Epidemiology, Microbiology, and Clinical Outcomes Among Patients With Intravenous Drug Use-Associated Infective Endocarditis in New Brunswick
Bibliographic record
Abstract
Background Within the context of Canada's opioid crisis, medical complications associated with intravenous drug use (IVDU) are increasing. Infective endocarditis (IE) is a serious complication of IVDU, and understanding the characteristics of these patients could aid health systems, clinicians, and patients in the optimization of treatment and prevention of IVDU-IE. Methods At a tertiary care hospital in southern New Brunswick, we conducted a retrospective chart review to identify patients with IVDU-IE admitted between January 1, 2013, and December 31, 2017. We collected data related to the epidemiology, microbiology, clinical manifestations, echocardiography, complications during hospital admission, and outcomes. Results Forty-two cases of IVDU-IE met inclusion criteria. The rate of IVDU-IE increased from 2.28 per 100,000 population in 2014 to 4.00 in 2017, which, although not statistically significant, reflects patterns in other jurisdictions. Most patients (72.4%) were male, and the mean age was 38.3 (±11.5) years. Most patients (79.3%) injected opioids. The most common clinical sign was fever (90.5%), and Staphylococcus aureus ( 61.9%) was the most common microorganism. The tricuspid valve was most commonly infected (58.5%), 50% of cases had heart failure as a complication during admission, and 45.2% of cases required valve replacement or repair. The 2-year survival rate after admission for initial IVDU-IE episode was 62.0% (95% confidence interval: 36.5-79.7). Conclusion IVDU-IE is common in New Brunswick and may be increasing. Despite the relatively young age of this patient population, IVDU-IE is associated with significant morbidity and mortality. Expanding effective harm reduction and addiction treatment strategies for this cohort is recommended.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".