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Record W2509782039 · doi:10.14740/cr490w

Prediction of Symptomatic Embolism in Filipinos With Infective Endocarditis Using the Embolic Risk French Calculator

2016· article· en· W2509782039 on OpenAlexvenueno aff
Jaime Alfonso M. Aherrera, Maria Teresa B. Abola, Maria Margarita Balabagno, Lauro L. Abrahan, Jose Donato A. Magno, Paul Ferdinand M. Reganit, Felix Eduardo R. Punzalan

Bibliographic record

VenueCardiology Research · 2016
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmbolismCardiologyInternal medicineInfective endocarditisEjection fractionAtrial fibrillationEndocarditisPulmonary embolismRelative riskFramingham Risk ScoreHeart failureConfidence intervalDisease

Abstract

fetched live from OpenAlex

Background: Cardioembolic events are life-threatening complications of infective endocarditis (IE). The embolic risk French calculator estimates the embolic risk in IE computed on admission. Variables in this tool include age, diabetes, atrial fibrillation, prior embolism, vegetation length, and Staphylococcus aureus on culture. A computed risk of > 7% was considered high in the development of this tool. Knowledge of this risk applied in our local setting is important to guide clinicians in preventing such catastrophic complications. Among patients with IE, we aim to determine the efficacy of the embolic risk French calculator, using a computed score of > 7%, in predicting major embolic events. Methods: All adults admitted from 2013 to 2016 with definite IE were included. The risk for embolic events was computed on admission. All were monitored for the duration of admission for the occurrence of the primary outcome (any major embolic event: arterial emboli, intracranial hemorrhage, pulmonary infarcts, or aneurysms). Secondary outcomes were: 1) composite of death and embolic events; and 2) death from any cause. Results: Eighty-seven adults with definite IE were included. Majority had a valvular heart disease and preserved ejection fraction (EF). The mitral valve was most commonly involved. Embolic events occurred in 25 (29%). Multivariate analysis identified a high embolic score > 7% (relative risk (RR): 15.12, P < 0.001), vegetation area >=18 mm 2 (RR: 6.39, P < 0.01), and a prior embolism (RR: 5.18, P = 0.018) to be independent predictors of embolic events. For the composite of embolic events and death, independent predictors include a high score of > 7% (RR: 13.56, P < 0.001) and a prior embolus (RR: 13.75, P = 0.002). Independent predictors of death were a high score > 7% (RR: 6.20, P = 0.003) and EF <=45% (RR: 9.91, P = 0.004). Conclusion: Cardioembolic events are more prevalent in our study compared to previous data. The embolic risk French calculator is a useful tool to estimate and predict risk for embolic events and in-hospital mortality. The risk of developing embolic events should be weighed against the risks of early preventive cardiac surgery, as to institute timely and appropriate management. Cardiol Res. 2016;7(4):130-139 doi: http://dx.doi.org/10.14740/cr490w Â

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.348
Teacher spread0.278 · 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 designObservational
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

Citations11
Published2016
Admission routes1
Has abstractyes

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