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Radiological Estimation of Intracranial Blood Volume and Occurrence of Hydrocephalus Determines Stress-Induced Hyperglycemia After Aneurysmal Subarachnoid Hemorrhage

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Abstract

Acute phase after aneurysmal subarachnoid hemorrhage (aSAH) is associated with several metabolic derangements including stress-induced hyperglycemia (SIH). The present study is designed to identify objective radiological determinants for SIH to better understand its contributory role in clinical outcomes after aSAH. A computer-aided detection tool was used to segment admission computed tomography (CT) images of aSAH patients to estimate intracranial blood and cerebrospinal fluid volumes. Modified Graeb score (mGS) was used as a semi-quantitative measure to estimate degree of hydrocephalus. The relationship between glycemic gap (GG) determined SIH, mGS, and estimated intracranial blood and cerebrospinal fluid volumes were evaluated using linear regression. Ninety-four [94/187 (50.3%)] among the study cohort had SIH (defined as GG > 26.7 mg/dl). Patients with SIH had 14.3 ml/1000 ml more intracranial blood volume as compared to those without SIH [39.6 ml (95% confidence interval, CI, 33.6 to 45.5) vs. 25.3 ml (95% CI 20.6 to 29.9), p = 0.0002]. Linear regression analysis of mGS with GG showed each unit increase in mGS resulted in 1.2 mg/dl increase in GG [p = 0.002]. Patients with SIH had higher mGS [median 4.0, interquartile range, IQR 2.0–7.0] as compared to those without SIH [median 2.0, IQR 0.0–6.0], p = 0.002. Patients with third ventricular blood on admission CT scan were more likely to develop SIH [67/118 (56.8%) vs. 27/69 (39.1%), p = 0.023]. Hence, the present study, using unbiased SIH definition and objective CT scan parameters, reports “dose-dependent” radiological features resulting in SIH. Such findings allude to a brain injury-stress response-neuroendocrine axis in etiopathogenesis of SIH.

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Abbreviations

ANOVA:

Analysis of variance

AG:

Admission glucose

aSAH:

Aneurysmal subarachnoid hemorrhage

AUROC:

Area under receiver operator characteristic

BCI:

Bicaudate index

CAD:

Computer-aided detection

CI:

Confidence interval

CSF:

Cerebrospinal fluid

CT:

Computed tomography

DCI:

Delayed cerebral ischemia

EVD:

External ventricular drain

GG:

Glycemic gap

GUI:

Graphic user interface

HbA1c:

Glycated hemoglobin

H&H:

Hunt and Hess

HU:

Hounsfield unit

IQR:

Interquartile range

mFS:

Modified Fisher score

mGS:

Modified Graeb score

NSICU:

Neurosciences intensive care unit

ROC:

Receiver operating characteristic

SAH:

Subarachnoid hemorrhage

SIH:

Stress-induced hyperglycemia

TH:

Threshold Hounsfield

VPS:

Ventriculoperitoneal shunt

WFNS:

World Federation of Neurological Surgeons

References

  1. Kruyt ND, Musters A, Biessels GJ, Devries JH, Coert BA, Vergouwen MD, et al. Beta-cell dysfunction and insulin resistance after subarachnoid haemorrhage. Neuroendocrinology. 2011;93(2):126–32. https://doi.org/10.1159/000324097.

    Article  CAS  PubMed  Google Scholar 

  2. Kruyt ND, Biessels GJ, DeVries JH, Luitse MJ, Vermeulen M, Rinkel GJ, et al. Hyperglycemia in aneurysmal subarachnoid hemorrhage: a potentially modifiable risk factor for poor outcome. J Cereb Blood Flow Metab. 2010;30(9):1577–87. https://doi.org/10.1038/jcbfm.2010.102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Kruyt ND, Roos YW, Dorhout Mees SM, van den Bergh WM, Algra A, Rinkel GJ, et al. High mean fasting glucose levels independently predict poor outcome and delayed cerebral ischaemia after aneurysmal subarachnoid haemorrhage. J Neurol Neurosurg Psychiatry. 2008;79(12):1382–5. https://doi.org/10.1136/jnnp.2007.142034.

