Evaluation of a Rapid Immunochromatographic test kit to the Gold Standard Fluorescent Antibody test for diagnosis of rabies in animals in Bhutan
Bibliographic record
Abstract
Abstract Background: Rabies kills approximately 59,000 people in the world each year worldwide. Rapid and accurate diagnosis of rabies is important for instituting rapid containment measures and for advising the exposed people for postexposure treatment. The application of a rapid diagnostic tests in the field can greatly enhance disease surveillance activities, especially in resource poor settings.Methods: From 2012 to 2017, a total of 179 brain tissue samples collected from different animal species (113 dogs, 50 cattle, 10 cats, 3 goats, 2 horses, and 1 bear) suspected of having died due to rabies were selected and tested using the rapid immunochromatographic kit from BioNote© company and compared to the Gold Standard Fluorescent Antibody test (FAT) for diagnosis of rabies.Results: Among 179 samples examined in this study, there was concordance in results by the rapid test and FAT in 115 positive samples and 54 negative samples. Test result were discordant in 10 samples which were positive by FAT, but negative (false negative) by rapid kit. The rapid test kit showed a sensitivity of 92% (95% CI: 85.9 – 95.6) and specificity of 100% (95% CI: 93.4 – 100) using FAT as the gold standard. The positive and negative predicative values were found to be 100% (95% CI:96.7 – 100) and 84% (95% CI: 73.6 – 91.3), respectively. Overall there was 94.41% (95% CI: 90 – 96.9) test agreement (almost perfect agreement) between rapid test and FAT (Kappa value = 0.874).Conclusions: Our results demonstrate the potential value of the rapid test kit for countries with limited diagnostic resources, including Bhutan. The rapid kit’s inability to correctly detect 10 FAT-positive samples (10 out of 179 (5.6%) were false negatives) in our study could have been due to the low viral load in the samples (< 102.0LD50/0.03ml) which could not be detected by the rapid kit as compared with the FAT. The human factor related to the varying experiences of the technicians who performed the test in the field also may have influenced the test result. The rapid test kit is inexpensive, rapid and easy to use in the field or in laboratory setting without the need for special training and can support to enhance rabies surveillance in resource poor countries.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".