Importance of case age in the purported association between phylogenetics and hemolytic uremic syndrome in<i>Escherichia coli</i>O157:H7 infections
Bibliographic record
Abstract
Escherichia coli O157:H7 is the largest cause of hemolytic uremic syndrome (HUS). Previous studies proposed that HUS risk varies across the E. coli O157:H7 phylogenetic tree (hypervirulent clade 8), but the role of age in the association is unknown. We determined phylogenetic lineage of E. coli O157:H7 isolates from 1160 culture-confirmed E. coli O157:H7 cases reported in Washington State, 2004-2015. Using generalised estimating equations, we tested the association between phylogenetic lineage and HUS. Age was evaluated as an effect modifier. Among 1082 E. coli O157:H7 cases with both phylogenetic lineage and HUS status (HUS n = 76), stratified analysis suggested effect modification by age. Lineages IIa and IIb, relative to Ib, did not appear associated with HUS in children 0-9-years-old. For cases 10-59-years-old, lineages IIa and IIb appeared to confer increased risk of HUS, relative to lineage Ib. The association reversed in ⩾60-year-olds. Results were similar for clade 8. Phylogenetic lineage appears to be associated with HUS risk only among those ⩾10-years-old. Among children <10, the age group most frequently affected, lineage does not explain progression to HUS. However, lineage frequency varied across age groups, suggesting differences in exposure and/or early disease manifestation.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".