Catheter‐related Infection and Septicemia: Impact of Seasonality and Modifiable Practices from the DOPPS
Bibliographic record
Abstract
Hemodialysis (HD) catheter-related infection (CRI) and septicemia contribute to adverse outcomes. The impact of seasonality and prophylactic dialysis practices during high-risk periods remain unexplored. This multicenter study analyzed DOPPS data from 12,122 HD patients (from 442 facilities) to determine the association between seasonally related climatic variables and CRI and septicemia. Climatic variables were determined by linkage to National Climatic Data Center of National Oceanic and Atmospheric Administration data. Catheter care protocols were examined to determine if they could mitigate infection risk during high-risk seasons. Survival models were used to estimate the adjusted hazard ratio (AHR) of septicemia by season and by facility catheter dressing protocol. The overall catheter-related septicemia rate was 0.47 per 1000 catheter days. It varied by season, with an AHR for summer of 1.46 (95% CI: 1.19-1.80) compared with winter. Septicemia was associated with temperature (AHR = 1.07; 95% CI: 1.02-1.13; p < 0.001). Dressing protocols using chlorhexidine (AHR of septicemia = 0.55; 95% CI: 0.39-0.78) were associated with fewest episodes of CRI or septicemia. Higher catheter-related septicemia in summer may be due to seasonal conditions (e.g., heat, perspiration) that facilitate bacterial growth and compromise protective measures. Extra vigilance and use of chlorhexidine-based dressing protocols may provide prophylaxis against CRI and septicemia.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".