Sensitivity of cerebral blood flow and oxygenation to high-intracranial pressure
Bibliographic record
Abstract
Intraventricular hemorrhage (IVH) is a common occurrence in preterm infants born with very low birth weights, often leading to hydrocephalus. Hydrocephalus is an abnormal accumulation of cerebral spinal fluid (CSF) in the brain that can cause high intracranial pressure (ICP) and subsequent brain injuries. Unfortunately, current neuromonitoring techniques, such as ultrasonography, can only detect injuries that have already occurred. This emphasizes the need for tools that can identify indicators of brain insult prior to the injury. This study aimed to investigate whether cerebral blood flow (CBF) and oxygenation are sensitive to elevated ICP. Experiments were conducted on five newborn piglets, comprised by an experimental (n = 3) and a control group (n = 2). ICP was increased in the experimental group by continuous infusion of saline into the lumbar CSF region. CBF, deoxy- and oxy-hemoglobin (Hb and HbO2) were continuously measured, starting 10 min before infusion and throughout the saline infusion, using a hybrid optical device that combines continuous-wave hyperspectral near infrared spectroscopy (h-NIRS) and diffuse correlation spectroscopy (DCS). Changes in CBF, Hb, and HbO2 were computed using methods reported in our previous works. The results revealed that when ICP increases, Hb increases while HbO2 and CBF decrease. Notably, there was a strong positive correlation between Hb and ICP and a negative correlation between HbO2, CBF, and ICP (p<0.05). These findings suggest that CBF, Hb, and HbO2 are sensitive to increased ICP and could be used to detect hydrocephalus-induced high ICP.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".