    Article  CAS  PubMed  Google Scholar 

  4. Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. Translating the A1C assay into estimated average glucose values. Diabetes Care. 2008;31(8):1473–8. https://doi.org/10.2337/dc08-0545.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Liao WI, Sheu WH, Chang WC, Hsu CW, Chen YL, Tsai SH. An elevated gap between admission and A1C-derived average glucose levels is associated with adverse outcomes in diabetic patients with pyogenic liver abscess. PLoS One. 2013;8(5):e64476. https://doi.org/10.1371/journal.pone.0064476.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Liao WI, Wang JC, Chang WC, Hsu CW, Chu CM, Tsai SH. Usefulness of glycemic gap to predict ICU mortality in critically ill patients with diabetes. Medicine (Baltimore). 2015;94(36):e1525. https://doi.org/10.1097/md.0000000000001525.

    Article  CAS  Google Scholar 

  7. Ray B, Ludwig A, Yearout LK, Thompson DM, Bohnstedt BN. Stress-induced hyperglycemia after spontaneous subarachnoid hemorrhage and its role in predicting cerebrospinal fluid diversion. World neurosurgery. 2017;100:208–15. https://doi.org/10.1016/j.wneu.2017.01.008.

    Article  PubMed  Google Scholar 

  8. Ko SB, Choi HA, Carpenter AM, Helbok R, Schmidt JM, Badjatia N, et al. Quantitative analysis of hemorrhage volume for predicting delayed cerebral ischemia after subarachnoid hemorrhage. Stroke. 2011;42(3):669–74. https://doi.org/10.1161/strokeaha.110.600775.

    Article  PubMed  Google Scholar 

  9. Jimenez-Roldan L, Alen JF, Gomez PA, Lobato RD, Ramos A, Munarriz PM, et al. Volumetric analysis of subarachnoid hemorrhage: assessment of the reliability of two computerized methods and their comparison with other radiographic scales. J Neurosurg. 2013;118(1):84–93. https://doi.org/10.3171/2012.8.jns12100.

    Article  PubMed  Google Scholar 

  10. Cortnum S, Sorensen P, Jorgensen J. Determining the sensitivity of computed tomography scanning in early detection of subarachnoid hemorrhage. Neurosurgery. 2010;66(5):900–2; discussion 3. https://doi.org/10.1227/01.Neu.0000367722.66098.21.

    Article  PubMed  Google Scholar 

  11. Morgan TC, Dawson J, Spengler D, Lees KR, Aldrich C, Mishra NK et al. The Modified Graeb score. An enhanced tool for intraventricular hemorrhage measurement and prediction of functional outcome. 2013;44(3):635–641. doi:https://doi.org/10.1161/strokeaha.112.670653.

  12. van Gijn J, Hijdra A, Wijdicks EF, Vermeulen M, van Crevel H. Acute hydrocephalus after aneurysmal subarachnoid hemorrhage. J Neurosurg. 1985;63(3):355–62. https://doi.org/10.3171/jns.1985.63.3.0355.

    Article  PubMed  Google Scholar 

  13. 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. J Neurosurg. 2010;113(4):774–80. https://doi.org/10.3171/2010.2.JNS09376

    Article  PubMed  Google Scholar 

  14. Bian L, Liu L, Wang C, Hussain M, Yuan Y, Liu G, et al. Hyperglycemia within day 14 of aneurysmal subarachnoid hemorrhage predicts 1-year mortality. Clin Neurol Neurosurg. 2013;115(7):959–64. https://doi.org/10.1016/j.clineuro.2012.09.026.

