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Record W2811326314 · doi:10.1097/ccm.0000000000003258

Management of the Critically Ill Adult Chimeric Antigen Receptor-T Cell Therapy Patient: A Critical Care Perspective

2018· review· en· W2811326314 on OpenAlexaff
Cristina Gutiérrez, Colleen McEvoy, Elena Mead, R. Scott Stephens, Laveena Munshi, Michael E. Detsky, Stephen M. Pastores, Joseph L. Nates

Bibliographic record

VenueCritical Care Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsMount Sinai HospitalToronto General Hospital
FundersNational Cancer Institute
KeywordsMedicineCritically illPerspective (graphical)Chimeric antigen receptorIntensive care medicineCritical illnessCell therapyImmunologyImmunotherapyImmune systemCell

Abstract

fetched live from OpenAlex

OBJECTIVES: Chimeric antigen receptor T-cell therapy, a type of immune effector therapy for cancer, has demonstrated encouraging results in clinical trials for the treatment of patients with refractory hematologic malignancies. Nevertheless, there are toxicities specific to these treatments that, if not recognized and treated appropriately, can lead to multiple organ failure and death. This article is a comprehensive review of the available literature and provides, from a critical care perspective, recommendations by experienced intensivists in the care of critically ill adult chimeric antigen receptor T-cell patients. DATA SOURCES: PubMed and Medline search of articles published from 2006 to date. STUDY SELECTION: Clinical studies, reviews, or guidelines were selected and reviewed by the authors. DATA EXTRACTION: Not available. DATA SYNTHESIS: Not available. CONCLUSIONS: Until modifications in chimeric antigen receptor T-cell therapy decrease their toxicities, the intensivist will play a leading role in the management of critically ill chimeric antigen receptor T-cell patients. As this novel immunotherapeutic approach becomes widely available, all critical care clinicians need to be familiar with the recognition and management of complications associated with this treatment.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.047
GPT teacher head0.405
Teacher spread0.358 · 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.

Study designNot applicable
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

Citations68
Published2018
Admission routes1
Has abstractyes

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