Injection Drug Use Endocarditis: An Inner-City Hospital Experience
Bibliographic record
Abstract
BackgroundThere has been a rise in the incidence of injection drug use and associated infective endocarditis.MethodsThe clinical outcomes of 39 patients admitted with injection drug use–associated infective endocarditis were collected with a mean follow-up of 14 months. The outcomes were compared for patients treated medically with those undergoing surgical intervention. Results: The mean age was 39 ± 11 years; 54% were female. Thirty-two patients (82%) had native and 7 (18%) prosthetic infective endocarditis. The tricuspid valve was affected in 17 patients (43%), the mitral in 10 (26%), the aortic in 4 (10%), and multiple valves in 8 (20%). Sixteen (41%) patients underwent surgery, and 23 (59%) were treated with medical therapy. The indications for surgery included heart failure, systemic emboli, recurrent infection, and vegetation size ≥10 mm. Patients undergoing surgery had a higher rate of paravalvular abscess (25% vs 0%, P = 0.02), valve perforation (37% vs 11%, P = 0.04), and mitral valve involvement (44% vs 13%, P = 0.06), whereas medically treated patients had higher tricuspid valve involvement (61% vs 19%, P = 0.02). During follow-up, 26% of medical and 31% of surgical cohort patients died (P = 0.7). Mortality was highest (54%) among those who continued medical management despite an indication for surgery. Univariate predictors of mortality were age (odds ratio [OR] 1.09, 95% confidence interval [CI]: 1.01-1.17; P = 0.02), heart failure (OR 6.9; 95% CI: 1.24-37.49; P = 0.02), septicemia (OR 4.40; 95% CI:0.99-19.54; P = 0.05), and shock (OR 10.8; 95% CI: 1.68-69.92; P = 0.01).ConclusionsDespite contemporary therapy, patients with injection drug use–associated infective endocarditis remain at high risk of complications and poor clinical outcomes. These findings highlight the need for developing new care pathways and a team approach for effective management.
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 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".