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Record W3081980264 · doi:10.1093/ehjcr/ytaa167

Antemortem diagnosis of nonbacterial thrombotic endocarditis in a patient with previously resected pancreatic adenocarcinoma: a case report

2020· article· en· W3081980264 on OpenAlexaff
Hamza Zahid Ullah Muhammadzai, Jay Shavadia, Udoka Okpalauwaekwe, Haissam Haddad

Bibliographic record

VenueEuropean Heart Journal - Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsMedicineMalignancyDifferential diagnosisAdenocarcinomaEndocarditisPresentation (obstetrics)BiopsySurgeryHeart failureRadiologyInternal medicinePathologyCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Nonbacterial thrombotic endocarditis (NBTE) is a rare manifestation of a number of systemic diseases, which include advanced malignancy and hypercoagulable states. CASE SUMMARY: We present a 67-year-old woman who had presented with chest pain and heart failure. Eight years ago, she had a successful Whipple resection for pancreatic adenocarcinoma. Echocardiography revealed mitral valve vegetations with negative blood cultures. She had multiple infarcts in the kidney, spleen, and brain. She was found to have a mass in the left 8th rib, consistent with metastatic pancreatic adenocarcinoma on biopsy. Ultimately, a diagnosis of NBTE was made after excluding other causes for her presentation. Because of her general poor condition, she expressed the wish for palliative care and later died 28 days after presentation. DISCUSSION: This case illustrates the possibility of NBTE in patients successfully treated for pancreatic adenocarcinoma and highlights the consideration of this relatively rare differential in patients with a previously treated malignancy presenting with heart failure.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.280
Teacher spread0.243 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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