Stroke Prognostication using Age and NIH Stroke Scale
SPAN-100
ABSTRACT
Objectives:
Age and stroke severity are major determinants of stroke outcomes, but systematically incorporating these prognosticators in the routine practice of acute ischemic stroke can be challenging. We evaluated the effect of an index combining age and stroke severity on response to IV tissue plasminogen activator (tPA) among patients in the National Institute of Neurological Disorders and Stroke (NINDS) tPA stroke trials.
Methods:
We created the Stroke Prognostication using Age and NIH Stroke Scale (SPAN) index by combining age in years plus NIH Stroke Scale (NIHSS) ≥100. We applied the SPAN-100 index to patients in the NINDS tPA stroke trials (parts I and II) to evaluate its ability to predict clinical response and risk of intracerebral hemorrhage (ICH) after thrombolysis. The main outcome measures included ICH (any type) and a composite favorable outcome (defined as a modified Rankin Scale score of 0 or 1, NIHSS ≤1, Barthel index ≥95, and Glasgow Outcome Scale score of 1) at 3 months. Bivariate and multivariable logistic regression analyses were used to determine the association between SPAN-100 and outcomes of interest.
Results:
Among 624 patients in the NINDS trials, 62 (9.9%) participants were SPAN-100 positive. Among those receiving tPA, ICH rates were higher for SPAN-100–positive patients (42% vs 12% in SPAN-100–negative patients; p < 0.001); similarly, ICH rates were higher in SPAN-100–positive patients (19% vs 5%; p = 0.005) among those not receiving tPA. SPAN-100 was associated with worse outcomes. The benefit of tPA, defined as favorable composite outcome at 3 months, was present in SPAN-100–negative patients (55.4% vs 40.2%; p < 0.001), but not in SPAN-100–positive patients (5.6% tPA vs 3.9%; p = 0.76). Similar trends were found for secondary outcomes (e.g., symptomatic ICH, catastrophic outcome, discharge home).
Conclusion:
The SPAN-100 index could be a simple method for estimating the clinical response and risk of hemorrhagic complications after tPA for acute ischemic stroke. These results need further confirmation in larger contemporary datasets.
Get full access to this article
View all available purchase options and get full access to this article.
Supplementary Material
STUDY FUNDING
Dr. Saposnik is supported by the Distinguished Clinician-Scientist Award from the Heart and Stroke Foundation of Canada (HSFC).
REFERENCES
1.
Weimar C, Konig IR, Kraywinkel K, Ziegler A, Diener HC. Age and National Institutes of Health Stroke Scale score within 6 hours after onset are accurate predictors of outcome after cerebral ischemia: development and external validation of prognostic models. Stroke 2004;35:158–162.
2.
Konig IR, Ziegler A, Bluhmki E, et al. Predicting long-term outcome after acute ischemic stroke: a simple index works in patients from controlled clinical trials. Stroke 2008;39:1821–1826.
3.
Predicting outcome after acute ischemic stroke: an external validation of prognostic models. Neurology 2004;62:581–585.
4.
Hacke W, Kaste M, Fieschi C, et al. Intravenous thrombolysis with recombinant tissue plasminogen activator for acute hemispheric stroke: The European Cooperative Acute Stroke Study (ECASS). JAMA 1995;274:1017–1025.
5.
Hacke W, Kaste M, Fieschi C, et al. Randomised double-blind placebo-controlled trial of thrombolytic therapy with intravenous alteplase in acute ischaemic stroke (ECASS II): Second European-Australasian Acute Stroke Study Investigators. Lancet 1998;352:1245–1251.
6.
Clark WM, Albers GW, Madden KP, Hamilton S. The rtPA (alteplase) 0- to 6-hour acute stroke trial, part A (a0276g): results of a double-blind, placebo-controlled, multicenter study: Thrombolytic Therapy in Acute Ischemic Stroke Study Investigators. Stroke 2000;31:811–816.
7.
Hacke W, Kaste M, Bluhmki E, et al. Thrombolysis with alteplase 3 to 4.5 hours after acute ischemic stroke. N Engl J Med 2008;359:1317–1329.
8.
The National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Group. Tissue plasminogen activator for acute ischemic stroke. N Engl J Med 1995;333:1581–1587.
9.
Mishra NK, Ahmed N, Andersen G, et al. Thrombolysis in very elderly people: controlled comparison of SITS international stroke thrombolysis registry and virtual international stroke trials archive. BMJ 2010;341:c6046.
