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

  • Kim, Joo Hyun (Department of Neurosurgery, Eulji University Eulji Hospital) ;
  • Kim, Jae Hoon (Department of Neurosurgery, Eulji University Eulji Hospital) ;
  • Kang, Hee In (Department of Neurosurgery, Eulji University Eulji Hospital) ;
  • Kim, Deok Ryeong (Department of Neurosurgery, Eulji University Eulji Hospital) ;
  • Moon, Byung Gwan (Department of Neurosurgery, Eulji University Eulji Hospital) ;
  • Kim, Joo Seung (Department of Neurosurgery, Eulji University Eulji Hospital)
  • Received : 2018.07.11
  • Accepted : 2018.10.12
  • Published : 2019.11.01

Abstract

Objective : Shunt-dependent hydrocephalus (SdHCP) is a well-known complication of aneurysmal subarachnoid hemorrhage (SAH). The risk factors for SdHCP have been widely investigated, but few risk scoring systems have been established to predict SdHCP. This study was performed to investigate the risk factors for SdHCP and devise a risk scoring system for use before aneurysm obliteration. Methods : We reviewed the data of 301 consecutive patients who underwent aneurysm obliteration following SAH from September 2007 to December 2016. The exclusion criteria for this study were previous aneurysm obliteration, previous major cerebral infarction, the presence of a cavum septum pellucidum, a midline shift of >10 mm on initial computed tomography (CT), and in-hospital mortality. We finally recruited 254 patients and analyzed the following data according to the presence or absence of SdHCP : age, sex, history of hypertension and diabetes mellitus, Hunt-Hess grade, Fisher grade, aneurysm size and location, type of treatment, bicaudate index on initial CT, intraventricular hemorrhage, cerebrospinal fluid drainage, vasospasm, and modified Rankin scale score at discharge. Results : In the multivariate analysis, acute HCP (bicaudate index of ${\geq}0.2$) (odds ratio [OR], 6.749; 95% confidence interval [CI], 2.843-16.021; p=0.000), Fisher grade of 4 (OR, 4.108; 95% CI, 1.044-16.169; p=0.043), and an age of ${\geq}50years$ (OR, 3.938; 95% CI, 1.375-11.275; p=0.011) were significantly associated with the occurrence of SdHCP. The risk scoring system using above parameters of acute HCP, Fisher grade, and age (AFA score) assigned 1 point to each (total score of 0-3 points). SdHCP occurred in 4.3% of patients with a score of 0, 8.5% with a score of 1, 25.5% with a score of 2, and 61.7% with a score of 3 (p=0.000). In the receiver operating characteristic curve analysis, the area under the curve (AUC) for the risk scoring system was 0.820 (p=0.080; 95% CI, 0.750-0.890). In the internal validation of the risk scoring system, the score reliably predicted SdHCP (AUC, 0.895; p=0.000; 95% CI, 0.847-0.943). Conclusion : Our results suggest that the herein-described AFA score is a useful tool for predicting SdHCP before aneurysm obliteration. Prospective validation is needed.

