Burden of Children Hospitalized With Pertussis in Canada in the Acellular Pertussis Vaccine Era, 1999–2015
Bibliographic record
Abstract
BACKGROUND: Recent increases in pertussis morbidity and mortality rates among young infants have led to a recommendation in some countries for vaccination against pertussis during pregnancy. Having data on the burden of pediatric pertussis in a large population over time is important for establishing the true burden of disease in the acellular pertussis (aP) vaccine era. Here, we describe age-specific epidemiology and morbidity and mortality rates in children hospitalized with pertussis over 17 years across Canada in the aP vaccine era. METHODS: Patients aged ≤16 years who were admitted to 1 of 12 pediatric tertiary-care hospitals across Canada between 1999 and 2015 with confirmed (laboratory-confirmed or epidemiologically linked) or probable (clinically diagnosed) pertussis were included. RESULTS: Overall, 1402 patients with pertussis were included. Infants aged <2 months had the highest mean annual incidences of pertussis hospitalization and intensive care unit (ICU) admission (116.40 [95% confidence interval (CI), 85.32-147.49] and 33.48 [95% CI, 26.35-40.62] per 100 000 population, respectively). The overall proportion of children who required ICU admission was 25.46%, and the proportion was highest in infants aged <2 months (37.90%). Over the span of this study, 21 deaths occurred. Age of <16 weeks, prematurity, encephalopathy, and a confirmed pertussis diagnosis were independent risk factors for ICU admission. Age of <4 weeks, prematurity, and female sex were independent risk factors for death. CONCLUSIONS: In the aP vaccine era, endemic pertussis still contributes considerably to childhood morbidity and death, particularly in infants aged <2 months. Vaccination against pertussis during pregnancy has the potential to reduce this disease burden.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".