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Record W2185628134 · doi:10.14740/jocmr2404w

Defibrillator-Induced Tricuspid Abscess Presenting as Diabetic Ketoacidosis and Wound Ulceration

2015· article· en· W2185628134 on OpenAlexvenueno aff
Rafay Khan, Sabrina Arshed, Amar Ahmed, Shuvendu Sen, Abdalla Yousif

Bibliographic record

VenueJournal of Clinical Medicine Research · 2015
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTricuspid valveDiabetic ketoacidosisForeign bodyAbscessEndocarditisSurgeryBacteremiaAntibioticsInternal medicine

Abstract

fetched live from OpenAlex

Right-sided endocarditis is predominantly seen in patients with a history of intravenous drug abuse. However, it is well shown in the literature to be associated with patients containing foreign bodies such as pacemakers, central venous lines, and in those with congenital heart disease. In patients with pacemaker leads and in those with automatic implantable cardioverter defibrillators (AICDs), it is important to suspect foreign body infection when there are signs and indications of bacteremia. When these leads become infected, they can spread the infection to the tricuspid valve resulting in vegetations. The proper management is removal of the infected lead and foreign body along with a prolonged course of antibiotics. However, it is unusual and a relatively rare entity to see foreign body infection resulting from a wound ulcer resulting in not only endocarditis but also abscess formation on the tricuspid valve. Here we report a case of a 60-year-old male with recent AICD placement presenting as diabetic ketoacidosis due to tricuspid abscess formation as a result of a foot ulcer.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.395
GPT teacher head0.561
Teacher spread0.167 · 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
Published2015
Admission routes1
Has abstractyes

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