Incidence and outcomes of non-communicable pediatric diseases during the COVID-19 pandemic: An interrupted timeseries analysis
Bibliographic record
Abstract
In response to the onset of the COVID-19 pandemic, many countries implemented public health interventions aimed at reducing the spread of the virus, such as social distancing and closure of all non-essential services, as well as closure of daycares and schools. Concerns have however been raised over the negative consequences of the COVID-19 pandemic and its associated interventions on healthcare systems and access to healthcare. Notably, worldwide reductions in pediatric emergency department (ED) visits were observed shortly after the onset of the pandemic. While this drop in ED visits has been attributed to a general reduction in infectious diseases other than SARS-CoV-2, concerns were raised over delayed treatment and worse prognosis for pediatric patients with chronic or non-communicable diseases. However, the impact of the pandemic on non-communicable pediatric diseases remains largely unknown.This study aimed to quantify whether there was a change in incidence of children (<18 years) presenting with 1) appendicitis and 2) confirmed or suspected cancers at the pediatric ED during the first year of the COVID-19 pandemic relative to prior to the pandemic in Quebec, as well as whether there were any changes in severity of pediatric patients with these diseases.This retrospective cohort study made use of the computerized emergency and admissions database of the two large tertiary-care pediatric centers in Montreal, Quebec: The McGill University Health Center (MUHC) and the Centre hospitalier universitaire Sainte-Justine (CHU-SJ). The diagnoses of interest included children with appendicitis in the first manuscript and children with confirmed or suspected cancer in the second manuscript. An interrupted timeseries design (ITS) was used to quantify the change in bi-monthly incidence of ED visits for the diagnoses of interest via Poisson regression or negative-binomial regression, as appropriate, adjusted for underlying baseline trend, seasonality, long term cycles, and hospital site. Outcomes of interests included the change in incidence at the onset of the COVID-19 pandemic (March-April 2020) and the change in bi-monthly trend throughout the first 14 months of the pandemic compared to the predicted incidence from a four-year historical control period (January 2016-February 2020). There was evidence of a 14% increase in appendicitis diagnoses at the pediatric ED (Incidence Rate Ratio(IRR)= 1.14, 95% CI= 1.01 ; 1.28). This increase remained stable throughout the first 14 months of the pandemic (IRR=1.00 , 95% CI= 0.95 ; 1.04). There was evidence of a decrease in average LOS for appendectomies during the pandemic (-0.88 days 95% CI= -1.65 ; -0.12), but any change in risk of perforation or surgical drainage remained ambiguous (risk ratio= 0.83, 95% CI= 0.52 ; 1.32). A 39% reduction in overall ED visits for children with suspected and confirmed cancers was observed at the onset of the pandemic (IRR= 0.65, 95% CI: 0.53, 0.79), followed by a gradual increase in cases to baseline throughout the pandemic (IRR=1.11, 95% CI: 1.05, 1.17). There was evidence of a reduction in risk of multiple readmissions during the pandemic relative to the pre-pandemic risk (HR= 0.83, 95% CI= 0.74 ; 0.93).This study found evidence of an increase in visits for appendicitis and a reduction in visits for suspected cancers at the pediatric ED during the COVID-19 pandemic relative to previous years. Potential associations between SARS-CoV-2 infection and onset of appendicitis should continue to be investigated. There was no indication of changes in severity of patients with appendicitis during the pandemic, indicating that delays in seeking medical treatment were not common or did not affect the prognosis of patients. The observed reduction in suspected cancer diagnoses and oncology ward admissions may be related to fewer non-SARS-CoV-2 viral transmissions during the first months of the pandemic, and/or in delays in seeking medical advice
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".