Pulmonary embolism in patients with COVID-19: characteristics and outcomes in the Cardio-COVID Italy multicenter study
Bibliographic record
Abstract
BACKGROUND: Pulmonary embolism (PE) has been described in coronavirus disease 2019 (COVID-19) critically ill patients, but the evidence from more heterogeneous cohorts is limited. METHODS: Data were retrospectively obtained from consecutive COVID-19 patients admitted to 13 Cardiology Units in Italy, from March 1st to April 9th, 2020, and followed until in-hospital death, discharge, or April 23rd, 2020. The association of baseline variables with computed tomography-confirmed PE was investigated by Cox hazards regression analysis. The relationship between D-dimer levels and PE incidence was evaluated using restricted cubic splines models. RESULTS: The study included 689 patients (67.3 ± 13.2 year-old, 69.4% males), of whom 43.6% were non-invasively ventilated and 15.8% invasively. 52 (7.5%) had PE over 15 (9-24) days of follow-up. Compared with those without PE, these subjects had younger age, higher BMI, less often heart failure and chronic kidney disease, more severe cardio-pulmonary involvement, and higher admission D-dimer [4344 (1099-15,118) vs. 818.5 (417-1460) ng/mL, p < 0.001]. They also received more frequently darunavir/ritonavir, tocilizumab and ventilation support. Furthermore, they faced more bleeding episodes requiring transfusion (15.6% vs. 5.1%, p < 0.001) and non-significantly higher in-hospital mortality (34.6% vs. 22.9%, p = 0.06). In multivariate regression, only D-dimer was associated with PE (HR 1.72, 95% CI 1.13-2.62; p = 0.01). The relation between D-dimer concentrations and PE incidence was linear, without inflection point. Only two subjects had a baseline D-dimer < 500 ng/mL. CONCLUSIONS: PE occurs in a sizable proportion of hospitalized COVID-19 patients. The implications of bleeding events and the role of D-dimer in this population need to be clarified.
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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 | 0.016 | 0.269 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| 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".