The effect of the COVID-19 pandemic on pediatric asthma-related emergency department visits and hospital admissions in Montréal, Quebec: a retrospective cohort study
Bibliographic record
Abstract
<h3>Background:</h3> Asthma is a chronic respiratory condition that affects 10% of Canadian children and is often exacerbated by viral respiratory infections, prompting concerns about the severity of SARS-CoV-2 disease in children with asthma. We compared sociodemographic and clinical characteristics of children presenting to the emergency department and the incidence of these visits, before and during the pandemic. <h3>Methods:</h3> We included children aged 0 to 17 years presenting with asthma to 2 tertiary pediatric emergency departments in Montréal, Quebec, between the prepandemic (Jan. 1, 2017, to Mar. 31, 2020) and pandemic (Apr. 1, 2020, to June 30, 2021) periods. We compared the number of emergency department visits and hospital admissions with an interrupted time series analysis and compared the sociodemographic characteristics based on the Canadian Index of Multiple Deprivation (CIMD) and clinical characteristics (including triage level, intensive care admissions, etc.) with Mann–Whitney and χ<sup>2</sup> tests. <h3>Results:</h3> We examined 22 746 asthma-related emergency department visits. During the pandemic, a greater proportion of patients presented a triage level 1 or 2 (19.3% v. 14.7%) and were admitted to the intensive care unit (2.5% v. 1.3%). The patients’ CIMD quintile distributions did not differ between the 2 periods. We found a 47% decrease (relative risk [RR] 0.53, 95% confidence interval [CI] 0.37 to 0.76) in emergency department visits and a 49% decrease (RR 0.51, 95% CI 0.34 to 0.76) in hospital admissions during the pandemic. <h3>Interpretation:</h3> The decrease in asthma-related emergency department visits was observed through the third wave of the pandemic, but children presented with a higher acuity and with no identified sociodemographic changes. Future studies are required to understand individual behaviours that may have led to the increased acuity at presentation observed in this study.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".