Bayesian estimation of sensitivity and specificity of a rapid mastitis test kit, bacterial culture, and PCR for detection of Staphylococcus aureus, Streptococcus species, and coliforms in bovine milk samples
Bibliographic record
Abstract
Our objectives were to evaluate the diagnostic accuracy of a rapid and novel immunochromatography-based mastitis kit that includes 3 independent tests to detect coliforms (Escherichia coli or Klebsiella pneumoniae), Streptococcus spp., and Staphylococcus aureus. The kit was developed to facilitate diagnostic-based mastitis treatment. Validation of the kit was based on 154 aseptically collected mastitis samples from 2 clinical herds (clinical population) and 120 milk samples from 3 nonclinical herds (nonclinical population) without clinical cases at the time of enrollment. One herd sampled at different times was common to both populations. A 3-test in 2-population Bayesian latent class model with uniform priors for all test parameters except specificity of culture, which was modeled informatively, was used to estimate sensitivity (Se) and specificity (Sp) of the test kit, culture, and PCR at the cow level. The mastitis test kit's 96.9% Sp for Streptococcus spp. had a low false positive percentage (3.1%), which, together with the kit's rapid turnaround time for results, makes it a suitable initial screening test that producers can use to identify clinical cows to treat based on Streptococcus spp. mastitis in kit-positive results. Due to the 60.4% kit Se, producers should follow up on Streptococcus spp. kit-negative cows using a confirmatory test such as PCR (Sp of 98.4%) or culture (Sp of 99.6%). In contrast, aerobic culture had Se of 76.5% and Sp of 99.6% for Streptococcus spp. Similarly, the Sp of the kit (98.2%) and culture (99.8%) for Staph. aureus were particularly high, and even though the kit's Se (61.0%) was lower than culture (88.4%; posterior probability of difference 98%), the kit could be beneficial before use of a confirmatory test for kit-negative samples due to its ease and rapid turnaround time. Mostly, quantitative real-time (q)PCR outperformed the kit's Se (37.7%) and Sp (92.9%) for coliforms, as well as the kit's Se (60.4%) for Streptococcus spp. However, qPCR may require more technical skills and turnaround time for final results. Use of the on-farm mastitis test kit evaluated in the present study could enhance sustainable antimicrobial drug use by rapidly identifying Streptococcus mastitis for targeted treatment. Furthermore, the kit may be used in a Staph. aureus outbreak where cows can be rapidly screened to identify cases for segregation or culling during an outbreak and kit-negative cows further confirmed by milk culture or qPCR. However, the cost-effectiveness of such an approach has not been investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.000 |
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".