The influence of comorbidity on the risk of access‐related bacteremia in chronic hemodialysis patients
Bibliographic record
Abstract
Access-related bacteremia is an important cause of morbidity in chronic hemodialysis patients. The incidence of bacteremia is higher in patients dialyzing through a tunneled central venous catheter (TCVC) compared with an arteriovenous fistula (AVF). Our aim was to explore if this is explained by patient comorbidity. Two groups of chronic hemodialysis outpatients were compared: all patients who dialyzed through a TCVC at any time during 2003 and were fit enough to subsequently have a functioning AVF or renal transplant even if it was after 2003 (Group 1; n=93); and all patients who dialyzed through a TCVC in 2003 and were not fit enough to have a functioning AVF or renal transplant (Group 2; n=119). Episodes of bacteremia (n=71) were identified and those not related to access were excluded. Patients in Group 1 were younger than Group 2 (57.5 years vs. 64.8 years; P=0.001). The incidences of bacteremia in Groups 1 and 2 were, respectively, 0.31 and 0.44 episodes per 1000 patient days while dialyzing through an AVF (P=0.77), and 2.21 and 2.27 per 1000 days while dialyzing through a TCVC (P=0.91). The 3-year actual survival from January 1, 2003 to January 1, 2006 was significantly higher in Group 1 than in Group 2 (80.6% vs. 26.1%; P<0.0001) confirming the higher comorbidity of the patients in Group 2. Patients dialyzing through a TCVC (compared with an AVF) have a significantly higher risk of access-related bacteremia, irrespective of comorbidity.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".