Bacteremia in kidney transplant recipients: Burden, causes, and consequences
Bibliographic record
Abstract
Bacteremia is an important complication after kidney transplantation. We examined bacteremia and its outcomes in a large cohort of kidney transplant recipients. Kidney transplants from 1-Jul-2004 to 1-Dec-2014 at the Toronto General Hospital were eligible for study inclusion. Bacteremia was defined as two blood culture positives for common skin contaminants or one blood culture positive for other organisms. The cumulative incidence of first bacteremia was estimated using the Kaplan-Meier method, and risk factors were examined in a Cox proportional hazards model. The risk of graft failure or death was assessed in a time-dependent Cox model. Over follow-up, 154 of 1333 patients had at least one bacteremia episode. The cumulative incidence of first bacteremia was 6.8% (6 months) and 11.9% (5 years). Risk factors included recipient diabetes mellitus, time on dialysis, dialysis modality, delayed graft function, donor age, and donor eGFR. Bacteremia increased the risk of total graft failure (hazard ratio 2.11 [95% CI: 1.50, 2.96]), death-censored graft failure (1.73 [0.99, 3.02]), and death with graft function (2.52 [1.63, 3.89]). In conclusion, bacteremia is common after kidney transplantation and impacts both graft and patient survival. Identifying high-risk patients for targeted preventive strategies may reduce the burden and adverse consequences of this important complication.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".