10.
Sylaja PN, Cote R, Buchan AM, Hill MD. Thrombolysis in patients older than 80 years with acute ischaemic stroke: Canadian Alteplase for Stroke Effectiveness Study. J Neurol Neurosurg Psychiatry 2006;77:826–829.
11.
Garg AX, Adhikari NK, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005;293:1223–1238.
12.
Saposnik G, Cote R, Phillips S, et al. Stroke outcome in those over 80: a multicenter cohort study across Canada. Stroke 2008;39:2310–2317.
13.
Kent DM, Selker HP, Ruthazer R, Bluhmki E, Hacke W. The stroke-thrombolytic predictive instrument: a predictive instrument for intravenous thrombolysis in acute ischemic stroke. Stroke 2006;37:2957–2962.
14.
Saposnik G, Kapral MK, Liu Y, et al. iScore: a risk score to predict death early after hospitalization for an acute ischemic stroke. Circulation 2011;123:739–749.
15.
Strbian D, Meretoja A, Ahlhelm FJ, et al. Predicting outcome of IV thrombolysis-treated ischemic stroke patients: the DRAGON score. Neurology 2012;78:427–432.
16.
The NINDS t-PA Stroke Study Group. Intracerebral hemorrhage after intravenous t-PA therapy for ischemic stroke. Stroke 1997;28:2109–2118.
17.
Saposnik G, Young B, Silver B, et al. Lack of improvement in patients with acute stroke after treatment with thrombolytic therapy: predictors and association with outcome. JAMA 2004;292:1839–1844.
18.
Altman DG. Confidence intervals for the number needed to treat. BMJ 1998;317:1309–1312.
19.
Lou M, Safdar A, Mehdiratta M, et al. The HAT score: a simple grading scale for predicting hemorrhage after thrombolysis. Neurology 2008;71:1417–1423.
20.
Ntaios G, Faouzi M, Ferrari J, Lang W, Vemmos K, Michel P. An integer-based score to predict functional outcome in acute ischemic stroke: the ASTRAL score. Neurology 2012;78:1916–1922.
21.
Saposnik G, Fang J, Kapral MK, et al. The iScore predicts effectiveness of thrombolytic therapy for acute ischemic stroke. Stroke 2012;43:1315–1322.
22.
Guzik AK, Raman R, Ernstron K, et al. Clinical outcomes of the ‘Stroke 100 club.’ Stroke 2012;43:A3572.
23.
Saposnik G, Raptis S, Kapral MK, et al. The iScore predicts poor functional outcomes early after hospitalization for an acute ischemic stroke. Stroke 2011;42:3421–3428.
24.
Saposnik G, Demchuk A, Tu JV, Johnston SC, Stroke Outcomes Research Canada (SORCan) Working Group. The iScore predicts efficacy and risk of bleeding in the National Institute of Neurological Disorders and Stroke tissue plasminogen activator stroke trial. J Stroke Cerebrovasc Dis Epub 2012 Oct 24.
25.
Merino JG, Silver B, Wong E, Demaerschalk B, Tamayo A, Hachinski V. Physician knowledge of the benefits, risks, and contraindications of tissue plasminogen activator for acute ischemic stroke. Stroke 2001;32:2208–2209.
Information & Authors
Information
Published In
Copyright
© 2012 American Academy of Neurology.
Publication History
Received: May 24, 2012
Accepted: August 15, 2012
Published online: November 21, 2012
Published in print: January 1, 2013
Disclosure
The authors report no disclosures relevant to the manuscript. Go to Neurology.org for full disclosures.
Authors
Author Contributions
G. Saposnik: drafting/revising the manuscript, study concept or design, analysis or interpretation of data, contribution of vital reagents/tools/patients, acquisition of data, statistical analysis, study supervision, obtaining funding. A. Guzik: drafting/revising the manuscript. B. Ovbiagele: drafting/revising the manuscript, study concept or design, analysis or interpretation of data. M. Reeves: drafting/revising the manuscript, analysis or interpretation of data, statistical analysis. S.C. Johnston: drafting/revising the manuscript, study concept or design, analysis or interpretation of data, study supervision.
Metrics & Citations
Metrics
Citations
Download Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Select your manager software from the list below and click Download.
