Quantification of neurological blood‐based biomarkers in critically ill patients with COVID‐19
Bibliographic record
Abstract
Abstract Background Multiple neurological manifestations of COVID‐19 have been reported such as headache, anosmia, ischemic stroke, and cerebral hemorrhages. Objective characterization of the acute neurological damage in critically ill patients with COVID‐19 has not yet been reported. Method We performed a prospective observational study of plasma brain biomarkers in critically ill patients with respiratory failure that were diagnosed with (COVID‐19) or without (ICU control) COVID‐19. Demographics, co‐morbidities, daily clinical physiologic and laboratory data were collected. Plasma samples were drawn for measurement of neurofilament‐light chain (NF‐L), total tau (t‐tau), ubiquitin carboxy‐terminal hydrolase L1 (UCH‐L1), and glial fibrillary acidic protein (GFAP). The primary neurological outcome was delirium as defined by the intensive care delirium screening checklist (ICDSC, scale 1 ‐ 8). Associations between brain biomarkers and markers of respiratory failure of COVID‐19 were analyzed. Result 27 patients with COVID‐19 and 19 ICU controls were enrolled. The concentration of plasma GFAP, UCH‐L1 and NF‐L levels was higher in both groups compared to healthy controls. Compared to ICU controls, patients with COVID‐19 had significantly higher GFAP (272 [150‐555] pg/ml vs 118 [78.5‐168] pg/ml, p=0.0009). In patients with COVID‐19, GFAP (rho=0.5115, p=0.0064), UCH‐L1 (rho=0.4056, p=0.0358) and NF‐L (rho=0.6223, p=0.0005) were positively correlated with the ICDSC score and were higher in patients diagnosed with delirium (ICDSC ≥4) in the COVID‐19 group but not ICU controls. There were no associations between PaO2/FiO2 or diagnosis of ARDS and plasma concentration of GFAP, t‐tau, UCH‐L1, or NF‐L in patients with COVID‐19. Conclusion Plasma GFAP is 2‐fold higher in critically ill patients with COVID‐19 compared to ICU controls, and higher concentrations of GFAP, UCH‐L1 and NF‐L are associated with delirium specifically in patients with COVID‐19.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".