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Record W2522029938 · doi:10.4330/wjc.v8.i9.534

Role of radionuclide imaging for diagnosis of device and prosthetic valve infections

2016· review· en· W2522029938 on OpenAlexaff
J. Sarrazin, François Philippon, Mikaël Trottier, Michel Tessier

Bibliographic record

VenueWorld Journal of Cardiology · 2016
Typereview
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsUniversité LavalInstitut Universitaire de Cardiologie et de Pneumologie de Québec
Fundersnot available
KeywordsMedicineContext (archaeology)Positron emission tomographyEndocarditisNuclear imagingSingle-photon emission computed tomographyInfective endocarditisEmission computed tomographyRadiologyCardiac imagingFluorodeoxyglucoseNuclear medicineCardiology

Abstract

fetched live from OpenAlex

Cardiovascular implantable electronic device (CIED) infection and prosthetic valve endocarditis (PVE) remain a diagnostic challenge. Cardiac imaging plays an important role in the diagnosis and management of patients with CIED infection or PVE. Over the past few years, cardiac radionuclide imaging has gained a key role in the diagnosis of these patients, and in assessing the need for surgery, mainly in the most difficult cases. Both 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) and radiolabelled white blood cell single-photon emission computed tomography/computed tomography (WBC SPECT/CT) have been studied in these situations. In their 2015 guidelines for the management of infective endocarditis, the European Society of Cardiology incorporated cardiac nuclear imaging as part of their diagnostic algorithm for PVE, but not CIED infection since the data were judged insufficient at the moment. This article reviews the actual knowledge and recent studies on the use of 18 F-FDG PET/CT and WBC SPECT/CT in the context of CIED infection and PVE, and describes the technical aspects of cardiac radionuclide imaging. It also discusses their accepted and potential indications for the diagnosis and management of CIED infection and PVE, the limitations of these tests, and potential areas of future research.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.338
Teacher spread0.315 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2016
Admission routes1
Has abstractyes

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