Keywords

References

  1. Adams H, Ban VS, Leinonen V, Aoun SG, Huttunen J, Saavalainen T, et al. : Risk of shunting after aneurysmal subarachnoid hemorrhage: a collaborative study and initiation of a consortium. Stroke 47 : 2488-2496, 2016 https://doi.org/10.1161/STROKEAHA.116.013739
  2. Bae IS, Yi HJ, Choi KS, Chun HJ : Comparison of incidence and risk factors for shunt-dependent hydrocephalus in aneurysmal subarachnoid hemorrhage patients. J Cerebrovasc Endovasc Neurosurg 16 : 78-84, 2014 https://doi.org/10.7461/jcen.2014.16.2.78
  3. Chan M, Alaraj A, Calderon M, Herrera SR, Gao W, Ruland S, et al. : Prediction of ventriculoperitoneal shunt dependency in patients with aneurysmal subarachnoid hemorrhage. J Neurosurg 110 : 44-49, 2009 https://doi.org/10.3171/2008.5.17560
  4. Diesing D, Wolf S, Sommerfeld J, Sarrafzadeh A, Vajkoczy P, Dengler NF : A novel score to predict shunt dependency after aneurysmal subarachnoid hemorrhage. J Neurosurg 128 : 1273-1279, 2018 https://doi.org/10.3171/2016.12.JNS162400
  5. Dorai Z, Hynan LS, Kopitnik TA, Samson D : Factors related to hydrocephalus after aneurysmal subarachnoid hemorrhage. Neurosurgery 52 : 763-769; discussion 769-771, 2003 https://doi.org/10.1227/01.NEU.0000053222.74852.2D
  6. Dupont S, Rabinstein AA : CT evaluation of lateral ventricular dilatation after subarachnoid hemorrhage: baseline bicaudate index values [correction of balues]. Neurol Res 35 : 103-106, 2013 https://doi.org/10.1179/1743132812Y.0000000121
  7. Dupont S, Rabinstein AA : Extent of acute hydrocephalus after subarachnoid hemorrhage as a risk factor for poor functional outcome. Neurol Res 35 : 107-110, 2013 https://doi.org/10.1179/1743132812Y.0000000122
  8. Gao F, Liu F, Chen Z, Hua Y, Keep RF, Xi G : Hydrocephalus after intraventricular hemorrhage: the role of thrombin. J Cereb Blood Flow Metab 34 : 489-494, 2014 https://doi.org/10.1038/jcbfm.2013.225
  9. Jabbarli R, Bohrer AM, Pierscianek D, Muller D, Wrede KH, Dammann P, et al. : The CHESS score: a simple tool for early prediction of shunt dependency after aneurysmal subarachnoid hemorrhage. Eur J Neurol 23 : 912-918, 2016 https://doi.org/10.1111/ene.12962
  10. Johanson CE, Duncan JA 3rd, Klinge PM, Brinker T, Stopa EG, Silverberg GD : Multiplicity of cerebrospinal fluid functions: new challenges in health and disease. Cerebrospinal Fluid Res 5 : 10, 2008 https://doi.org/10.1186/1743-8454-5-10
  11. Li T, Zhang P, Yuan B, Zhao D, Chen Y, Zhang X : Thrombin-induced TGF-${\beta}1$ pathway: a cause of communicating hydrocephalus post subarachnoid hemorrhage. Int J Mol Med 31 : 660-666, 2013 https://doi.org/10.3892/ijmm.2013.1253
  12. Motiei-Langroudi R, Adeeb N, Foreman PM, Harrigan MR, Fisher WS Rd, Vyas NA, et al. : Predictors of shunt insertion in aneurysmal subarachnoid hemorrhage. World Neurosurg 98 : 421-426, 2017 https://doi.org/10.1016/j.wneu.2016.11.092
  13. Nam KH, Hamm IS, Kang DH, Park J, Kim YS : Risk of shunt dependent hydrocephalus after treatment of ruptured intracranial aneurysms : surgical clipping versus endovascular coiling according to Fisher grading system. J Korean Neurosurg Soc 48 : 313-318, 2010 https://doi.org/10.3340/jkns.2010.48.4.313
  14. Pinggera D, Kerschbaumer J, Petr O, Ortler M, Thome C, Freyschlag CF : The volume of the third ventricle as a prognostic marker for shunt dependency after aneurysmal subarachnoid hemorrhage. World Neurosurg 108 : 107-111, 2017 https://doi.org/10.1016/j.wneu.2017.08.129
  15. Rincon F, Gordon E, Starke RM, Buitrago MM, Fernandez A, Schmidt JM, et al. : Predictors of long-term shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage. Clinical article. J Neurosurg 113 : 774-780, 2010 https://doi.org/10.3171/2010.2.JNS09376
  16. Sakka L, Coll G, Chazal J : Anatomy and physiology of cerebrospinal fluid. Eur Ann Otorhinolaryngol Head Neck Dis 128 : 309-316, 2011 https://doi.org/10.1016/j.anorl.2011.03.002
  17. Tso MK, Ibrahim GM, Macdonald RL : Predictors of shunt-dependent hydrocephalus following aneurysmal subarachnoid hemorrhage. World Neurosurg 86 : 226-232, 2016 https://doi.org/10.1016/j.wneu.2015.09.056
  18. Wilson CD, Safavi-Abbasi S, Sun H, Kalani MY, Zhao YD, Levitt MR, et al. : Meta-analysis and systematic review of risk factors for shunt dependency after aneurysmal subarachnoid hemorrhage. J Neurosurg 126 : 586-595, 2017 https://doi.org/10.3171/2015.11.JNS152094
  19. Wilson DA, Nakaji P, Abla AA, Uschold TD, Fusco DJ, Oppenlander ME, et al. : A simple and quantitative method to predict symptomatic vasospasm after subarachnoid hemorrhage based on computed tomography: beyond the Fisher scale. Neurosurgery 71 : 869-875, 2012 https://doi.org/10.1227/NEU.0b013e318267360f
  20. Woernle CM, Winkler KM, Burkhardt JK, Haile SR, Bellut D, Neidert MC, et al. : Hydrocephalus in 389 patients with aneurysm-associated subarachnoid hemorrhage. J Clin Neurosci 20 : 824-826, 2013 https://doi.org/10.1016/j.jocn.2012.07.015
  21. Xie Z, Hu X, Zan X, Lin S, Li H, You C : Predictors of shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage? A systematic review and meta-analysis. World Neurosurg 106 : 844-860.e6, 2017 https://doi.org/10.1016/j.wneu.2017.06.119
  22. Yamada S, Nakase H, Park YS, Nishimura F, Nakagawa I : Discriminant analysis prediction of the need for ventriculoperitoneal shunt after subarachnoid hemorrhage. J Stroke Cerebrovasc Dis 21 : 493-497, 2012 https://doi.org/10.1016/j.jstrokecerebrovasdis.2010.11.010
  23. Zaidi HA, Montoure A, Elhadi A, Nakaji P, McDougall CG, Albuquerque FC, et al. : Long-term functional outcomes and predictors of shuntdependent hydrocephalus after treatment of ruptured intracranial aneurysms in the BRAT trial: revisiting the clip vs coil debate. Neurosurgery 76 : 608-613; discussion 613-614; quiz 614, 2015 https://doi.org/10.1227/NEU.0000000000000677

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