Skip to main content

Advertisement

SpringerLink
Log in

The effect of sex differences on complications and 90-day outcomes after aneurysmal subarachnoid hemorrhage: a propensity score-matched analysis

  • Research
  • Published:
Neurosurgical Review Aims and scope Submit manuscript

Abstract

Aneurysmal subarachnoid hemorrhage (aSAH) is the most devastating form of stroke. Up to now, little is known about the effect of sex differences on complications and outcomes. We retrospectively reviewed aSAH patients admitted to our institution between January 2015 and December 2020. The functional outcomes at discharge and 90 days after discharge were assessed using the modified Rankin Scale (mRS). Baseline characteristics, in-hospital complications, and outcomes were compared after 1:1 propensity score matching (PSM). The area under the curve (AUC) in the receiver operating characteristic curve (ROC) analysis was calculated to measure each independent risk factor’s prediction ability. A total of 833 patients were included. After PSM, 109 male patients were compared with 109 female patients. Female patients had a higher incidence of anemia (47/109 [43.1%] vs. 30/109 [27.5%], p = 0.016) than male patients, while male patients had a higher incidence of pneumonia (36/109 [33.0%] vs. 19/109 [17.4%], p = 0.008) than female patients. No significant differences were found in the rate of unfavorable outcomes at discharge and 90-day outcomes (40/109 [36.7%] vs. 50/109 [45.9%], p = 0.169; 15/109 [13.8%] vs. 19/107 [17.8%], p = 0.420) between female and male patients. Pneumonia (AUC = 0.749, 95% confidence interval [CI] = 0.623–0.875, p < 0.001) and anemia (AUC = 0.753, 95% CI = 0.632–0.873, p = 0.002) showed good ability to predict 90-day unfavorable outcomes in male and female patients, respectively. Female patients had a higher incidence of anemia but a lower incidence of pneumonia during hospitalization. However, differences in in-hospital complications did not result in differences in outcomes between women and men. Clinical Trial Registration: NCT04785976. 2021/03/05, retrospectively registered.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Data availability

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Code availability

N/A.

References

  1. Lovelock CE, Rinkel GJ, Rothwell PM (2010) Time trends in outcome of subarachnoid hemorrhage: Population-based study and systematic review. Neurology 74:1494–1501. https://doi.org/10.1212/WNL.0b013e3181dd42b3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Schatlo B, Fung C, Fathi AR, Sailer M, Winkler K, Daniel RT, Bijlenga P, Ahlborn P, Seule M, Zumofen D, Reinert M, Woernle C, Stienen M, Levivier M, Hildebrandt G, Mariani L, Bernays R, Fandino J, Raabe A, Keller E, Schaller K (2012) Introducing a nationwide registry: the Swiss study on aneurysmal subarachnoid haemorrhage (Swiss SOS). Acta Neurochir (Wien) 154:2173–2178; discussion 2178. https://doi.org/10.1007/s00701-012-1500-4

  3. Duijghuisen JJ, Greebe P, Nieuwkamp DJ, Algra A, Rinkel GJ (2016) Sex-related differences in outcome in patients with aneurysmal subarachnoid hemorrhage. J Stroke Cerebrovasc Dis 25:2067–2070. https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.04.018

    Article  PubMed  Google Scholar 

  4. Hamdan A, Barnes J, Mitchell P (2014) Subarachnoid hemorrhage and the female sex: analysis of risk factors, aneurysm characteristics, and outcomes. J Neurosurg 121:1367–1373. https://doi.org/10.3171/2014.7.JNS132318

    Article  PubMed  Google Scholar 

  5. Kongable GL, Lanzino G, Germanson TP, Truskowski LL, Alves WM, Torner JC, Kassell NF (1996) Gender-related differences in aneurysmal subarachnoid hemorrhage. J Neurosurg 84:43–48. https://doi.org/10.3171/jns.1996.84.1.0043

    Article  CAS  PubMed  Google Scholar 

  6. Nichols L, Stirling C, Otahal P, Stankovich J, Gall S (2018) Socioeconomic disadvantage is associated with a higher incidence of aneurysmal subarachnoid hemorrhage. J Stroke Cerebrovasc Dis 27:660–668. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.09.055

    Article  PubMed  Google Scholar 

  7. Rehman S, Chandra R, Zhou K, Tan D, Lai L, Asadi H, Froelich J, Thani N, Nichols L, Blizzard L, Smith K, Thrift A, Stirling C, Callisaya M, Breslin M, Reeves M, Gall S (2020) Sex differences in aneurysmal subarachnoid haemorrhage (aSAH): aneurysm characteristics, neurological complications, and outcome. Acta Neurochir 162:2271–2282. https://doi.org/10.1007/s00701-020-04469-5

