Shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage: incidence, predictors, and revision rates
Bibliographic record
Abstract
OBJECT: Chronic shunt-dependent hydrocephalus is a recognized complication of aneurysmal subarachnoid hemorrhage. While its incidence and risk factors have been well described, the long-term performance of shunts in this setting has not been not widely reported. METHODS: Using administrative databases, the authors derived a retrospective cohort of patients undergoing treatment of a ruptured aneurysm in Ontario, Canada, between 1995 and 2005. The authors determined the incidence of shunt-dependent hydrocephalus and analyzed putative risk factors. Mortality rates and indicators of morbidity were recorded. Patients were followed up for the occurrence of shunt failure over time. RESULTS: Of 3120 patients in the cohort, 585 (18.75%) developed shunt-dependent hydrocephalus. On multivariate analysis, age, acute hydrocephalus, ventilation on admission, aneurysms in the posterior circulation and giant aneurysms were all significant predictors of shunt-dependent hydrocephalus. The mortality rate was not increased in patients with chronic hydrocephalus (hazard ratio 1.04, p = 0.63); however, indicators of morbidity were increased in these patients. Of the 585 patients with shunt-dependent hydrocephalus, only 173 (29.6%) underwent a subsequent revision procedure. Ninety-eight percent of these revisions were completed within 6 months. Subsequent revisions occurred more frequently. On multivariate analysis, significant predictors of shunt revision included aneurysm location in the posterior circulation and endovascular treatment of the initial ruptured aneurysm. CONCLUSIONS: Shunt-dependent hydrocephalus affects a significant proportion of subarachnoid hemorrhage survivors, contributing to additional morbidity among these patients. Shunt failures occur less frequently in patients who underwent treatment for a ruptured aneurysm than with other forms of hydrocephalus. Most failures occur within 6 months, suggesting that shunt dependency may be transient in the majority of patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".