Prevalence of Right- and Left-Sided Endocarditis Among Intravenous Drug Use Patients at a Large Academic Medical Center
Bibliographic record
Abstract
Background: Left-sided infective endocarditis (IE) is increasingly being recognized among intravenous drug use (IVDU) patients. We sought to assess the trends and risk factors that contribute to left-sided IE in this high-risk population at University of Kentucky. Methods: A retrospective chart review of patients with the diagnosis of both IE and IVDU admitted at University of Kentucky was carried out from January 1, 2015 to December 31, 2019. Baseline characteristics, trends of endocarditis and clinical outcomes (mortality and in-hospital interventions) were recorded. Results: A total of 197 patients were admitted for management of endocarditis. One hundred and fourteen (57.9%) had right-sided endocarditis, 25 (12.7%) had combined left-sided and right-sided endocarditis, and 58 (29.4%) had left-sided endocarditis. Staphylococcus aureus was the most common pathogen. Mortality and inpatient surgical interventions were higher among patients with left-sided endocarditis. Patent foramen ovale (PFO) was the most common shunt found (3.1%), followed by atrial septal defect (ASD, 2.4%) with PFO being significantly more common among patients with left-sided endocarditis. Conclusion: Right-sided endocarditis continues to be predominant among IVDU patients and Staphylococcus aureus was the most common organism involved. Patients with evidence of left-sided disease were found to have significantly more PFO, needed more inpatient valvular surgeries, and had higher all-cause mortality. Further studies are needed to assess if PFO or ASD can increase the risk of acquiring left-sided endocarditis in IVDU. Cardiol Res. 2023;14(3):176-182 doi: https://doi.org/10.14740/cr1484
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".