was diagnosed with both pembrolizumab-induced SCLS and CRS. She was successfully treated with a multimodal treatment approach including intravenous immunoglobulins, steroids, diuretics and axitinib for SCLS as well as ruxolitinib for CRS. After several months of hospitalization, her symptoms finally improved with this treatment regimen, and she was able to attain euvolemic state and be discharged from the hospital. This case highlights certain rare and severe adverse effects of treatment with PD-1 inhibitors. Furthermore, it proposes a novel therapeutic approach for similar cases based upon probable underlying physiopathological mechanisms in SCLS and CRS.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.061
GPT teacher head0.382
Teacher spread0.321 · 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 designCase report
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
Published2025
Admission routes2
Has abstractyes

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