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Record W2468851147 · doi:10.1089/crsi.2016.0012

Bioprosthetic Valve <i>Streptococcus bovis</i> Endocarditis Secondary to Colon Cancer Presenting with a Lacunar Stroke

2016· article· en· W2468851147 on OpenAlexaff
Benjamin Chin‐Yee, Kalpa Shah, Ori D. Rotstein, Amro Nagy, Cameron Williams, Howard Leong‐Poi, Jonathan Lu, Fahad Razak

Bibliographic record

VenueSurgical Infections Case Reports · 2016
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsSt. Michael's HospitalToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsStreptococcus bovisMedicineEndocarditisOccultBacteremiaColonoscopyColorectal cancerComplicationStroke (engine)Internal medicineCancerAntibioticsSurgeryGastroenterologyPathology

Abstract

fetched live from OpenAlex

Background:Streptococcus bovis endocarditis is an uncommon but reported complication of colon cancer. Studies show that approximately 50% of patients with S. bovis infection have underlying colonic neoplasm. Case Presentation: An 82-year-old woman presented to the hospital with a lacunar stroke resulting from S. bovis endocarditis of her bioprosthetic aortic valve, ultimately leading to the diagnosis of colonic malignant disease. The patient's neurologic deficits resolved and she completed a course of intravenous antibiotics followed by a successful right hemicolectomy to remove the colonic neoplasm. We review recent literature on the association between S. bovis endocarditis and colon cancer and discuss the implications for the clinical management of this condition. Conclusion: Because of the high rate of association between S. bovis infection and colonic neoplasms, the presence of S. bovis bacteremia should prompt a work-up for occult malignant disease by colonoscopy.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.012
GPT teacher head0.288
Teacher spread0.276 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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