Chronic Sequelae of <i>E. coli</i> O157: Systematic Review and Meta-analysis of the Proportion of <i>E. coli</i> O157 Cases That Develop Chronic Sequelae
Bibliographic record
Abstract
OBJECTIVE: This was a systematic review and meta-analysis to determine the proportion of Escherichia coli O157 cases that develop chronic sequelae. DATA SOURCES: We conducted a systematic review of articles published prior to July 2011 in Pubmed, Agricola, CabDirect, or Food Safety and Technology Abstracts. STUDY SELECTION: Studies were selected that reported the number of E. coli O157 cases that developed reactive arthritis (ReA), hemolytic uremic syndrome (HUS), irritable bowel syndrome, inflammatory bowel disease, or Guillain Barré syndrome. METHODS: Three levels of screening and data extraction of articles were conducted using predefined data fields. Meta-analysis was performed on unique outcome measures using a random-effects model, and heterogeneity was assessed using the I² value. Meta-regression was used to explore the influence of nine study-level variables on heterogeneity. RESULTS: A total of 82 studies were identified reporting 141 different outcome measures; 81 reported on HUS and one reported on ReA. Depending on the number of cases of E. coli O157, the estimate for the proportion of E. coli O157 cases that develop HUS ranged from 17.2% in extra-small studies (<50 cases) to 4.2% in extra-large studies (>1000 cases). Heterogeneity was significantly associated with group size (p<0.0001); however, the majority of the heterogeneity was unexplained. CONCLUSIONS: High unexplained heterogeneity indicated that the study-level factors examined had a minimal influence on the variation of estimates reported.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".