Ten‐year study of bacteremia in hemodialysis patients in a single center
Bibliographic record
Abstract
Background: The incidence of infection in patients on chronic hemodialysis in higher than that of the general population. Infection is known to be a major cause of morbidity and mortality in these patients. The vascular access is important for hemodialysis, but infection through this route is the most common source of bacteremia and can be lethal to the patients. Despite the high morbidity and mortality of bacteremia in patients on chronic hemodialysis, the clinical characteristics of bacteremia in hemodialysis patients is rarely reported yet in Korea. Methods: We included 696 hemodialysis patients from January 1993 to December 2003 at Uijongbu St. Mary's Hospital. We investigated incidence, source, causative organisms, clinical manifestations, complication, and mortality of bacteremia. We compared clinical factors, morbidity, and mortality between arteriovenous fistula and central venous catheter groups. Results: Total 52 cases of bacteremia occurred in 43 patients. The major source of infection was vascular access (48%). Staphylococcus aureus was most common organism isolated. Major complications were septic shock (9.6%), pneumonia (9.6%), infective endocarditis (3.8%), and aortic pseudoaneurysm (1.9%). Nine patients died from septic shock (n = 4), aspiration pneumonia (n = 2), hypoxic brain injury (n = 1), gastrointestinal bleeding (n = 1), and rupture of aortic pseudoaneurysm. The central venous catheter group (n = 22) had higher incidences of vascular access as a source of infection (81.8% vs 23.3%, p < 0.001) and staphylococcus as a causative organism (77.2% vs 50.0%, p = 0.042) than the arteriovenous group. Conclusion: This data shows that bacteremia causes high incidence of fatal complications and mortality. Therefore, careful management of vascular access as well as early detection of bacteremia is an important factor for the prevention of infection and proper antibiotic therapy should be started early.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".