Comparison of techniques for culture of dialysis water and fluid
Bibliographic record
Abstract
INTRODUCTION: Microbiological culture of dialysis water and fluid is a routine safety measure. In the United States (U.S.), laboratories perform these cultures on trypticase soy agar at 35-37°C for 48 h (TSA-48h), not on the tryptone glucose extract agar or Reasoner's 2A agar at 17-23°C for 7 days (TGEA-7d and R2A-7d, respectively) recommended by international standards. We compared culture methods to identify samples exceeding the accepted action level of 50 CFU/mL. METHODS: Dialysis water and fluid samples collected from 41 U.S. dialysis programs between 2011 and 2014 were cultured at two U.S. laboratories. Each sample was cultured using (1) either TGEA-7d or R2A-7d and (2) TSA-48h. We compared proportions exceeding the action level by different methods and test characteristics of TSA-48h to those of TGEA-7d and R2A-7d. FINDINGS: The proportion of water samples yielding colony counts ≥50 CFU/mL by TGEA-7d was significantly different from the proportion by TSA-48h (P = 0.001; difference in proportion 4.3% [95%CI 1.3-7.3%]). The proportions of dialysis fluid samples ≥50 CFU/mL by TGEA-7d and TSA-48h were not significantly different; there were no significant differences for comparisons of R2A-7d to TSA-48h. DISCUSSION: In dialysis fluid, TSA-48h was comparable to TGEA-7d and R2A-7d in identifying samples as having bacterial counts ≥50 CFU/mL. In dialysis water, TSA-48h was comparable to R2A-7d in identifying samples ≥50 CFU/mL, but TGEA-7d did yield significantly more results above 50 CFU/mL. Nonetheless, the negative predictive value of a TSA-48h result of <50 CFU/mL in dialysis water exceeded 95%.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".