Skip to main content

Advertisement

SpringerLink
Log in

Derivation and validation of a simple risk score for predicting 1-year mortality in stroke

  • ORIGINAL COMMUNICATION
  • Published:
Journal of Neurology Aims and scope Submit manuscript

Abstract

Context

Numerous models have been presented for the prognosis in acute stroke; however they have been criticized for being difficult to use, and few have been validated in independent samples.

Objectives

To develop simple risk score models for 1-year mortality in acute stroke in patients > 60 years old and validate the models.

Design

From a cohort of 2321 consecutive patients > 60 years of age with acute stroke in one hospital, we randomly selected 800 patients for chart review. Among 737 patients with validated acute stroke, we randomly split the sample into (1) a derivation (60%; n = 442) and (2) a validation sample (40%; n=295).We used logistic regression to develop three models with 2- covariates and a corresponding risk score from the derivation sample. The models were validated using area under the receiver operating curves.

Results

Three risk score models for 1-year mortality after stroke were developed using combinations of age, Canadian Neurological Scale score (CNSscore) (≥3.5 = 0, >3.5 = 1), Charlson comorbidity index and stroke type (ischemic = 0, hemorrhagic = 1). Both 2-variable (Age -60 + (30*CNSscore)), 3-variable (Age -60 + (30*CNSscore) + 4*Charlson)) and 4-variable (Age -60 + (25*CNSscore) + (5*Charlson) + (18*Stroke type)) models reliably predicted the outcome with an area under the receiver operating curve ranging 0.71 to 0.72.

Conclusions

Simple models incorporating two to four covariates reliably predicted 1-year mortality. Such models can be used to stratify prognosis in clinical practice, research or intervention trials.

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

Similar content being viewed by others

References

  1. Benesch C, Witter DM Jr, Wilder AL, Duncan PW, Samsa GP, Matchar DB (1997) Inaccuracy of the International Classification of Diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease. Neurology 49:660-64

    CAS  PubMed  Google Scholar 

  2. Boysen G, Christensen H (2001) Stroke severity determines body temperature in acute stroke. Stroke 32:413-17

    Article  CAS  PubMed  Google Scholar 

  3. Broderick J, Brott T, Kothari R, Miller R, Khoury J, Pancioli A, Gebel J, Mills D, Minneci L, Shukla R (1998) The Greater Cincinnati/Northern Kentucky Stroke Study: preliminary first-ever and total incidence rates of stroke among blacks. Stroke 29:415-21

    CAS  PubMed  Google Scholar 

  4. Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373-83

    Article  CAS  PubMed  Google Scholar 

  5. Counsell C, Dennis M (2001) Systematic review of prognostic models in patients with acute stroke. Cerebrovasc Dis 12:159-70

    Article  CAS  PubMed  Google Scholar 

  6. Demchuk AM, Buchan AM (2000) Predictors of stroke outcome. Neurol Clin 18:455-73

    Article  CAS  PubMed  Google Scholar 

  7. Ellekjaer H, Holmen J, Kruger O, Terent A (1999) Identification of incident stroke in Norway: Hospital discharge data compared with a population- based stroke register. Stroke 30:56-0

    CAS  PubMed  Google Scholar 

  8. Fiorelli M, Alperovitch A, Argentino C, Sacchetti ML, Toni D, Sette G, Cavalletti C, Gori MC, Fieschi C (1995) Prediction of long-term outcome in the early hours following acute ischemic stroke. Arch Neurol 52:250-55

    CAS  PubMed  Google Scholar 

  9. German Stroke Study Collaboration (2004) Predicting outcome after acute ischemic stroke: an external validation of prognostic models.Neurology 24; 62(4):581-85

    Google Scholar 

  10. Goldstein LB (1998) Accuracy of ICD- 9-CM coding for the identification of patients with acute ischemic stroke: effect of modifier codes. Stroke 29:1602-604

    CAS  PubMed  Google Scholar 

  11. Goldstein LB, Chilukuri V (1997) Retrospective assessment of initial stroke severity with the Canadian Neurological Scale. Stroke 28:1181-184

    CAS  PubMed  Google Scholar 

  12. Hajat C, Hajat S, Sharma P (2000) Effects of poststroke pyrexia on stroke outcome: a meta-analysis of studies in patients. Stroke 31:410-14

    CAS  PubMed  Google Scholar 

  13. Hankey GJ, Jamrozik K, Broadhurst RJ, Forbes S, Burvill PW, Anderson CS, Stewart-Wynne EG (2000) Five-year survival after first-ever stroke and related prognostic factors in the Perth Community Stroke Study. Stroke 31:2080-086

