From cellular function to global impact: the vascular perspective on COVID-19
Bibliographic record
Abstract
Since COVID-19 was declared a pandemic a year ago, our understanding of its effects on the vascular system has slowly evolved. At the cellular level, SARS-CoV-2 - the virus that causes COVID-19 - accesses the vascular endothelium through the angiotensin-converting enzyme 2 (ACE-2) receptor and induces proinflammatory and prothrombotic responses. At the clinical level, these pathways lead to thromboembolic events that affect the pulmonary, extracranial, mesenteric, and lower extremity vessels. At the population level, the presence of vascular risk factors predisposes individuals to more severe forms of COVID-19, whereas the absence of vascular risk factors does not spare patients with COVID-19 from unprecedented rates of stroke, pulmonary embolism and acute limb ischemia. Finally, at the community and global level, the fear of COVID-19, measures taken to limit the spread of SARS-CoV-2 and reallocation of limited hospital resources have led to delayed presentations of severe forms of ischemia, surgery cancellations and missed opportunities for limb salvage. The purpose of this narrative review is to present some of the data on COVID-19, from cellular mechanisms to clinical manifestations, and discuss its impact on the local and global surgical communities from a vascular perspective.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".