The Incidence of Pulmonary Embolism in Hospitalized Non-ICU Patients with COVID-19 during the First Wave: A Multicenter Retrospective Cohort Study in the Netherlands
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: During the first COVID-19 outbreak in 2020 in the Netherlands, the incidence of pulmonary embolism (PE) appeared to be high in COVID-19 patients admitted to the intensive care unit (ICU). This study was performed to evaluate the incidence of PE during hospital stay in COVID-19 patients not admitted to the ICU. METHODS: Data were retrospectively collected from 8 hospitals in the Netherlands. Patients admitted between February 27, 2020, and July 31, 2020, were included. Data extracted comprised clinical characteristics, medication use, first onset of COVID-19-related symptoms, admission date due to COVID-19, and date of PE diagnosis. Only polymerase chain reaction (PCR)-positive patients were included. All PEs were diagnosed with computed tomography pulmonary angiography (CTPA). RESULTS: Data from 1,852 patients who were admitted to the hospital ward were collected. Forty patients (2.2%) were diagnosed with PE within 28 days following hospital admission. The median time to PE since admission was 4.5 days (IQR 0.0-9.0). In all 40 patients, PE was diagnosed within the first 2 weeks after hospital admission and for 22 (55%) patients within 2 weeks after onset of symptoms. Patient characteristics, pre-existing comorbidities, anticoagulant use, and laboratory parameters at admission were not related to the development of PE. CONCLUSION: In this retrospective multicenter cohort study of 1,852 COVID-19 patients only admitted to the non-ICU wards, the incidence of CTPA-confirmed PE was 2.2% during the first 4 weeks after onset of symptoms and occurred exclusively within 2 weeks after hospital admission.
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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 | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it