MétaCan
Menu
← Back to cohort
Record W3160271919 · doi:10.14740/jmc3702

Osimertinib-Induced Unilateral Diffuse Alveolar Hemorrhage in a Patient With Pulmonary Adenocarcinoma

2021· article· en· W3160271919 on OpenAlexvenueno aff
Shiho Saeki, Kanako Nishimatsu, Shôichi Ihara, Seigo Minami

Bibliographic record

VenueJournal of Medical Cases · 2021
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBronchoalveolar lavageDiffuse alveolar hemorrhageLungChest radiographOsimertinibGround-glass opacityDiffuse alveolar damagePathologyRadiologyAdenocarcinomaSurgeryAnesthesiaInternal medicineCancer

Abstract

fetched live from OpenAlex

A 70-year-old man with lung adenocarcinoma was admitted to our hospital due to progressive dyspnea, 4 months after osimertinib initiation. His chest radiograph and computed tomography revealed ground-glass opacities and consolidations dominantly in the upper left lung. He took neither antiplatelet nor anticoagulation agent. No abnormality in coagulation was detected. Bronchoalveolar lavage fluid (BALF) became serially and increasingly hemorrhagic, and confirmed the diagnosis of alveolar hemorrhage. After steroid pulse therapy and withdrawal of osimertinib, his condition gradually improved, accompanied by regression of ground-glass opacities and consolidations. Osimertinib causes not only interstitial pneumonia but also alveolar hemorrhage. The consolidations may spread not bilaterally, but be localized unilaterally. We have to keep this rare adverse event in mind, and consider immediate withdrawal of osimertinib and treatment with steroid. Increased lymphocytes in the BALF may be a potential indicator of sensitivity to steroid and favorable prognosis in diffuse alveolar hemorrhage.

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)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical Cases→Same topicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis→French-language works237,207→