Different drugs, different sides: injection use of opioids alone, and not stimulants alone, predisposes to right-sided endocarditis
Bibliographic record
Abstract
OBJECTIVES: Many studies suggest that infective endocarditis (IE) in people who inject drugs is predominantly right sided, while other studies suggest left sided disease; few have differentiated by class of drug used. We hypothesised that based on differing physiological mechanisms, opioids but not stimulants would be associated with right sided IE. METHODS: A retrospective case series of 290 adult (age ≥18) patients with self-reported recent injection drug use, admitted for a first episode of IE to one of three hospitals in London Ontario between April 2007 and March 2018, stratified patients by drug class used (opioid, stimulant or both), and by site of endocarditis. Other outcomes captured included demographics, causative organisms, cardiac and non-cardiac complications, referral to addiction services, medical versus surgical management, and survival. RESULTS: Of those who injected only opioids, 47/71 (69%) developed right-sided IE, 17/71 (25%) developed left-sided IE and 4/71 (6%) had bilateral IE. Of those who injected only stimulants, 11/24 (46%) developed right-sided IE, 11/24 (46%) developed left-sided IE and 2/24 (8%) had bilateral IE. Relative to opioid-only users, stimulant-only users were 1.75 (95% CI 1.05 to 2.93; p=0.031) times more likely to have a left or bilateral IE versus right IE. CONCLUSIONS: While injection use of opioids is associated with a strong predisposition to right-sided IE, stimulants differ in producing a balanced ratio of right and left-sided disease. As the epidemic of crystal methamphetamine injection continues unabated, the rate of left-sided disease, with its attendant higher morbidity and mortality, may also grow.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".