Endothelial glycocalyx damage in patients with severe COVID-19 on mechanical ventilation – A prospective observational pilot study
Bibliographic record
Abstract
BACKGROUND: Coronavirus disease (COVID-19) associated endotheliopathy and microvascular dysfunction are of concern. OBJECTIVE: The objective of the present single-center observational pilot study was to compare endothelial glycocalyx (EG) damage and endotheliopathy in patients with severe COVID-19 (COVID-19 group) with patients with bacterial pneumonia with septic shock (non-COVID group). METHODS: Biomarkers of EG damage (syndecan-1), endothelial cells (EC) damage (thrombomodulin), and activation (P-selectin) were measured in blood on three consecutive days from admission to the intensive care unit (ICU). The sublingual microcirculation was studied by Side-stream Dark Field (SDF) imaging with automatic assessment. RESULTS: We enrolled 13 patients in the non-COVID group (mean age 70 years, 6 women), and 15 in the COVID-19 group (64 years old, 3 women). The plasma concentrations of syndecan-1 were significantly higher in the COVID-19 group during all three days. Differences regarding other biomarkers were not statistically significant. The assessment of the sublingual microcirculation showed improvement on Day 2 in the COVID-19 group. Plasma levels of C-reactive protein (CRP) were significantly higher on the first two days in the COVID-19 group. Plasma syndecan-1 and CRP were higher in patients suffering from severe COVID-19 pneumonia compared to bacterial pneumonia patients. CONCLUSIONS: These findings support the role of EG injury in the microvascular dysfunction in COVID-19 patients who require ICU.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".