Risk factors of infective endocarditis in persons who inject drugs
Bibliographic record
Abstract
BACKGROUND: The rising incidence of infective endocarditis (IE) among people who inject drugs (PWID) has been a major concern across North America. The coincident rise in IE and change of drug preference to hydromorphone controlled-release (CR) among our PWID population in London, Ontario intrigued us to study the details of injection practices leading to IE, which have not been well characterized in literature. METHODS: A case-control study, using one-on-one interviews to understand risk factors and injection practices associated with IE among PWID was conducted. Eligible participants included those who had injected drugs within the last 3 months, were > 18 years old and either never had or were currently admitted for an IE episode. Cases were recruited from the tertiary care centers and controls without IE were recruited from outpatient clinics and addiction clinics in London, Ontario. RESULTS: Thirty three cases (PWID IE+) and 102 controls (PWID but IE-) were interviewed. Multivariable logistic regressions showed that the odds of having IE were 4.65 times higher among females (95% CI 1.85, 12.28; p = 0.001) and 5.76 times higher among PWID who did not use clean injection equipment from the provincial distribution networks (95% CI 2.37, 14.91; p < 0.001). Injecting into multiple sites and heating hydromorphone-CR prior to injection were not found to be significantly associated with IE. Hydromorphone-CR was the most commonly injected drug in both groups (90.9% cases; 81.4% controls; p = 0.197). DISCUSSION: Our study highlights the importance of distributing clean injection materials for IE prevention. Furthermore, our study showcases that females are at higher risk of IE, which is contrary to the reported literature. Gender differences in injection techniques, which may place women at higher risk of IE, require further study. We suspect that the very high prevalence of hydromorphone-CR use made our sample size too small to identify a significant association between its use and IE, which has been established in the literature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".