Infective endocarditis in a hemodialysis patient: A dreaded complication
Bibliographic record
Abstract
Infection is the most common cause of death in hemodialysis patients, after cardiovascular disease. Dialysis access infections, with secondary septicemia, contribute significantly to patient mortality. The most common source is temporary catheterization. Bacteremia occurs commonly in patients receiving hemodialysis, with infective endocarditis being a relatively uncommon, but potentially lethal complication. Valvular calcification is the most significant risk factor. The diagnosis of infective endocarditis is made clinically and confirmed with the echocardiographic modified Duke's criteria. The most common pathogen is Staphylococcus aureus and the mitral valve is the most common site. Staphylococcus aureus infective endocarditis is commonly associated with embolic phenomenon. A high index of suspicion is critical in the early recognition and management of infective endocarditis. However, prevention of bacteremia is undoubtedly the best strategy with the early placement of arteriovenous fistulae. In the case of temporary catheterization, the use of topical mupirocin or polysporin and gentamicin and/or citrate locking is beneficial. Although catheter salvage has not been studied in randomized trials, catheter removal remains standard therapy during bacteremia.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".