Skip to main content

Advertisement

SpringerLink
Log in

The Modified Fisher Scale Lacks Interrater Reliability

  • Original work
  • Published:
Neurocritical Care Aims and scope Submit manuscript

Abstract

Background

The modified Fisher scale (mFS) is a critical clinical and research tool for risk stratification of cerebral vasospasm. As such, the mFS is included as a common data element by the National Institute of Neurological Disorders and Stroke SAH Working Group. There are few studies assessing the interrater reliability of the mFS.

Methods

We distributed a survey to a convenience sample with snowball sampling of practicing neurointensivists and through the research survey portion of the Neurocritical Care Society Web site. The survey consisted of 15 scrollable CT scans of patients with SAH for mFS grading, two questions regarding the definitions of the scale criteria and demographics of the responding physician. Kendall’s coefficient of concordance was used to determine the interrater reliability of mFS grading.

Results

Forty-six participants (97.8% neurocritical care fellowship trained, 78% UCNS-certified in neurocritical care, median 5 years (IQR 3–6.3) in practice, treating median of 80 patients (IQR 50–100) with SAH annually from 32 institutions) completed the survey. By mFS criteria, 30% correctly identified that there is no clear measurement of thin versus thick blood, and 42% correctly identified that blood in any ventricle is scored as “intraventricular blood.” The overall interrater reliability by Kendall’s coefficient of concordance for the mFS was moderate (W = 0.586, p < 0.0005).

Conclusions

Agreement among raters in grading the mFS is only moderate. Online training tools could be developed to improve mFS reliability and standardize research in SAH.

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.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Hop JW, Rinkel GJ, Algra A, van Gijn J. Initial loss of consciousness and risk of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Stroke. 1999;30(11):2268–71.

    Article  CAS  Google Scholar 

  2. Hijdra A, van Gijn J, Nagelkerke NJ, Vermeulen M, van Crevel H. Prediction of delayed cerebral ischemia, rebleeding, and outcome after aneurysmal subarachnoid hemorrhage. Stroke. 1988;19(10):1250–6.

    Article  CAS  Google Scholar 

  3. Chou SH, Smith EE, Badjatia N, et al. A randomized, double-blind, placebo-controlled pilot study of simvastatin in aneurysmal subarachnoid hemorrhage. Stroke. 2008;39(10):2891–3.

    Article  CAS  Google Scholar 

  4. Dorsch N. A clinical review of cerebral vasospasm and delayed ischaemia following aneurysm rupture. Acta Neurochir Suppl. 2011;110(Pt 1):5–6.

    PubMed  Google Scholar 

  5. Dorhout Mees SM, Kerr RS, Rinkel GJ, Algra A, Molyneux AJ. Occurrence and impact of delayed cerebral ischemia after coiling and after clipping in the International Subarachnoid Aneurysm Trial (ISAT). J Neurol. 2012;259(4):679–83.

    Article  Google Scholar 

  6. Rosengart AJ, Schultheiss KE, Tolentino J, Macdonald RL. Prognostic factors for outcome in patients with aneurysmal subarachnoid hemorrhage. Stroke. 2007;38(8):2315–21.

    Article  Google Scholar 

  7. Fisher CM, Kistler JP, Davis JM. Relation of cerebral vasospasm to subarachnoid hemorrhage visualized by computerized tomographic scanning. Neurosurgery. 1980;6(1):1–9.

    Article  CAS  Google Scholar 

  8. Rosen DS, Macdonald RL. Subarachnoid hemorrhage grading scales: a systematic review. Neurocrit Care. 2005;2(2):110–8.

    Article  Google Scholar 

  9. Komiyama M. Misunderstanding of Fisher’s grouping system for computed tomography evaluation of aneurysmal subarachnoid haemorrhage. Interv Neuroradiol. 2019;25(6):653–4.

    Article  Google Scholar 

  10. Claassen J, Bernardini GL, Kreiter K, et al. Effect of cisternal and ventricular blood on risk of delayed cerebral ischemia after subarachnoid hemorrhage: the Fisher scale revisited. Stroke. 2001;32(9):2012–20.

    Article  CAS  Google Scholar 

  11. Singer R, Ogilvy C, Rordorf G. Subarachnoid hemorrhage grading scales. UpToDate Inc. UpToDate Web site. https://www.uptodate.com. Published 2020. Updated November 19, 2019. Accessed 5 Feb 2020.

  12. Frontera JA, Claassen J, Schmidt JM, et al. Prediction of symptomatic vasospasm after subarachnoid hemorrhage: the modified fisher scale. Neurosurgery. 2006;59(1):21–7 (discussion 21-27).

    Article  Google Scholar 

  13. Rosen DS, Macdonald RL. Subarachnoid hemorrhage grading scales. UpToDate Inc. UpToDate Web site. https://www.uptodate.com. Published 2020. Updated November 19, 2019. Accessed 5 Feb 2020.

  14. de Oliveira Manoel AL, Jaja BN, Germans MR, et al. The VASOGRADE: a simple grading scale for prediction of delayed cerebral ischemia after subarachnoid hemorrhage. Stroke. 2015;46(7):1826–31.

    Article  Google Scholar 

  15. van der Steen WE, Leemans EL, van den Berg R, et al. Radiological scales predicting delayed cerebral ischemia in subarachnoid hemorrhage: systematic review and meta-analysis. Neuroradiology. 2019;61(3):247–56.

    Article  Google Scholar 

  16. Kramer AH, Hehir M, Nathan B, et al. A comparison of 3 radiographic scales for the prediction of delayed ischemia and prognosis following subarachnoid hemorrhage. J Neurosurg. 2008;109(2):199–207.

