Bacteria and the growing threat of multidrug resistance for invasive cardiac interventions
Bibliographic record
Abstract
Invasive cardiovascular procedures which include heart transplantations, congenital heart surgery, coronary artery bypass grafts, cardiac valve repair and replacement, and interventional cardiac electrophysiology procedures represent common mechanisms to treat a variety of cardiovascular diseases across the globe. The majority of these invasive approaches employ antibiotics as a regular and obligatory feature of the invasive procedure. Although the growing incidence of bacterial resistance to currently used antibiotics threatens to curtail the use of all interventional surgical techniques, it remains an underappreciated threat within the arsenal of cardiovascular therapies. It is reasonable to expect that the continued overuse of antibiotics and the frequent management of coronavirus disease 2019 (COVID-19) infected patients with high doses of antibiotics will inevitably accentuate the rise of multidrug resistance. The purpose of this article is to heighten awareness of the role of bacterial infections in cardiovascular disease, the use of antibiotics in today's cardiovascular surgical theaters, the threat facing cardiovascular surgery should multidrug resistance continue to rise unabated, and the development of new antibiotic platforms to solve this problem.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".