Increased rate of significant findings on brain MRI during the early stage of the COVID-19 pandemic
Bibliographic record
Abstract
Objectives To assess the effect of the COVID-19 pandemic on the proportion of abnormal paediatric neuroimaging findings as a surrogate marker for potential underutilisation. Methods Consecutive paediatric brain MRIs performed between March 27th and June 19th 2019 (T baseline ) and March 23rd and June 1st 2020 (T pandemic ) were reviewed and classified according to presence or absence and type of imaging abnormality, and graded regarding severity on a 5-point Likert scale, where grade 4 was defined as abnormal finding requiring non-urgent intervention and grade 5 was defined as acute illness prompting urgent medical intervention. Non-parametric statistical testing was used to assess for significant differences between T pandemic vs. T baseline . Results Fewer paediatric MRI brains were performed during T pandemic compared to T baseline (12.2 vs 14.7 examinations/day). No significant difference was found between the two time periods regarding sex and age (T baseline : 557 females (44.63%), 7.95 ± 5.49 years, T pandemic : 385 females (44.61%), 7.64 ± 6.11 years; p = 1 and p = .079, respectively). MRI brain examinations during T pandemic had a higher likelihood of being abnormal, 41.25% vs. 25.32% ( p<.0001). Vascular abnormalities were more frequent during T pandemic (11.01% vs 8.01%, p = .02), congenital malformations were less common (8.34% vs 12.34%, p = .004). Severity of MRI brain examinations was significantly different when comparing group 4 and group 5 individually and combined between T baseline and T pandemic ( p = .0018, p < .0001, and p <.0001, respectively). Conclusions The rate of abnormality and severity found on paediatric brain MRI was significantly higher during the early phase of the pandemic, likely due to underutilisation.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| 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".