Increase in new-onset type 1 diabetes diagnoses among Brazilian children and adolescents during the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVE: This study aimed to determine if there was a rise in new T1DM cases in children during the pandemic in a large metropolitan area in Brazil. METHODS: The authors conducted a cross-sectional study at five public tertiary care centers that specialize in diabetes in children, comparing all new T1DM cases (ages 0.5-18y) diagnosed from March 2020 to December 2021 (pandemic period, PP) with those from March 2018 to December 2019 (historical period, HP). RESULTS: There were 167 new cases in the PP compared to 99 in the HP, reflecting a 68.7 % rise, with a notable peak observed in the third quarter of 2020 (p = 0.006). The average age of diagnosis was 8.4 ± 4.2 years in the PP and 7.5 ± 3.6 years in the HP, with no significant difference (p = 0.06). The gender distribution, BMI Z scores, and duration of diabetes symptoms before diagnosis were similar. The incidence of diabetic ketoacidosis (DKA) at onset was elevated but did not increase during the pandemic (62.6 % historical vs. 59.3 % pandemic period). During the PP, 24 % of patients reported symptoms of SARS-CoV-2 infection before the diagnosis of T1DM or at admission, and 13 % (7/53) of tested patients were positive for SARS-CoV-2. CONCLUSIONS: The present findings indicate a significant rise in new T1DM cases among children during the COVID-19 pandemic compared to prior years, without differences in DKA at onset.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".