Infective endocarditis: it takes a team
Bibliographic record
Abstract
Infective endocarditis (IE) is a relatively rare but life-threatening systemic infection, which remains associated with high morbidity and mortality. The epidemiology of IE has shifted to involve an increasing numbers of older patients with both cardiovascular and other types of prosthetic devices, multiple comorbid conditions often requiring invasive procedures, increasingly virulent pathogens, in particular Staphylococcus aureus, or that can harbour anti-microbial resistance, and an escalation of injection drug use in many areas of the world. In parallel, advancements in diagnostic and therapeutic options have led to complex strategies in patients' management. Despite these epidemiologic shifts, clinical trials have been rare and most of the evidence guiding IE management derives from expert consensus or analysis of large registries. Because of this, a multi-disciplinary IE team-based approach has been recommended as the standard of care. The aim of this review is to explore the rationale for a multi-disciplinary team-based approach to the management of IE. This approach has proved to be potentially beneficial based on multiple investigations that have evaluated patient outcomes. In addition, implementation strategies, feasibility and options of the team approach have also been highlighted.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".