Diagnostic Accuracy Assessment of Sensititre and Agar Disk Diffusion for Determining Antimicrobial Resistance Profiles of Bovine Clinical Mastitis Pathogens
Bibliographic record
Abstract
Determining the accuracy and precision of a measuring instrument is pertinent in antimicrobial susceptibility testing. This study was conducted to predict the diagnostic accuracy of the Sensititre MIC mastitis panel (Sensititre) and agar disk diffusion (ADD) method with reference to the manual broth microdilution test method for antimicrobial resistance profiling of Escherichia coli (n = 156), Staphylococcus aureus (n = 154), streptococcal (n = 116), and enterococcal (n = 31) bovine clinical mastitis isolates. The activities of ampicillin, ceftiofur, cephalothin, erythromycin, oxacillin, penicillin, the penicillin-novobiocin combination, pirlimycin, and tetracycline were tested against the isolates. Diagnostic accuracy was determined by estimating the area under the receiver operating characteristic curve; intertest essential and categorical agreements were determined as well. Sensititre and the ADD method demonstrated moderate to highly accurate (71 to 99%) and moderate to perfect (71 to 100%) predictive accuracies for 74 and 76% of the isolate-antimicrobial MIC combinations, respectively. However, the diagnostic accuracy was low for S. aureus-ceftiofur/oxacillin combinations and other streptococcus-ampicillin combinations by either testing method. Essential agreement between Sensititre automatic MIC readings and MIC readings obtained by the broth microdilution test method was 87%. Essential agreement between Sensititre automatic and manual MIC reading methods was 97%. Furthermore, the ADD test method and Sensititre MIC method exhibited 92 and 91% categorical agreement (sensitive, intermediate, resistant) of results, respectively, compared with the reference method. However, both methods demonstrated lower agreement for E. coli-ampicillin/cephalothin combinations than for Gram-positive isolates. In conclusion, the Sensititre and ADD methods had moderate to high diagnostic accuracy and very good essential and categorical agreement for most udder pathogen-antimicrobial combinations and can be readily employed in veterinary diagnostic laboratories.
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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 | 0.019 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".