    Article  PubMed  Google Scholar 

  15. Deo RC. Machine learning in medicine. Circulation. 2015;132(20):1920–30. https://doi.org/10.1161/circulationaha.115.001593.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Poulymenopoulou M, Malamateniou F, Vassilacopoulos G. Machine learning for knowledge Extraction from PHR big data. Stud Health Technol Inform. 2014;202:36–9.

    PubMed  Google Scholar 

  17. Roos YB, de Haan RJ, Beenen LF, Groen RJ, Albrecht KW, Vermeulen M. Complications and outcome in patients with aneurysmal subarachnoid haemorrhage: a prospective hospital based cohort study in the Netherlands. J Neurol Neurosurg Psychiatry. 2000;68(3):337–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Hijdra A, Van Gijn J, Stefanko S, Van Dongen KJ, Vermeulen M, Van Crevel H. Delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: clinicoanatomic correlations. Neurology. 1986;36(3):329–33.

    Article  CAS  PubMed  Google Scholar 

  19. Vergouwen MD, Vermeulen M, van Gijn J, Rinkel GJ, Wijdicks EF, Muizelaar JP, et al. Definition of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage as an outcome event in clinical trials and observational studies: proposal of a multidisciplinary research group. Stroke. 2010;41(10):2391–5. https://doi.org/10.1161/strokeaha.110.589275.

    Article  PubMed  Google Scholar 

  20. Alberti O, Becker R, Benes L, Wallenfang T, Bertalanffy H. Initial hyperglycemia as an indicator of severity of the ictus in poor-grade patients with spontaneous subarachnoid hemorrhage. Clin Neurol Neurosurg. 2000;102(2):78–83.

    Article  CAS  PubMed  Google Scholar 

  21. Vergouwen MD, van Geloven N, de Haan RJ, Kruyt ND, Vermeulen M, Roos YB. Increased cortisol levels are associated with delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Neurocrit Care. 2010;12(3):342–5. https://doi.org/10.1007/s12028-010-9331-8.

    Article  CAS  PubMed  Google Scholar 

  22. Schwartz MW, Porte D, Jr. Diabetes, obesity, and the brain. Science 2005;307(5708):375–379. doi:https://doi.org/10.1126/science.1104344.

  23. Obici S, Zhang BB, Karkanias G, Rossetti L. Hypothalamic insulin signaling is required for inhibition of glucose production. Nat Med. 2002;8(12):1376–82. https://doi.org/10.1038/nm798.

    Article  CAS  PubMed  Google Scholar 

  24. Wang YM, Lin YJ, Chuang MJ, Lee TH, Tsai NW, Cheng BC, et al. Predictors and outcomes of shunt-dependent hydrocephalus in patients with aneurysmal sub-arachnoid hemorrhage. BMC Surg. 2012;12:12. https://doi.org/10.1186/1471-2482-12-12.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Lai L, Morgan MK. Predictors of in-hospital shunt-dependent hydrocephalus following rupture of cerebral aneurysms. J Clin Neurosci. 2013;20(8):1134–8. https://doi.org/10.1016/j.jocn.2012.09.033.

    Article  PubMed  Google Scholar 

  26. Appelboom G, Piazza MA, Hwang BY, Carpenter A, Bruce SS, Mayer S, et al. Severity of intraventricular extension correlates with level of admission glucose after intracerebral hemorrhage. Stroke. 2011;42(7):1883–8. https://doi.org/10.1161/strokeaha.110.608166.

    Article  PubMed  Google Scholar 

  27. Dumont T, Rughani A, Silver J, Tranmer BI. Diabetes mellitus increases risk of vasospasm following aneurysmal subarachnoid hemorrhage independent of glycemic control. Neurocrit Care. 2009;11(2):183–9. https://doi.org/10.1007/s12028-009-9232-x.

