Evaluation of Clinical Outcomes of Intravenous Drug Use-Related Infective Endocarditis in Buprenorphine-Treated Patients
Bibliographic record
Abstract
PURPOSE: Intravenous drug use (IVDU) is an independent risk factor for infective endocarditis (IE). IVDU-related IE is associated with poor clinical outcomes, such as infection-related and drug abuse-related readmissions and mortality. Critical interventions to treat addiction, such as medication for opioid use disorder (MOUD) with buprenorphine, may prevent these unfavorable outcomes. This study aimed to establish the effectiveness of buprenorphine prescriptions at hospital discharge for patients admitted for IVDU-related IE. METHODS: A single center, retrospective cohort study evaluated the effectiveness of discharge prescriptions of buprenorphine in adult patients (≥18 years of age) with OUD and IVDU-related IE. Outcomes of 30-day readmissions, 180-day readmissions, and mortality were compared to a cohort of patients who were not prescribed buprenorphine at hospital discharge. RESULTS: The primary endpoint of all cause 30-day readmission was lower in patients who received buprenorphine (n=11/122, 9%) at hospital discharge for IVDU-related IE compared to those who did not (n=9/48, 19%), although not statistically significant (unadjusted OR 0.429, 95% CI 0.165-1.138, p=0.082). After accounting for intensive care admission, infusion unit admission, and psychiatry consultation, the odds of all cause 30-day readmission were statistically lower in patients prescribed buprenorphine (adjusted OR 0.337, 95% CI 0.125-0.909, p=0.029). Additionally, significantly more patients prescribed buprenorphine at discharge followed-up in an outpatient treatment program, 57% and 15% respectively (p<0.001). Incidence of readmission at 180 days and mortality was similar between the two cohorts. CONCLUSIONS: This study demonstrated that buprenorphine prescriptions at hospital discharge in patients with OUD admitted for IVDU-related IE were effective at decreasing readmission rates at 30 days and increasing outpatient treatment follow-up. Therefore, it is imperative that an emphasis on addiction-focused interventions, such as initiating buprenorphine, be considered in this patient population at hospital discharge to decrease hospital readmissions and engage patients in outpatient treatment for OUD. This study is the first to evaluate the effects of MOUD on readmission rates for patients hospitalized with IVDU-related IE and contributes to the growing body of evidence to support addiction-focused interventions for this unique patient population.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".