Literature DB >> 26428322

Predictors of Shunt-Dependent Hydrocephalus Following Aneurysmal Subarachnoid Hemorrhage.

Michael K Tso1, George M Ibrahim1, R Loch Macdonald2.   

Abstract

BACKGROUND: Shunt-dependent hydrocephalus is a common complication of aneurysmal subarachnoid hemorrhage (aSAH). There is a need to identify patients who require ventriculoperitoneal shunt (VPS) insertion so that any modifiable risk factors can be addressed early after aSAH.
METHODS: Exploratory analysis was performed on 413 patients enrolled in CONSCIOUS-1, a prospective randomized controlled trial of patients with aSAH treated with clazosentan. The association between clinical and neuroimaging covariates and VPS placement was first determined by univariate analysis. Covariates with P < 0.15 on univariate analysis were then analyzed in a multivariate logistic regression model. Receiver operating characteristic curve analysis was used to define optimal predictive thresholds. The published literature was reviewed to determine the overall rate of VPS insertion after aSAH.
RESULTS: Overall, 17.2% (71/413) of patients required VPS insertion. Multivariate analysis demonstrated that insertion of an external ventricular drain (odds ratio, 6.21; 95% confidence interval, 2.51-16.91) and increasing volume of cerebrospinal fluid (CSF) drainage per day (odds ratio, 1.004; 95% confidence interval, 1.000-1.009) were associated with VPS insertion. Receiver operating characteristic curve analysis revealed an optimal daily CSF output threshold of 78 mL was predictive of VPS insertion. Among 41,789 patients with aSAH from 66 published studies, the overall VPS insertion rate was 12.7%.
CONCLUSIONS: The presence of an external ventricular drain and increased daily CSF output (above 78 mL/day) seems to be predictive of subsequent VPS insertion after aSAH. Although we could not identify modifiable risk factors for needing a VPS, nevertheless, these findings identify patients at greatest risk of VPS placement and inform treatment decisions as well as patient expectations.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Hydrocephalus; Multivariate analysis; Risk factors; Shunt; Subarachnoid hemorrhage

Mesh:

Substances:

Year:  2015        PMID: 26428322     DOI: 10.1016/j.wneu.2015.09.056

Source DB:  PubMed          Journal:  World Neurosurg        ISSN: 1878-8750            Impact factor:   2.104


  11 in total

Review 1.  Effect of the drainage of cerebrospinal fluid in patients with aneurismal subarachnoid hemorrhage: A meta-analysis.

Authors:  Cong Qian; Xiaobo Yu; Jingyin Chen; Chi Gu; Lin Wang; Gao Chen; Yuying Dai
Journal:  Medicine (Baltimore)       Date:  2016-10       Impact factor: 1.889

2.  The effect of fenestration of the lamina terminalis on the incidence of shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage (FISH): Study protocol for a randomized controlled trial.

Authors:  Chuanyuan Tao; Chaofeng Fan; Xin Hu; Junpeng Ma; Lu Ma; Hao Li; Yi Liu; Hong Sun; Min He; Chao You
Journal:  Medicine (Baltimore)       Date:  2016-12       Impact factor: 1.889

3.  Early variations of laboratory parameters predicting shunt-dependent hydrocephalus after subarachnoid hemorrhage.

Authors:  Min Kyun Na; Yu Deok Won; Choong Hyun Kim; Jae Min Kim; Jin Hwan Cheong; Je Il Ryu; Myung-Hoon Han
Journal:  PLoS One       Date:  2017-12-12       Impact factor: 3.240

Review 4.  Hydrocephalus after Subarachnoid Hemorrhage: Pathophysiology, Diagnosis, and Treatment.

Authors:  Sheng Chen; Jinqi Luo; Cesar Reis; Anatol Manaenko; Jianmin Zhang
Journal:  Biomed Res Int       Date:  2017-03-08       Impact factor: 3.411

5.  Risk Factors and Preoperative Risk Scoring System for Shunt-Dependent Hydrocephalus Following Aneurysmal Subarachnoid Hemorrhage.

Authors:  Joo Hyun Kim; Jae Hoon Kim; Hee In Kang; Deok Ryeong Kim; Byung Gwan Moon; Joo Seung Kim
Journal:  J Korean Neurosurg Soc       Date:  2019-05-08

6.  Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage.

Authors:  Giovanni Muscas; Tommaso Matteuzzi; Eleonora Becattini; Simone Orlandini; Francesca Battista; Antonio Laiso; Sergio Nappini; Nicola Limbucci; Leonardo Renieri; Biagio R Carangelo; Salvatore Mangiafico; Alessandro Della Puppa
Journal:  Acta Neurochir (Wien)       Date:  2020-07-08       Impact factor: 2.216

Review 7.  The Pathogenesis of Hydrocephalus Following Aneurysmal Subarachnoid Hemorrhage.

Authors:  Lu-Ting Kuo; Abel Po-Hao Huang
Journal:  Int J Mol Sci       Date:  2021-05-10       Impact factor: 5.923

8.  Age-specific global epidemiology of hydrocephalus: Systematic review, metanalysis and global birth surveillance.

Authors:  Albert M Isaacs; Jay Riva-Cambrin; Daniel Yavin; Aaron Hockley; Tamara M Pringsheim; Nathalie Jette; Brendan Cord Lethebe; Mark Lowerison; Jarred Dronyk; Mark G Hamilton
Journal:  PLoS One       Date:  2018-10-01       Impact factor: 3.240

9.  Review of CHESS Score in SAH Patients in Local Malaysian Population.

Authors:  Sze-Voon Yee; Abdul Rahman Ghani; Azman Raffiq
Journal:  J Neurosci Rural Pract       Date:  2020-03-03

Review 10.  Lessons from the CONSCIOUS-1 Study.

Authors:  Alexander J Schupper; Matthew E Eagles; Sean N Neifert; J Mocco; R Loch Macdonald
Journal:  J Clin Med       Date:  2020-09-14       Impact factor: 4.241

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