Cited By
- Evaluating Serum Copeptin as a Promising Biomarker for Predicting Acute Ischaemic Stroke Severity: A Hospital-Based Study on Strokes, Cureus, (2024).https://doi.org/10.7759/cureus.63700
- A Multimodal Ensemble Deep Learning Model for Functional Outcome Prognosis of Stroke Patients, Journal of Stroke, 26, 2, (312-320), (2024).https://doi.org/10.5853/jos.2023.03426
- External Validation and Updating of Published Models for Predicting 7-day Risk of Symptomatic Intracranial Hemorrhage after Receiving Alteplase for Acute Ischemic Stroke: A Retrospective Cohort Study, Annals of Indian Academy of Neurology, 27, 1, (58-66), (2024).https://doi.org/10.4103/aian.aian_837_23
- Factors predicting functional outcome after rtPA for patients with acute ischemic stroke, The Egyptian Journal of Neurology, Psychiatry and Neurosurgery, 60, 1, (2024).https://doi.org/10.1186/s41983-024-00790-3
- Stroke Measures Analysis of pRognostic Testing—Mortality nomogram predicts long-term mortality after ischemic stroke, International Journal of Stroke, (2024).https://doi.org/10.1177/17474930241278808
- Functional Outcomes and Symptomatic Intracranial Hemorrhage After Endovascular Treatment in Acute Vertebrobasilar Artery Occlusions: External Validation of Prediction Models, Stroke: Vascular and Interventional Neurology, 4, 3, (2024).https://doi.org/10.1161/SVIN.123.001284
- HERMES-24 Score Derivation and Validation for Simple and Robust Outcome Prediction After Large Vessel Occlusion Treatment, Stroke, 55, 8, (1982-1990), (2024).https://doi.org/10.1161/STROKEAHA.123.045871
- Barthel Index, SPAN-100, and NIHSS Studies on the Predictive Value of Prognosis in Patients With Thrombolysis, The Neurologist, 29, 3, (158-162), (2024).https://doi.org/10.1097/NRL.0000000000000554
- Multi-modality multi-task model for mRS prediction using diffusion-weighted resonance imaging, Scientific Reports, 14, 1, (2024).https://doi.org/10.1038/s41598-024-71072-4
- Development and Internal Validation of Machine Learning Models to Predict Mortality and Disability After Mechanical Thrombectomy for Acute Anterior Circulation Large Vessel Occlusion, World Neurosurgery, 182, (e137-e154), (2024).https://doi.org/10.1016/j.wneu.2023.11.060
- See more
Loading...
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Personal login Institutional LoginPurchase Options
The neurology.org payment platform is currently offline. Our technical team is working as quickly as possible to restore service.
If you need immediate support or to place an order, please call or email customer service:
- 1-800-638-3030 for U.S. customers - 8:30 - 7 pm ET (M-F)
- 1-301-223-2300 for customers outside the U.S. - 8:30 - 7 pm ET (M-F)
- [email protected]
We appreciate your patience during this time and apologize for any inconvenience.
We thank Dr. Yufe for his comments regarding our article. [1] Regarding the control group for the SPAN-100, figures 1 and 2 and table 2 provide a comparison of multiple outcomes between SPAN-100 patients receiving tPA and placebo. SPAN-100 patients receiving tPA had higher risk of intracerebral hemorrhage compared to SPAN-100 in the placebo group. No significant benefit was observed in functional clinical outcomes allowing for a small sample size. The combination of age and stroke severity are the two major predictors of stroke outcomes. Although these results need to be validated in a larger dataset, we believe are useful when counseling ischemic stroke patients and their families.
1. Saposnik G, Guzik AK, Reeves M, Ovbiagele B, Johnston SC. Stroke Prognostication using Age and NIH Stroke Scale: SPAN-100. Neurology 2013; 80: 21-28.
For disclosures, please contact the editorial office at [email protected].
I read the article by Saposnik et al. with interest. [1] Without a control group with a Positive SPAN 100, it is difficult to know if giving tPA is of benefit. Studies have shown that the elderly do benefit from Tpa so that leaves the severity of the stroke as measured by the NIHSS Score as the main determinant of a good outcome.
Nevertheless, the paper is a useful tool with which to counsel families and substitute decision makers who must often decide for the aphasic patient on whether to give or not to give tpa in SPAN 100 patients.
1. Saposnik G, Guzik AK, Reeves M, Ovbiagele B, Johnston SC. Stroke Prognostication using Age and NIH Stroke Scale: SPAN-100. Neurology 2013; 80: 21-28.
For disclosures, contact the editorial office. .