Observational studyNeurocritical care2022
Predicting Shunt Dependency from the Effect of Cerebrospinal Fluid Drainage on Ventricular Size.
Observational study in Neurocritical care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Early Prediction of External Ventricular Drain Weaning Trial Outcome in Patients with SAH Based on ICP Pulse Morphological Similarity: A Single-Center Retrospective Cohort Analysis.Neurocritical care · 2026Article
- Non-Invasive Brain-Computer Interfaces: Converging Frontiers in Neural Signal Decoding and Flexible Bioelectronics Integration.Nano-micro letters · 2026Review
- Reply to: Ventriculitis incidence and outcomes in patients with aneurysmal subarachnoid hemorrhage: a prospective observational study.Critical care science · 2026Article
- Predictive factors for shunt dependency in patients with spontaneous intraventricular hemorrhage.Scientific reports · 2024Article
- Early prediction of ventricular peritoneal shunt dependency in aneurysmal subarachnoid haemorrhage patients by recurrent neural network-based machine learning using routine intensive care unit data.Journal of clinical monitoring and computing · 2024Article
- Predictors of shunt insertion in patients with aneurysmal subarachnoid haemorrhage-a single-centre retrospective analysis.Acta neurochirurgica · 2024Article
- The value of ventricular measurements in the prediction of shunt dependency after aneurysmal subarachnoid hemorrhage.Acta neurochirurgica · 2023Article
- Morphometric Study of the Initial Ventricular Indices to Predict the Complications and Outcome of Aneurysmal Subarachnoid Hemorrhage.Journal of clinical medicine · 2023Article
- Navigating the Ocean of Big Data in Neurocritical Care.Neurocritical care · 2022Article
Corrections and comments
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Authors and funding
16 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundProlonged external ventricular drainage (EVD) in patients with subarachnoid hemorrhage (SAH) leads to morbidity, whereas early removal can have untoward effects related to recurrent hydrocephalus. A metric to help determine the optimal time for EVD removal or ventriculoperitoneal shunt (VPS) placement would be beneficial in preventing the prolonged, unnecessary use of EVD. This study aimed to identify whether dynamics of cerebrospinal fluid (CSF) biometrics can temporally predict VPS dependency after SAH.
methodsThis was a retrospective analysis of a prospective, single-center, observational study of patients with aneurysmal SAH who required EVD placement for hydrocephalus. Patients were divided into VPS-dependent (VPS+) and non-VPS dependent groups. We measured the bicaudate index (BCI) on all available computed tomography scans and calculated the change over time (ΔBCI). We analyzed the relationship of ΔBCI with CSF output by using Pearson's correlation. A k-nearest neighbor model of the relationship between ΔBCI and CSF output was computed to classify VPS.
resultsFifty-eight patients met inclusion criteria. CSF output was significantly higher in the VPS+ group in the 7 days post EVD placement. There was a negative correlation between delta BCI and CSF output in the VPS+ group (negative delta BCI means ventricles become smaller) and a positive correlation in the VPS- group starting from days four to six after EVD placement (p < 0.05). A weighted k-nearest neighbor model for classification had a sensitivity of 0.75, a specificity of 0.70, and an area under the receiver operating characteristic curve of 0.80.
conclusionsThe correlation of ΔBCI and CSF output is a reliable intraindividual biometric for VPS dependency after SAH as early as days four to six after EVD placement. Our machine learning model leverages this relationship between ΔBCI and cumulative CSF output to predict VPS dependency. Early knowledge of VPS dependency could be studied to reduce EVD duration in many centers (intensive care unit length of stay).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.