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Record W4324120883 · doi:10.1177/11795476231160045

Mitral Valve Endocarditis in Patient Awaiting TAVI: A Case Report

2023· article· en· W4324120883 on OpenAlexaff
Faith Michael, Jamie Farrow, Anthony Main

Bibliographic record

VenueClinical Medicine Insights Case Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsHealth Sciences NorthNOSM University
Fundersnot available
KeywordsMedicineCardiologyEndocarditisHeart failureInternal medicineMitral regurgitationInfective endocarditisStenosisPerforationvalvular heart diseasePopulationSurgery

Abstract

fetched live from OpenAlex

Background: for TAVI is not well-studied. We present a unique case of a patient waiting for TAVI with decompensated heart failure who was found to have a large mitral vegetation, and consider risk factors for the development of IE in this population. Case description: We report the case of an 85-year-old male with severe aortic stenosis and recurrent small bowel angiodysplasias, requiring frequent blood transfusions and intravenous iron. He presented to a peripheral hospital in decompensated heart failure. Transfer was arranged to our center to expedite TAVI, under the premise that worsening aortic stenosis precipitated his decompensated state. Prior to TAVI, an echocardiogram was done, and demonstrated a 30 × 18 mm mass on the mitral valve with anterior leaflet perforation and severe mitral regurgitation. The findings were consistent with IE, and the TAVI was cancelled. Despite antibiotic therapy, the patient unfortunately deteriorated and palliative care was provided. Conclusions: This case highlights the need for further research regarding the risk of IE in patients waiting for TAVI. Current literature focuses on the development and management of IE following TAVI. Clinicians must understand that TAVI candidates have multiple risk factors for IE, including valvular disease, age, and comorbidities. IE should be considered as a possible cause for decompensated heart failure in patients awaiting TAVI.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.426
Teacher spread0.368 · 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 teacher head, not a consensus.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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