Association between “D-dimeritis” in the emergency department and COVID-19 hospital burden
Bibliographic record
Abstract
This study analyzed D-dimer tests requested by the two emergency departments of the University Hospital Trust of Verona during the Coronavirus disease 2019 (COVID-19) pandemic. Our findings show that the aggregate monthly number of D-dimer test requests from both emergency departments increased significantly (+39%) in 2021 compared to 2019, followed by a steady decline until 2024, when the aggregate monthly test requests were nearly threefold lower than before the pandemic. A strong association was observed between monthly D-dimer test requests and ICU admissions for COVID-19 in Verona (r=0.90; p=0.037), whereas no significant correlation was found with COVID-19 positive cases (r=0.11; p=0.855) or COVID-19 hospitalizations (r=0.70; p=0.118) in Verona. These results suggest that the heightened severity of COVID-19 cases during the early pandemic phase was a key driver of increased D-dimer test requests, while the subsequent decline may reflect reduced disease burden, improved test appropriateness through enhanced healthcare staff education, and a better understanding of COVID-19 pathophysiology.
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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) | 0.001 | 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".