Retrospective Study on Escherichia coli Infection in Broilers Subjected to Postmortem Examination and Antibiotic Resistance of Isolates in Trinidad
Bibliographic record
Abstract
An 8-yr retrospective study was conducted to evaluate the rate of Escherichia coli infection and antibiotic resistance of isolates from diseased broilers submitted for diagnosis in Trinidad from 1990 to 1997. Of a total of 906 cases of diseased birds subjected to postmortem examination, 603 (66.6%) had E. coli infection. The number of cases increased over the years from 16 in 1990 to a peak of 294 in 1996. For every year, at least 50% of all broiler cases had E. coli infection. The rate of infection was significantly higher during the rainy season (74.1 +/- 6.9%) than during the dry season (57.8 +/- 7.0%). Approximately 50% of all E. coli isolates were resistant to 9 out of a total of 11 antimicrobial drugs selected for the study. The isolates showed an increasing trend of resistance to amoxicillin, apramycin, gentamicin, nitrofurantoin, norfloxacin, and sulfamethoxazole-trimethoprim. However, only the trends of resistance to apramycin and norfloxacin were statistically significant. Overall, of the antimicrobial drugs selected, norfloxacin relatively appeared as the best choice for treatment. From this study, we conclude that the high rate of E. coli infection in broilers submitted for diagnosis along with the high resistance of isolates to antimicrobial drugs constitute a threat to the poultry industry on the island.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".