    CAS  PubMed  Google Scholar 

  14. Kammersgaard LP, Jorgensen HS, Rungby JA, Reith J, Nakayama H, Weber UJ, Houth J, Olsen TS (2002) Admission body temperature predicts long-term mortality after acute stroke: the Copenhagen Stroke Study. Stroke 33:1759-762

    Article  CAS  PubMed  Google Scholar 

  15. Lee DS,Austin PC, Rouleau JL, Liu PP, Naimark D, Tu JV (2003) Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model. JAMA 290:2581-587

    Article  CAS  PubMed  Google Scholar 

  16. Moons KG,Harrell FE, Steyerberg EW (2002) Should scoring rules be based on odds ratios or regression coefficients? J Clin Epidemiol 55:1054-055

    Article  PubMed  Google Scholar 

  17. Petty GW, Brown RD Jr, Whisnant JP, Sicks JD, O'Fallon WM, Wiebers DO (2000) Ischemic stroke subtypes: a population-based study of functional outcome, survival, and recurrence. Stroke 31:1062-068

    CAS  PubMed  Google Scholar 

  18. Ronning OM,Guldvog B (1998) Stroke units versus general medical wards, I: twelve- and eighteen-month survival: a randomized, controlled trial. Stroke 29:58-2

    CAS  PubMed  Google Scholar 

  19. Stavem K, Lossius M, Ronning OM (2003) Reliability and validity of the Canadian Neurological Scale in retrospective assessment of initial stroke severity. Cerebrovasc Dis 16:286-91

    Article  PubMed  Google Scholar 

  20. Stavem K, Ronning OM (2002) Survival of unselected stroke patients in a stroke unit compared with conventional care. QJM 95:143-52

    Article  CAS  PubMed  Google Scholar 

  21. Sumer MM, Ozdemir I, Tascilar N (2003) Predictors of outcome after acute ischemic stroke. Acta Neurol Scand 107:276-80

    Article  CAS  PubMed  Google Scholar 

  22. Tilling K, Sterne JA, Rudd AG, Glass TA, Wityk RJ, Wolfe CD (2001) A new method for predicting recovery after stroke. Stroke 32:2867-873

    Article  CAS  PubMed  Google Scholar 

  23. Tu JV, Naylor CD (1997) Clinical prediction rules. J Clin Epidemiol 50:743-44

    Article  CAS  PubMed  Google Scholar 

  24. Wang Y, Lim LL, Heller RF, Fisher J, Levi CR (2003) A prediction model of 1-year mortality for acute ischemic stroke patients. Arch Phys Med Rehabil 84:1006-011

    Article  PubMed  Google Scholar 

  25. Wang Y, Lim LL, Levi C, Heller RF, Fischer J (2001) A prognostic index for 30-day mortality after stroke. J Clin Epidemiol 54:766-73

    Article  CAS  PubMed  Google Scholar 

  26. Weimar C, Konig IR, Kraywinkel K, Ziegler A,Diener HC (2004) German Stroke Study Collaboration. 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 35:158-62

    Article  CAS  PubMed  Google Scholar 

  27. Weimar C, Roth M, Willig V, Kostopoulos P, Benemann J, Diener HC (2006) Development and validation of a prognostic model to predict recovery following intracerebral hemorrhage. J Neurol 253:788-93

    Article  PubMed  Google Scholar 

  28. Weimar C, Ziegler A, Konig IR, Diener HC (2002) Predicting functional outcome and survival after acute ischemic stroke. J Neurol 249:888-95

    Article  PubMed  Google Scholar 

  29. Weir NU, Counsell CE, McDowall M, Gunkel A, Dennis MS (2003) Reliability of the variables in a new set of models that predict outcome after stroke. J Neurol Neurosurg Psychiatry 74:447-51

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Medical Department, Akershus University Hospital, Lørenskog, Norway

    O. G. Solberg MD & K. Stavem MD, PhD

  2. Dept. of Neurology, Akershus University Hospital, Lørenskog, Norway

    M. Dahl MD

  3. The Knowledge Center for the Health Services, Oslo, Norway

    P. Mowinckel MSc

  4. Helse Øst Health Services Research Centre, Lørenskog, Norway

    K. Stavem MD, PhD

  5. Dept. of Cardiology, Rikshospitalet University Hospital, 0027, Oslo, Norway

    O. G. Solberg MD

Authors
  1. O. G. Solberg MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Dahl MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. P. Mowinckel MSc
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. K. Stavem MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to O. G. Solberg MD.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Solberg, O.G., Dahl, M., Mowinckel, P. et al. Derivation and validation of a simple risk score for predicting 1-year mortality in stroke. J Neurol 254, 1376–1383 (2007). https://doi.org/10.1007/s00415-007-0555-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00415-007-0555-2

Key words

Search

Navigation