The Second Heart Program—A multidisciplinary team supporting people who inject drugs with infective endocarditis: Protocol of a feasibility study
Bibliographic record
Abstract
INTRODUCTION: Infective endocarditis (IE) is a severe and highly prevalent infection among people who inject drugs (PWID). While short-term (30-day) outcomes are similar between PWID and non-PWID, the long-term outcomes among PWID after IE are poor, with 1-year mortality rates in excess of 25%. Novel clinical interventions are needed to address the unique needs of PWID with IE, including increasing access to substance use treatment and addressing structural barriers and social determinants of health. METHODS AND ANALYSIS: PWID with IE will be connected to a multidisciplinary team that will transition with them from hospital to the community. The six components of the Second Heart Team are: (1) peer support worker with lived experience, (2) systems navigator, (3) addiction medicine physician, (4) primary care physician, (5) infectious diseases specialist, (6) cardiovascular surgeon. A convergent mixed-methods study design will be used to test the feasibility of this intervention. We will concurrently collect quantitative and qualitative data and 'mix' at the interpretation stage of the study to answer our research questions. ETHICS AND DISSEMINATION: This study has been approved by the Hamilton Integrated Research Ethics Board (Project No. 7012). Results will be presented at national and international conferences and submitted for publication in a scientific journal. CLINICAL TRAIL REGISTRARION: Trial registration number: ISRCTN14968657 https://www.isrctn.com/ISRCTN14968657.
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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 | 0.083 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.064 | 0.015 |
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".