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Record W2971455274 · doi:10.1002/rcr2.483

A rare case of acute respiratory distress syndrome caused by use of gadolinium‐based magnetic resonance imaging contrast media

2019· article· en· W2971455274 on OpenAlexaboutno aff
Yi Lee, Tzu Yi Chung, Hsu‐Chung Liu

Bibliographic record

VenueRespirology Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineARDSGadoliniumMagnetic resonance imagingGadobutrolRespiratory distressRadiologyAnaphylaxisAcute respiratory distressMethylprednisoloneIntensive care medicineAnesthesiaLungInternal medicineAllergy

Abstract

fetched live from OpenAlex

Gadolinium-based magnetic resonance imaging (MRI) contrast is generally considered to be stable and safe. Adverse reactions due to MRI contrast agents are classified into allergic-like reactions and physiological reactions. Acute respiratory distress syndrome (ARDS) caused by gadolinium-based MRI contrast is extremely rare. Due to the immediate and severe nature of ARDS, medical practitioners may seek after other aetiologies other than MRI-contrast-induced ARDS for patients' clinical manifestations such as acute-onset difficulty of breathing. It is crucial to keep in mind the possibility of ARDS after gadolinium injection, as missing the diagnosis leads to a high mortality. A clear clinical scenario of ARDS induced by gadobutrol (Gadovist, Bayer Inc., Toronto, Canada) was presented in our patient who did not develop symptoms of anaphylaxis. We successfully managed the patient with methylprednisolone and bilevel positive airway pressure ventilation and the patient was discharged in stable condition on day 6.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.265
Teacher spread0.246 · 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 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

Citations10
Published2019
Admission routes1
Has abstractyes

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