Consequences of Social Distancing Measures During the COVID-19 Pandemic First Wave on the Epidemiology of Children Admitted to Pediatric Emergency Departments and Pediatric Intensive Care Units: A Systematic Review
Bibliographic record
Abstract
Objectives: To synthesize knowledge describing the impact of social distancing measures (SDM) during the first wave of the COVID-19 pandemic on acute illness in children by focusing on the admission to pediatric emergency departments (PED) and pediatric intensive care units (PICU). Methods: We searched Cochrane Database of Systematic Reviews, Cochrane Controlled Trials Register, EPOC Register, MEDLINE, Evidence-Based Medicine Reviews, EMBASE, WHO database on COVID-19, Cochrane Resources on COVID-19, Oxford COVID-19 Evidence Service, Google Scholar for literature on COVID-19 including pre-print engines such as medRxiv, bioRxiv, Litcovid and SSRN for unpublished studies on COVID-19 in December 2020. We did not apply study design filtering. The primary outcomes of interest were the global incidence of admission to PICU and PED, disease etiologies, and elective/emergency surgeries, compared to the historical cohort in each studied region, country, or hospital. Results: We identified 6,660 records and eighty-seven articles met our inclusion criteria. All the studies were with before and after study design compared with the historical data, with an overall high risk of bias. The median daily PED admissions decreased to 65% in 39 included studies and a 54% reduction in PICU admission in eight studies. A significant decline was reported in acute respiratory illness and LRTI in five studies with a median decrease of 63%. We did not find a consistent trend in the incidence of poisoning, but there was an increasing trend in burns, DKA, and a downward trend in trauma and unplanned surgeries. Conclusions: SDMs in the first wave of the COVID-19 pandemic reduced the global incidence of pediatric acute illnesses. However, some disease groups, such as burns and DKA, showed a tendency to increase and its severity of illness at hospital presentation. Continual effort and research into the subject should be essential for us to better understand the effects of this new phenomenon of SDMs to protect the well-being of children. Systematic Review Registration: Clinicaltrials.gov, identifier: CRD42020221215.
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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 | 0.004 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".