Does social distancing impact pediatric upper airway infections? An observational controlled study and a brief literature review
Bibliographic record
Abstract
PURPOSE: SARS-CoV-2 pandemic has reduced social interaction even among children. The objective of the study was to assess the role of social distancing in the course of common pediatric upper airway recurrent diseases. MATERIALS AND METHODS: Patients aged ≤14 years with at least one ENT-related clinical condition were retrospectively recruited. All patients had two outpatient evaluations in the same period (April - September): the control group had the first evaluation in 2018 and second in 2019, whereas the case group had the first evaluation in 2019 and second in 2020. Patients of each group were individually compared between their two visits and deemed improved/unchanged/worsened for each specific ENT condition. The percentage of children improved/unchanged/worsened were then collectively compared between the two groups for each condition. RESULTS: Patients who experienced social distancing presented a significantly higher improvement rate than controls for recurrent acute otitis media episodes (35.1 % vs. 10.8 %; Fisher's exact test p = 0.033) and for tympanogram type (54.5 % vs. 11.1 %, Fisher's exact test p = 0.009). CONCLUSIONS: The anti-contagion social restrictions decreased the prevalence of middle ear infections and effusion in children. Further studies on larger cohorts are required to better elucidate these findings.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".