Background
Prognostication after a stroke has important implications for care and for decisions
made by patients and their families. It is not clear why clinicians, even experienced
stroke neurologists, poorly estimate the risk of disability and death following stroke.
Methods
We analyzed the results from the Clinician Judgment versus Risk Score to predict Stroke
Outcomes study in which each clinician estimated the risk of death and the risk of
death or disability in 5 case-based ischemic stroke scenarios. We employed a mixed-effect
linear model to disentangle the ability of clinicians to discriminate between poor
and good prognosis cases (slope) from the calibration of quantitative estimates (intercept),
and to assess for any effect of anchoring in the death or disability condition (through
a comparison with the death condition).
Results
One hundred eleven clinicians made 1665 predictions. Clinicians were able to discriminate
between cases with low and high risks of death (slope of .81, 95% confidence interval
[CI] .70-.93), but the quantitative estimates were not well calibrated (intercept
of 5.14, 95% CI 3.97-6.33). The discrimination was poorer (slope of .67, 95% CI .60-.75),
but the calibration was better (intercept of −.34, 95% CI −5.43 to 4.98) in the death
or disability estimates.
Conclusion
Poor stroke prognostication can be explained by poor calibration and an anchoring
effect, which are both amenable to specific training interventions.
Key Words
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References
- Predicting outcome of IV thrombolysis-treated ischemic stroke patients: the DRAGON score.Neurology. 2012; 78: 427-432
- IScore: a risk score to predict death early after hospitalization for an acute ischemic stroke.Circulation. 2011; 123: 739-749
- JURaSSiC: accuracy of Clinician vs Risk Score Prediction of Ischemic Stroke Outcomes.Neurology. 2013; 81: 448-455
- Measuring the accuracy of diagnostic systems.Science. 1988; 240: 1285-1293
- Quantifying the information value of clinical assessments with signal detection theory.Annu Rev Psychol. 1999; 50: 215-241
- ROC analysis applied to the evaluation of medical imaging techniques.Invest Radiol. 1979; 14: 109-121
- Cognitive biases in playing the lottery: estimating the odds and choosing the numbers.J Appl Soc Psychol. 1992; 22: 934-952
- Registry of the Canadian Stroke Network—Progress Report 2001-2005.(Institute for Clinical Evaluative Sciences)2005
- Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment.Stroke. 1993; 24: 35-41
- Risk factors, outcome, and treatment in subtypes of ischemic stroke: the German stroke data bank.Stroke. 2001; 32: 2559-2566
- Baseline NIH Stroke Scale score strongly predicts outcome after stroke: a report of the Trial of Org 10172 in Acute Stroke Treatment (TOAST).Neurology. 1999; 53: 126-131
- The iScore predicts poor functional outcomes early after hospitalization for an acut e ischemic stroke.Stroke. 2011; 42: 3421-3428
- Stroke Prognostication using Age and NIH Stroke Scale: SPAN-100.Neurology. 2013; 80: 21-28
Article info
Publication history
Published online: March 14, 2016
Accepted:
January 16,
2016
Received in revised form:
January 10,
2016
Received:
November 13,
2015
Footnotes
Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT01657279.
Identification
DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.01.024
Copyright
© 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.
