Do patients with recurrent episodes of campylobacteriosis differ from those with a single disease event?
Bibliographic record
Abstract
BACKGROUND: Although Campylobacter is the leading cause of reported bacterial gastro-enteritis in industrialized countries, little is known on its recurrence. The objective of this study is to describe the risk and the patient characteristics of recurrent episodes of human campylobacteriosis reported in Quebec. METHODS: Laboratory-confirmed cases of campylobacteriosis reported in the province of Quebec, Canada, through ongoing surveillance between 1996 and 2006 were analyzed. The risk of having a recurrent episode of campylobacteriosis was described using life table estimates. Logistic regression was used to assess if gender, age and patient residential location were associated with an increased risk of recurrence. RESULTS: Compared to the baseline risk, the risk for a recurrent disease event was higher for a period of four years and followed a decreasing trend. This increased risk of a recurrent event was similar across gender, but higher for people from rural areas and lower for children under four years of age. CONCLUSIONS: These results may suggest the absence of durable immunity or clinical resilience following a first episode of campylobacteriosis and periodical re-exposure, at least among cases reported through the surveillance system.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".