Streptococcus Pneumoniae-Associated Hemolytic Uremic Syndrome Canadian Immunization Monitoring Program ACTive National Pediatric Surveillance (1991-2019)
Bibliographic record
Abstract
Abstract Background: Streptococcus pneumoniae-associated hemolytic uremic syndrome (SP-HUS) is an underreported cause of pediatric non-diarrheal HUS. This study describes the epidemiology of the largest Canadian case series of SP-HUS in comparison with non-HUS invasive pneumococcal disease (IPD). Methods: The Canadian Immunization Monitoring Program, ACTive (IMPACT) is a national surveillance network for vaccine-preventable diseases. All confirmed IPD cases between 1991-2019 were included in the analysis. IPD cases with new HUS diagnoses were identified as SP-HUS cases, and the rest as non-HUS IPD cases. Results: There were 30 (0.4%) cases of SP-HUS amongst 6,757 IPD cases. The median age of SP-HUS cases was 27.5 months, with no significant differences between SP-HUS and non-HUS cases in age or sex. S. pneumoniae serotypes 3 (30%) and 19A (26.7%) were more common in SP-HUS compared to non-HUS cases (P<0.0001). Pneumonia was more frequently observed in SP-HUS (67% vs. cases 26%; P<0.0001). All SP-HUS cases were hospitalized, compared with 71% non-HUS IPD cases (P=0.0004). SP-HUS cases had a longer median hospital length of stay (23.5 vs. 7 days; P<0.0001) and a higher proportion required ICU admission (70 vs 15.5%; P<0.0001). Moreover, ICU stays were longer in HUS cases compared with non-HUS cases (9 vs. 3 days; P<0.0001). All 30 SP-HUS patients survived while 3% of non-HUS cases died (P=0.33). Conclusion: SP-HUS was usually seen in IPD cases with pneumonia and was most commonly caused by serotypes 3 and 19A. Mortality was rare, but ICU care with lengthy hospital stay was common.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".