    Article  Google Scholar 

  17. Jiménez-Roldán L, Alén JF, Gómez PA, 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.

    Article  Google Scholar 

  18. Suarez JI, Sheikh MK, Macdonald RL, et al. Common data elements for unruptured intracranial aneurysms and subarachnoid hemorrhage clinical research: a national institute for neurological disorders and stroke and national library of medicine project. Neurocrit Care. 2019;30(Suppl 1):4–19.

    Article  Google Scholar 

  19. Lund Research Ltd. https://statistics.laerd.com/premium/spss/kccir/kendalls-coefficient-of-concordance-in-spss-4.php. Accessed 4 May 2020.

  20. Woo PYM, Tse TPK, Chan RSK, et al. Computed tomography interobserver agreement in the assessment of aneurysmal subarachnoid hemorrhage and predictors for clinical outcome. J Neurointerv Surg. 2017;9(11):1118–24.

    Article  Google Scholar 

  21. Dupont SA, Wijdicks EF, Manno EM, Lanzino G, Rabinstein AA. Prediction of angiographic vasospasm after aneurysmal subarachnoid hemorrhage: value of the Hijdra sum scoring system. Neurocrit Care. 2009;11(2):172–6.

    Article  Google Scholar 

  22. Macdonald RL. Delayed neurological deterioration after subarachnoid haemorrhage. Nat Rev Neurol. 2014;10(1):44–58.

    Article  CAS  Google Scholar 

  23. Damani R, Mayer S, Dhar R, et al. Common data element for unruptured intracranial aneurysm and subarachnoid hemorrhage: recommendations from assessments and clinical examination workgroup/subcommittee. Neurocrit Care. 2019;30(Suppl 1):28–35.

    Article  Google Scholar 

  24. Hackenberg KAM, Etminan N, Wintermark M, et al. Common data elements for radiological imaging of patients with subarachnoid hemorrhage: proposal of a multidisciplinary research group. Neurocrit Care. 2019;30(Suppl 1):60–78.

    Article  Google Scholar 

  25. Kummer B. Modified fisher grading scale for subarachnoid hemorrhage (SAH). http://www.mdcalc.com. Accessed 5 Feb 2020.

  26. Lyden P, Brott T, Tilley B, et al. Improved reliability of the NIH Stroke Scale using video training. NINDS TPA Stroke Study Group. Stroke. 1994;25(11):2220–6.

    Article  CAS  Google Scholar 

  27. Mak HK, Yau KK, Khong PL, et al. Hypodensity of > 1/3 middle cerebral artery territory versus Alberta Stroke Programme Early CT Score (ASPECTS): comparison of two methods of quantitative evaluation of early CT changes in hyperacute ischemic stroke in the community setting. Stroke. 2003;34(5):1194–6.

    Article  Google Scholar 

  28. Gupta AC, Schaefer PW, Chaudhry ZA, et al. Interobserver reliability of baseline noncontrast CT Alberta Stroke Program Early CT Score for intra-arterial stroke treatment selection. AJNR Am J Neuroradiol. 2012;33(6):1046–9.

    Article  CAS  Google Scholar 

  29. Mura J, Rojas-Zalazar D, Ruíz A, Vintimilla LC, Marengo JJ. Improved outcome in high-grade aneurysmal subarachnoid hemorrhage by enhancement of endogenous clearance of cisternal blood clots: a prospective study that demonstrates the role of lamina terminalis fenestration combined with modern microsurgical cisternal blood evacuation. Minim Invasive Neurosurg. 2007;50(6):355–62.

    Article  CAS  Google Scholar 

  30. Mayer SA, Aldrich EF, Bruder N, et al. Thick and diffuse subarachnoid blood as a treatment effect modifier of Clazosentan after subarachnoid hemorrhage. Stroke. 2019;50(10):2738–44.

    Article  CAS  Google Scholar 

Download references

Funding

None.

Author information

Authors and Affiliations

  1. Department of Neurology, Lehigh Valley Health Network, 1250 S Cedar Crest Blvd, Suite 405, Allentown, PA, USA

    Christopher Melinosky

  2. Network Office of Research and Innovation (NORI), Lehigh Valley Health Network, Allentown, PA, USA

    Hope Kincaid

  3. Department of Neurology, Neurological Institute, New York Presbyterian Hospital, Columbia University, New York, NY, USA

    Jan Claassen

  4. Department of Neurology, Program in Trauma, University of Maryland School of Medicine, Baltimore, MD, USA

    Gunjan Parikh, Neeraj Badjatia & Nicholas A. Morris

Authors
  1. Christopher Melinosky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hope Kincaid
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jan Claassen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gunjan Parikh
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Neeraj Badjatia
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Nicholas A. Morris
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The manuscript complies with all instructions to authors. Authorship requirements have been met, and the final manuscript was approved by all authors. This has not been published elsewhere and is not under consideration by another journal.

Corresponding author

Correspondence to Christopher Melinosky.

Ethics declarations

Conflict of interest

Dr. Claassen reports grants from NINDS, grants from NINDS, other from iCE Neurosystem, outside the submitted work. There are no other conflicts of interest.

Ethical approval

This study adheres to ethical guidelines. This study was reviewed and approved by LVHN’s institutional review board (IRB) and qualified as Human Subjects Research in Exempt Category (2) (i).

Additional information

Publisher's Note

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 562 kb)

Supplementary material 2 (PDF 655 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Melinosky, C., Kincaid, H., Claassen, J. et al. The Modified Fisher Scale Lacks Interrater Reliability. Neurocrit Care 35, 72–78 (2021). https://doi.org/10.1007/s12028-020-01142-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12028-020-01142-8

Keywords

Search

Navigation