scholarly journals Role of Systemic Inflammatory Response Syndrome in the Occurrence of Delayed Ischemic Neurological Deficits after Aneurysmal Subarachnoid Hemorrhage

2000 ◽  
Vol 28 (4) ◽  
pp. 290-293
Author(s):  
Hideo KIMURA ◽  
Takeo FUKUSHIMA ◽  
Masaaki YAMAMOTO ◽  
Syuji HAYASHI ◽  
Masamichi TOMONAGA
2019 ◽  
Vol 130 (6) ◽  
pp. 1984-1991 ◽  
Author(s):  
Aaron P. Wessell ◽  
Matthew J. Kole ◽  
Gregory Cannarsa ◽  
Jeffrey Oliver ◽  
Gaurav Jindal ◽  
...  

OBJECTIVEThe authors sought to evaluate whether a sustained systemic inflammatory response was associated with shunt-dependent hydrocephalus following aneurysmal subarachnoid hemorrhage.METHODSA retrospective analysis of 193 consecutive patients with aneurysmal subarachnoid hemorrhage was performed. Management of hydrocephalus followed a stepwise algorithm to determine the need for external CSF drainage and subsequent shunt placement. Systemic inflammatory response syndrome (SIRS) data were collected for all patients during the first 7 days of hospitalization. Patients who met the SIRS criteria every day for the first 7 days of hospitalization were considered as having a sustained SIRS. Univariate and multivariate regression analyses were used to determine predictors of shunt dependence.RESULTSSixteen percent of patients required shunt placement. Sustained SIRS was observed in 35% of shunt-dependent patients compared to 14% in non–shunt-dependent patients (p = 0.004). On multivariate logistic regression, female sex (OR 0.35, 95% CI 0.142–0.885), moderate to severe vasospasm (OR 3.78, 95% CI 1.333–10.745), acute hydrocephalus (OR 21.39, 95% CI 2.260–202.417), and sustained SIRS (OR 2.94, 95% CI 1.125–7.689) were significantly associated with shunt dependence after aneurysmal subarachnoid hemorrhage. Receiver operating characteristic analysis revealed an area under the curve of 0.83 for the final regression model.CONCLUSIONSSustained SIRS was a predictor of shunt-dependent hydrocephalus following aneurysmal subarachnoid hemorrhage even after adjustment for potential confounding variables in a multivariate logistic regression model.


2003 ◽  
Vol 31 (4) ◽  
pp. 1048-1052 ◽  
Author(s):  
Takeshi Motoyama ◽  
Kazufumi Okamoto ◽  
Ichirou Kukita ◽  
Masamichi Hamaguchi ◽  
Yoshihiro Kinoshita ◽  
...  

2018 ◽  
Vol 46 (12) ◽  
pp. e1152-e1159 ◽  
Author(s):  
Verena Rass ◽  
Max Gaasch ◽  
Mario Kofler ◽  
Alois Josef Schiefecker ◽  
Bogdan-Andrei Ianosi ◽  
...  

2007 ◽  
Vol 22 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Catherine S.C. Bouman ◽  
Heleen M. Oudemans-van Straaten ◽  
Marcus J. Schultz ◽  
Margreeth B. Vroom

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