Cerebral Hemodynamics and Intracranial Compliance Impairment in Critically Ill COVID-19 Patients: A Pilot Study
Bibliographic record
Abstract
Introduction: One of the possible mechanisms by which the new coronavirus (SARS-Cov2) could induce brain damage is the impairment of cerebrovascular hemodynamics (CVH) and intracranial compliance (ICC) due to the elevation of intracranial pressure (ICP). The main objective of this study was to assess the presence of CVH and ICC alterations in patients with COVID-19 and evaluate their association with short-term clinical outcomes. Methods: Fifty consecutive critically ill COVID-19 patients were studied with transcranial Doppler (TCD) and non-invasive monitoring of ICC. Subjects were included upon ICU admission; CVH was evaluated using mean flow velocities in the middle cerebral arteries (mCBFV), pulsatility index (PI), and estimated cerebral perfusion pressure (eCPP), while ICC was assessed by using the P2/P1 ratio of the non-invasive ICP curve. A CVH/ICC score was computed using all these variables. The primary composite outcome was unsuccessful in weaning from respiratory support or death on day 7 (defined as UO). Results: At the first assessment (n = 50), only the P2/P1 ratio (median 1.20 [IQRs 1.00–1.28] vs. 1.00 [0.88–1.16]; p = 0.03) and eICP (14 [11–25] vs. 11 [7–15] mmHg; p = 0.01) were significantly higher among patients with an unfavorable outcome (UO) than others. Patients with UO had a significantly higher CVH/ICC score (9 [8–12] vs. 6 [5–7]; p < 0.001) than those with a favorable outcome; the area under the receiver operating curve (AUROC) for CVH/ICC score to predict UO was 0.86 (95% CIs 0.75–0.97); a score > 8.5 had 63 (46–77)% sensitivity and 87 (62–97)% specificity to predict UO. For those patients undergoing a second assessment (n = 29), after a median of 11 (5–31) days, all measured variables were similar between the two time-points. No differences in the measured variables between ICU non-survivors (n = 30) and survivors were observed. Conclusions: ICC impairment and CVH disturbances are often present in COVID-19 severe illness and could accurately predict an early poor outcome.
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How this classification was reachedexpand
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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".