    Article  PubMed  Google Scholar 

  8. Wang YX, He J, Zhang L, Li Y, Zhao L, Liu H, Yang L, Zeng XJ, Yang J, Peng GM, Ahuja A, Yang ZH (2016) A higher aneurysmal subarachnoid hemorrhage incidence in women prior to menopause: a retrospective analysis of 4,895 cases from eight hospitals in China. Quant Imaging Med Surg 6:151–156. https://doi.org/10.21037/qims.2016.01.06

    Article  PubMed  PubMed Central  Google Scholar 

  9. Fuentes A, Stone McGuire L, Amin-Hanjani S (2022) Sex Differences in cerebral aneurysms and subarachnoid hemorrhage. Stroke 53:624–633. https://doi.org/10.1161/strokeaha.121.037147

    Article  PubMed  Google Scholar 

  10. Li R, Lin F, Chen Y, Lu J, Han H, Ma L, Zhao Y, Yan D, Li R, Yang J, He S, Li Z, Zhang H, Yuan K, Wang K, Hao Q, Ye X, Wang H, Li H, Zhang L, Shi G, Zhou J, Zhao Y, Zhang Y, Li Y, Wang S, Chen X, Zhao Y (2022) A 90-day prognostic model based on the early brain injury indicators after aneurysmal subarachnoid hemorrhage: the TAPS Score. Transl Stroke Res. https://doi.org/10.1007/s12975-022-01033-4

    Article  PubMed  PubMed Central  Google Scholar 

  11. Li R, Lin F, Chen Y, Lu J, Han H, Yan D, Li R, Yang J, Li Z, Zhang H, Yuan K, Jin Y, Hao Q, Li H, Zhang L, Shi G, Zhou J, Zhao Y, Zhang Y, Li Y, Wang S, Chen X, Zhao Y (2021) In-hospital complication-related risk factors for discharge and 90-day outcomes in patients with aneurysmal subarachnoid hemorrhage after surgical clipping and endovascular coiling: a propensity score-matched analysis. Journal of neurosurgery:1–12. https://doi.org/10.3171/2021.10.Jns211484

  12. Connolly ES Jr, Rabinstein AA, Carhuapoma JR, Derdeyn CP, Dion J, Higashida RT, Hoh BL, Kirkness CJ, Naidech AM, Ogilvy CS, Patel AB, Thompson BG, Vespa P, American Heart Association Stroke C, Council on Cardiovascular Radiology and Intervention, Council on Cardiovascular N, Council on Cardiovascular Surgery and Anesthesia, Council on Clinical C (2012) Guidelines for the management of aneurysmal subarachnoid hemorrhage: a guideline for healthcare professionals from the American Heart Association/american Stroke Association. Stroke 43:1711–1737. https://doi.org/10.1161/STR.0b013e3182587839

    Article  PubMed  Google Scholar 

  13. de Rooij N, Rinkel G, Dankbaar J, Frijns C (2013) Delayed cerebral ischemia after subarachnoid hemorrhage: a systematic review of clinical, laboratory, and radiological predictors. Stroke 44:43–54. https://doi.org/10.1161/strokeaha.112.674291

    Article  PubMed  Google Scholar 

  14. Dhar R, Diringer M (2008) The burden of the systemic inflammatory response predicts vasospasm and outcome after subarachnoid hemorrhage. Neurocrit Care 8:404–412. https://doi.org/10.1007/s12028-008-9054-2

    Article  PubMed  PubMed Central  Google Scholar 

  15. Dorhout Mees SM, van Dijk GW, Algra A, Kempink DR, Rinkel GJ (2003) Glucose levels and outcome after subarachnoid hemorrhage. Neurology 61:1132–1133. https://doi.org/10.1212/01.wnl.0000090466.68866.02

    Article  CAS  PubMed  Google Scholar 

  16. Duan W, Pan Y, Wang C, Wang Y, Zhao X, Wang Y, Liu L, Investigators C (2018) Risk factors and clinical impact of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: analysis from the China National Stroke Registry. Neuroepidemiology 50:128–136. https://doi.org/10.1159/000487325

    Article  PubMed  Google Scholar 

  17. English SW, Chasse M, Turgeon AF, Lauzier F, Griesdale D, Garland A, Fergusson D, Zarychanski R, van Walraven C, Montroy K, Ziegler J, Dupont-Chouinard R, Carignan R, Dhaliwal A, Mallick R, Sinclair J, Boutin A, Pagliarello G, Tinmouth A, McIntyre L, Canadian Critical Care Trials G (2018) Anemia prevalence and incidence and red blood cell transfusion practices in aneurysmal subarachnoid hemorrhage: results of a multicenter cohort study. Crit Care 22:169. https://doi.org/10.1186/s13054-018-2089-7