    Article  PubMed  Google Scholar 

  28. Ferguson S, Macdonald RL. Predictors of cerebral infarction in patients with aneurysmal subarachnoid hemorrhage. Neurosurgery. 2007;60(4):658–67; discussion 67. https://doi.org/10.1227/01.Neu.0000255396.23280.31.

    Article  PubMed  Google Scholar 

  29. de Rooij NK, Rinkel GJ, Dankbaar JW, Frijns CJ. Delayed cerebral ischemia after subarachnoid hemorrhage: a systematic review of clinical, laboratory, and radiological predictors. Stroke. 2013;44(1):43–54. https://doi.org/10.1161/strokeaha.112.674291.

    Article  PubMed  Google Scholar 

  30. Schlenk F, Vajkoczy P, Sarrafzadeh A. Inpatient hyperglycemia following aneurysmal subarachnoid hemorrhage: relation to cerebral metabolism and outcome. Neurocrit Care. 2009;11(1):56–63. https://doi.org/10.1007/s12028-009-9222-z.

    Article  CAS  PubMed  Google Scholar 

  31. Beseoglu K, Steiger HJ. Elevated glycated hemoglobin level and hyperglycemia after aneurysmal subarachnoid hemorrhage. Clin Neurol Neurosurg. 2017;163:128–32. https://doi.org/10.1016/j.clineuro.2017.10.037.

    Article  PubMed  Google Scholar 

  32. Juvela S, Siironen J, Kuhmonen J. Hyperglycemia, excess weight, and history of hypertension as risk factors for poor outcome and cerebral infarction after aneurysmal subarachnoid hemorrhage. J Neurosurg. 2005;102(6):998–1003. https://doi.org/10.3171/jns.2005.102.6.0998.

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors would like to thank Blair Apple, BS, and Brittany Karfonta, BS, with Clinical Studies Unit in Department of Neurology, Oklahoma University Health Sciences Center for their support in data management of the present study.

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Authors and Affiliations

  1. Division of Critical Care Neurology, Department of Neurology, College of Medicine, The University of Oklahoma Health Sciences Center, 920 Stanton L Young Blvd; Ste 2040, Oklahoma City, OK, 73104, USA

    Joshua A Santucci, Stephen R Ross, John C Greenert & Bappaditya Ray

  2. Electrical Engineering, University of Oklahoma, Norman, OK, USA

    Faranak Aghaei & Bin Zheng

  3. Epidemiology and Biostatistics, College of Public Health, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

    Lance Ford & Kimberly M Hollabaugh

  4. Radiology, College of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

    Benjamin O Cornwell & Dee H Wu

  5. Neurosurgery, College of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

    Bradley N Bohnstedt

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  1. Joshua A Santucci
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Correspondence to Bappaditya Ray.

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Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Not applicable due to retrospective nature of the study design.

Electronic supplementary material

Supplementary Figure 1

Segmentation software shows image processing of blood products with intracerebral hemorrhage (a,b), intraventricular hemorrhage (c,d) and subarachnoid hemorrhage (e,f) (PNG 394 kb)

High resolution image (TIF 510 kb)

Supplementary Figure 2

Video shows image analyses software in use (AVI 6125 kb)

Supplementary Figure 3

Linear correlation noted between modified Graeb score with intracranial blood volume (a) and with intracranial blood+CSF volumes (b). (PNG 83 kb)

High resolution image (TIF 118 kb)

Supplementary Figure 4

ROC curves shows AUROC for various parameters determining cohort’s mortality (a) and stress-induced hyperglycemia (b). (PNG 73 kb)

High resolution image (TIF 108 kb)

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Santucci, J.A., Ross, S.R., Greenert, J.C. et al. Radiological Estimation of Intracranial Blood Volume and Occurrence of Hydrocephalus Determines Stress-Induced Hyperglycemia After Aneurysmal Subarachnoid Hemorrhage. Transl. Stroke Res. 10, 327–337 (2019). https://doi.org/10.1007/s12975-018-0646-7

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