Equid trypanosomiasis: A systematic review of the global impact of a neglected veterinary disease: Prevalence, morbidity and mortality
Bibliographic record
Abstract
presented to all clinics included in the study during the study period.The relationship between selected epidemiological factors and outcome was analysed statistically using a Pearson Chi-Square Test with a significance level of p < 0.05.A correspondence analysis was conducted to display in a bi-plot any structure hidden in the multivariate setting of the data.Results: 571 cases met the inclusion criteria.The overall prevalence of tetanus was 0.15% (571 of 64,713).The distribution of cases is significantly lower during the summer compared to the other seasons ( p = 0.003).Tetanus was more frequent in animals under 6 years old ( p = 0.05, 309 of 571) and mortality rate was higher in animals under 6 years old ( p = 0.006, 234 of 309), and in autumn ( p = 0.04).Similarly, mortality rate was higher in animals presenting with wounds in the limb compared to other wound locations ( p = 0.005). Main limitations: Retrospective multicentre study.Conclusions: Age, season and wound location are significantly related to tetanus survival in working equids.This should be considered by clinicians when evaluating, treating or advising on the prognosis of tetanus cases.This is the largest sample size of tetanus studied in equids and provides useful data for veterinarians and researchers.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.012 | 0.013 |
| 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) | 0.002 | 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".