    Article  PubMed  PubMed Central  Google Scholar 

  18. Germans MR, Jaja BNR, de Oliviera Manoel AL, Cohen AH, Macdonald RL (2018) Sex differences in delayed cerebral ischemia after subarachnoid hemorrhage. J Neurosurg 129:458–464. https://doi.org/10.3171/2017.3.JNS162808

    Article  CAS  PubMed  Google Scholar 

  19. Nieuwkamp DJ, Vaartjes I, Algra A, Bots ML, Rinkel GJ (2013) Age- and gender-specific time trend in risk of death of patients admitted with aneurysmal subarachnoid hemorrhage in the Netherlands. Int J Stroke 8(Suppl A100):90–94. https://doi.org/10.1111/ijs.12006

    Article  PubMed  Google Scholar 

  20. Rehman S, Chandra RV, Zhou K, Tan D, Lai L, Asadi H, Froelich J, Thani N, Nichols L, Blizzard L, Smith K, Thrift AG, Stirling C, Callisaya ML, Breslin M, Reeves MJ, Gall S (2020) Sex differences in aneurysmal subarachnoid haemorrhage (aSAH): aneurysm characteristics, neurological complications, and outcome. Acta Neurochir (Wien) 162:2271–2282. https://doi.org/10.1007/s00701-020-04469-5

    Article  Google Scholar 

  21. Sheehan JP, Polin RS, Sheehan JM, Baskaya MK, Kassell NF (1999) Factors associated with hydrocephalus after aneurysmal subarachnoid hemorrhage. Neurosurgery 45:1120–1127; discussion 1127–1128. https://doi.org/10.1097/00006123-199911000-00021

  22. Yu W (2022) Vasospasm and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: recent advances and future directions in translational research. Transl Stroke Res. https://doi.org/10.1007/s12975-022-01028-1

    Article  PubMed  PubMed Central  Google Scholar 

  23. Wu M, Chen Y, Li Z, Gu H, Yang K, Xiong Y, Wang Y, Wang C (2022) Dysphagia screening and pneumonia after subarachnoid hemorrhage: findings from the Chinese stroke center alliance. CNS Neurosci Ther 28:913–921. https://doi.org/10.1111/cns.13822

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cinotti R, Dordonnat-Moynard A, Feuillet F, Roquilly A, Rondeau N, Lepelletier D, Caillon J, Asseray N, Blanloeil Y, Rozec B, Asehnoune K (2014) Risk factors and pathogens involved in early ventilator-acquired pneumonia in patients with severe subarachnoid hemorrhage. Eur J Clin Microbiol Infect Dis 33:823–830. https://doi.org/10.1007/s10096-013-2020-8

    Article  CAS  PubMed  Google Scholar 

  25. Chen Y, Lian B, Peng L, Ding C, Lin Y, Yu L, Wang D, Kang D (2020) Neutrophil to lymphocyte ratio is a prognosis factor for post-operative pneumonia in aneurysmal subarachnoid hemorrhage patients. Chin Med J 134:682–689. https://doi.org/10.1097/cm9.0000000000001304

    Article  PubMed  PubMed Central  Google Scholar 

  26. Zhang X, Zhang S, Wang C, Liu R, Li A (2022) High neutrophil-to-albumin ratio predicts postoperative pneumonia in aneurysmal subarachnoid hemorrhage. Front Neurol 13:840858. https://doi.org/10.3389/fneur.2022.840858

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ayling OGS, Ibrahim GM, Alotaibi NM (2018) Anemia after aneurysmal subarachnoid hemorrhage is associated with poor outcome and death. Stroke: A J Cereb Circ 49:1859–1865

    Article  Google Scholar 

  28. Asare K (2008) Anemia of critical illness. Pharmacotherapy 28:1267–1282. https://doi.org/10.1592/phco.28.10.1267

    Article  CAS  PubMed  Google Scholar 

  29. Al-Mufti F, Amuluru K, Damodara N, Dodson V, Roh D, Agarwal S, Meyers PM, Connolly ES Jr, Schmidt MJ, Claassen J, Park S (2019) Admission neutrophil-lymphocyte ratio predicts delayed cerebral ischemia following aneurysmal subarachnoid hemorrhage. J Neurointerv Surg 11:1135–1140. https://doi.org/10.1136/neurintsurg-2019-014759

    Article  PubMed  Google Scholar 

  30. Al-Mufti F, Misiolek KA, Roh D, Alawi A, Bauerschmidt A, Park S, Agarwal S, Meyers PM, Connolly ES, Claassen J, Schmidt JM (2019) White blood cell count improves prediction of delayed cerebral ischemia following aneurysmal subarachnoid hemorrhage. Neurosurgery 84:397–403. https://doi.org/10.1093/neuros/nyy045

