Bedside transcranial sonography monitoring in a patient with hydrocephalus post subarachnoid hemorrhage
Bibliographic record
Abstract
BACKGROUND: Development of hydrocephalus can occur after subarachnoid hemorrhage (SAH). Typically, it is diagnosed with computed tomography, CT, scan. However, transcranial sonography (TCS) can be used particularly in patients with craniotomy which removes the acoustic interference of the skull and allows a closer up visualization of brain structures through the skin. CASE PRESENTATION: We report a 73-year-old woman who was hospitalized for SAH and developed acute hydrocephalus requiring an external ventricular drain (EVD). In this patient, detection and monitoring of hydrocephalus was done and monitored with a small pocket-sized TCS device. Nine days after surgery, weaning of the EVD was attempted. Prior to EVD closure and removal, TCS showed a measurement of the 3rd ventricle at around 1.16 cm. On the third day, the patient deteriorated clinically and the TCS showed a dilated 3rd ventricle measuring 1.37 cm which correlated well with computed tomography and with clinical signs of active hydrocephalus as both her sensorium and communication were affected. Subsequently following EVD re-installation, on the next day, TCS showed that the 3rd ventricle dimension was reduced to 0.99 cm and the following day it went down to 0.69 cm. CONCLUSIONS: Patients with SAH and in particular those with a craniotomy can be monitored easily at the bedside with hand-held TCS for the development and monitoring of hydrocephalus.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".