Impact of acute hydrocephalus after aneurysmal SAH on longitudinal cognitive outcome- post-hoc analysis of the MoCA-DCI study.
Bibliographic record
Abstract
Hydrocephalus is a common complication following aneurysmal subarachnoid hemorrhage (aSAH), associated with increased morbidity and mortality. While its immediate negative impact on cognitive function is well-known, the longitudinal effects, especially in lower-grade aSAH patients, remain unclear. This study aimed to assess these effects. Within the prospective, multicenter "MoCA-DCI study" (ClinicalTrials.gov NCT03032471), patients with a GCS of 13-15 < 72 h post-aSAH underwent serial neuropsychological assessments using the Montreal Cognitive Assessment (MoCA) at baseline (< 72 h post-aSAH), around discharge (14-28 days post-aSAH), and at 3-month follow-up. Standardized MoCA scores were compared to evaluate cognitive outcomes, and the likelihood of a clinically meaningful decline (≥ 2 points) was assessed in patients with and without hydrocephalus. We included 112 patients, mean age 53.9 years (SD 13.9), 66.1% female. Forty patients (35.7%) developed acute hydrocephalus and received external ventricular drainage; 10 of these (25%) required a ventriculo-peritoneal shunt. MoCA z-scores were significantly lower in the hydrocephalus group at baseline (-2.84 vs. -1.12, p < 0.001), at discharge (-3.35 vs. 0.53, p < 0.001), and at 3 months (-0.68 vs. 0.07, p = 0.02). Patients with hydrocephalus were more likely to experience a ≥ 2-point decline from baseline at discharge (OR 2.76, 95% CI 1.16-6.53; p = 0.02) but not at the 3-month follow-up (OR 1.22, 95% CI 0.32-4.62; p = 0.77). Acute hydrocephalus has a negative impact on longitudinal neurocognitive function, yet patients demonstrate improvements until 3-month follow-up. The impairment of cognitive function may be partially recovered as cerebrospinal fluid flow is restored or permanently diverted.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".