    Article  PubMed  Google Scholar 

  31. Behrouz R, Godoy DA, Topel CH, Birnbaum LA, Caron JL, Grandhi R, Johnson JN, Misra V, Seifi A, Urbansky K (2016) Early hypoalbuminemia is an independent predictor of mortality in aneurysmal subarachnoid hemorrhage. Neurocrit Care 25:1–7

    Article  Google Scholar 

  32. Claassen J, Vu A, Kreiter KT, Kowalski RG, Du EY, Ostapkovich N, Fitzsimmons BF, Connolly ES, Mayer SA (2004) Effect of acute physiologic derangements on outcome after subarachnoid hemorrhage. Crit Care Med 32:832–838. https://doi.org/10.1097/01.ccm.0000114830.48833.8a

    Article  PubMed  Google Scholar 

  33. Baldwin ME, Macdonald RL, DRL Huo (2004) Early Vasospasm on admission angiography in patients with aneurysmal subarachnoid hemorrhage is a predictor for in-hospital complications and poor outcome. Stroke 35

  34. Terao Y, Takada M, Tanabe T, Ando Y, Sumikawa K (2007) Microalbuminuria is a prognostic predictor in aneurysmal subarachnoid hemorrhage. Intensive Care Med 33:1000

    Article  Google Scholar 

Download references

Acknowledgements

We thank all the staff and participants for their contribution to this study.

Funding

This study was supported by the National Key Research and Development Program of China (Grant No. 2021YFC2501101 and 2020YFC2004701) and the National Natural Science Foundation of China (Grant No. 82071296, 81671129 and 81471210).

Author information

Authors and Affiliations

  1. Department of Neurosurgery, Fengtai District, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring West Road, Beijing, 100070, China

    Runting Li, Fa Lin, Yu Chen, Junlin Lu, Jun Yang, Heze Han, Kexin Yuan, Ke Wang, Debin Yan, Ruinan Li, Shihao He, Zhipeng Li, Haibin Zhang, Li Ma, Yahui Zhao, Qiang Hao, Xun Ye, Hao Wang, Shuo Wang, Xiaolin Chen & Yuanli Zhao

  2. Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

    Xiheng Chen & Youxiang Li

  3. Department of Critical Care Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

    Hongliang Li, Linlin Zhang, Guangzhi Shi & Jianxin Zhou

  4. Beijing, China

    Shuo Wang & Yuanli Zhao

  5. Stroke Center, Beijing Institute for Brain Disorders, Beijing, China

    Shuo Wang, Xiaolin Chen & Yuanli Zhao

  6. Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China

    Shuo Wang, Xiaolin Chen & Yuanli Zhao

Authors
  1. Runting Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fa Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Junlin Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Heze Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kexin Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ke Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Debin Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ruinan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Shihao He
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Zhipeng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Haibin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Xiheng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Li Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Yahui Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Qiang Hao
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Xun Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Hao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Hongliang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Linlin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Guangzhi Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Jianxin Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Youxiang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Shuo Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Xiaolin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Yuanli Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception and design: Xiaolin Chen, Yuanli Zhao. Acquisition of data: Runting Li, Fa Lin, Yu Chen, Junlin Lu, Heze Han, Li Ma, Yahui Zhao, Debin Yan, Ruinan Li, Jun Yang, Shihao He, Zhipeng Li, Haibin Zhang, Kexin Yuan, Ke Wang, Hongliang Li, Linlin Zhang. Analysis and interpretation of data: All authors. Drafting the article: Runting Li. Reviewed submitted version of manuscript: Xiaolin Chen, Yuanli Zhao. Statistical analysis: Runting Li, Fa Lin, Yu Chen, Junlin Lu, Qiang Hao. Administrative/technical/material support: Youxiang Li, Shuo Wang, Guangzhi Shi, Jianxin Zhou. Study supervision: Xiaolin Chen, Yuanli Zhao.

Corresponding authors

Correspondence to Xiaolin Chen or Yuanli Zhao.

Ethics declarations

Ethics approval

This study was approved by the Institutional Review Board of Beijing Tiantan Hospital (KY 2021–008-01). All the analysis was performed according to the Declaration of Helsinki and the local ethics policies.

Consent to participate

Informed consent for clinical analysis was obtained from all individual participants or their authorized representatives.

Consent for publication

All authors read and approved the final manuscript.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 16 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, R., Lin, F., Chen, Y. et al. The effect of sex differences on complications and 90-day outcomes after aneurysmal subarachnoid hemorrhage: a propensity score-matched analysis. Neurosurg Rev 45, 3339–3347 (2022). https://doi.org/10.1007/s10143-022-01836-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10143-022-01836-x

Keywords

Search

Navigation