Incidence of acute pulmonary embolism among patients hospitalized with COVID-19: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Coronavirus disease 2019 (COVID-19) is a global pandemic, which is associated with venous thromboembolism and pulmonary embolism (PE). This study aimed to estimate the pooled incidence of PE among patients hospitalized with COVID-19 within the published literature. Methods: This systematic review and meta-analysis was performed according to PRISMA guidelines. An electronic search using MEDLINE /PubMed, ScienceDirect, Cochrane, and OpenGray databases was conducted May 19th, 2020. Eligible studies included sufficient data to calculate the incidence of PE diagnosed during hospitalization in patients with COVID-19. Case reports were excluded. Quality was assessed using the Newcastle-Ottawa scale (observational cohort and case-control), AXIS tool (cross-sectional), and quality assessment tool (case series). Demographics and PE incidence data were extracted from the included studies and analyzed with R language. The pooled incidence of PE in patients hospitalized with COVID-19 was calculated. Results: The database search identified 128 records. Ten observational studies were eligible and were included in the meta-analysis with a total of 1722 patients (mean age= 63.36). .The incidence of PE was noted to be higher in males. The D-dimer levels were specified between PE group and non-PE group in only three studies, while the remaining either reported it improperly or had missing data.The pooled PE incidence in patients hospitalized with COVID-19 was 17% (95% CI: 0.1-0.26). There was a high degree of study heterogeneity (I2 = 94%, p<0.01). Conclusion: The pooled PE incidence in patients hospitalized with COVID-19 is 17%. This increased incidence is greater than that previously reported in the general population of non-COVID-19. Attention and further investigation of this risk is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".