114 A Comparison of <i>in vitro</i> Disc Diffusion and Time‐Kill Kinetic Assays for the Evaluation of Antimicrobial Activity of Silver Containing Wound Dressings
Bibliographic record
Abstract
There is a plethora of new silver containing dressings on the market today. Various manufacturers attempt to show that their dressings are the most efficacious and therefore should be preferentially employed by health care workers based on the results of their in vitro tests. However, there have been no studies to date that clearly identify which in vitro tests are appropriate for comparison purposes. The available literature suggests that there are problems with disc sensitivity assays in terms of assessing the antimicrobial efficacy of silver. Spadaro (1985) has shown that the diameters of zones of inhibition were not proportional to the concentration of anodic silver in complex test media. Further, Richards et al (2001) have shown that zones of inhibition did not appear to correlate to log reduction assay data for silver containing dressings. Other authors favour log reduction or time kill assays as they better compare to clinical data. The purpose of this study was to determine which in vivo test is most appropriate for evaluating the antimicrobial efficacy of silver‐containing dressings. This was done by testing 8 different silver containing dressings and 2 non‐silver (mafenide acetate or hexamethylene biguanide) containing topical agents against 17 clinically relevant microorganisms using both zone of inhibition assays and time‐kill kinetic assays in complex media. The results for the two assays were then correlated to determine if the methods generated similar results. It was determined that the two methods do not correlate at all. This is most likely a result of the silver interacting with the media in the zone of inhibition test, thus invalidating the results of this test. We therefore conclude that zone of inhibition data generated for silver‐containing dressings is of little value when assessing antimicrobial efficacy, and that time‐kill assays are of greater use.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".