Effect of Cerebral Perfusion Pressure on Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
BACKGROUND: Increased cerebral perfusion pressure (CPP)>70 mmHg has been associated with acute respiratory distress syndrome (ARDS) after traumatic brain injury (TBI). Since this reported association, significant changes in ventilation strategies and fluid management have been accepted as routine critical care. Recently, individualized perfusion targets using autoregulation monitoring suggest CPP titration>70 mmHg. Given these clinical advances, the association between ARDS and increased CPP requires further delineation. OBJECTIVE: To determine the association between ARDS and increased CPP after TBI. METHODS: We conducted a single-center historical cohort study investigating the association of increased CPP and ARDS after TBI. We collected demographic data and physiologic data for CPP, intracranial pressure, mechanical ventilation, cumulative fluid balance and delta/driving pressure (ΔP). We collected outcomes measures pertaining to duration of ventilation, intensive care unit admission length, hospitalization length and 6-month neurological outcome. RESULTS: In total, 113 patients with severe TBI and multimodal neuromonitoring were included. In total, 16 patients (14%) developed ARDS according to the Berlin definition. There was no difference in the mean CPP during the first 7 days of admission between patients who developed ARDS (74 mmHg SD 18 vs. 73 mmHg SD 18, p=0.86) versus those who did not. Patients who developed ARDS had a higher ΔP (15 mmHg [5] vs. 12 mmHg [4], p=0.016) and lower lung compliance (35 ml/cmH2O [10] vs. 49 ml/cmH2O [18], p=0.024) versus those who did not. CONCLUSION: We did not observe an association between increased CPP and ARDS. Patients with ARDS had higher ΔP and lower lung compliance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".