Validating the telestroke mimic score a prediction rule for identifying stroke mimics evaluated over telestroke networks

Syed F. Ali, Gordian J. Hubert, Jeffrey A Switzer, Jennifer J. Majersik, Roland Backhaus, L. Wylie Shepard, Kishore Vedala, Lee H. Schwamm

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Background and Purpose-Up to 30% of acute stroke evaluations are deemed stroke mimics, and these are common in telestroke as well. We recently published a risk prediction score for use during telestroke encounters to differentiate stroke mimics from ischemic cerebrovascular disease derived and validated in the Partners TeleStroke Network. Using data from 3 distinct US and European telestroke networks, we sought to externally validate the TeleStroke Mimic (TM) score in a broader population. Methods-We evaluated the TM score in 1930 telestroke consults from the University of Utah, Georgia Regents University, and the German TeleMedical Project for Integrative Stroke Care Network. We report the area under the curve in receiveroperating characteristic curve analysis with 95% confidence interval for our previously derived TM score in which lower TM scores correspond with a higher likelihood of being a stroke mimic. Results-Based on final diagnosis at the end of the telestroke consultation, there were 630 of 1930 (32.6%) stroke mimics in the external validation cohort. All 6 variables included in the score were significantly different between patients with ischemic cerebrovascular disease versus stroke mimics. The TM score performed well (area under curve, 0.72; 95% confidence interval, 0.70-0.73; P<0.001), similar to our prior external validation in the Partners National Telestroke Network. Conclusions-The TM score's ability to predict the presence of a stroke mimic during telestroke consultation in these diverse cohorts was similar to its performance in our original cohort. Predictive decision-support tools like the TM score may help highlight key clinical differences between mimics and patients with stroke during complex, time-critical telestroke evaluations.

Original languageEnglish (US)
Pages (from-to)688-692
Number of pages5
JournalStroke
Volume49
Issue number3
DOIs
StatePublished - Jan 1 2018

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Stroke
Cerebrovascular Disorders
Area Under Curve
Referral and Consultation
Confidence Intervals
tebufenozide
Population

Keywords

  • Area under curve
  • Cerebrovascular disorders
  • Cohort studies
  • Humans
  • Risk

ASJC Scopus subject areas

  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine
  • Advanced and Specialized Nursing

Cite this

Validating the telestroke mimic score a prediction rule for identifying stroke mimics evaluated over telestroke networks. / Ali, Syed F.; Hubert, Gordian J.; Switzer, Jeffrey A; Majersik, Jennifer J.; Backhaus, Roland; Shepard, L. Wylie; Vedala, Kishore; Schwamm, Lee H.

In: Stroke, Vol. 49, No. 3, 01.01.2018, p. 688-692.

Research output: Contribution to journalArticle

Ali, SF, Hubert, GJ, Switzer, JA, Majersik, JJ, Backhaus, R, Shepard, LW, Vedala, K & Schwamm, LH 2018, 'Validating the telestroke mimic score a prediction rule for identifying stroke mimics evaluated over telestroke networks', Stroke, vol. 49, no. 3, pp. 688-692. https://doi.org/10.1161/STROKEAHA.117.018758
Ali, Syed F. ; Hubert, Gordian J. ; Switzer, Jeffrey A ; Majersik, Jennifer J. ; Backhaus, Roland ; Shepard, L. Wylie ; Vedala, Kishore ; Schwamm, Lee H. / Validating the telestroke mimic score a prediction rule for identifying stroke mimics evaluated over telestroke networks. In: Stroke. 2018 ; Vol. 49, No. 3. pp. 688-692.
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abstract = "Background and Purpose-Up to 30{\%} of acute stroke evaluations are deemed stroke mimics, and these are common in telestroke as well. We recently published a risk prediction score for use during telestroke encounters to differentiate stroke mimics from ischemic cerebrovascular disease derived and validated in the Partners TeleStroke Network. Using data from 3 distinct US and European telestroke networks, we sought to externally validate the TeleStroke Mimic (TM) score in a broader population. Methods-We evaluated the TM score in 1930 telestroke consults from the University of Utah, Georgia Regents University, and the German TeleMedical Project for Integrative Stroke Care Network. We report the area under the curve in receiveroperating characteristic curve analysis with 95{\%} confidence interval for our previously derived TM score in which lower TM scores correspond with a higher likelihood of being a stroke mimic. Results-Based on final diagnosis at the end of the telestroke consultation, there were 630 of 1930 (32.6{\%}) stroke mimics in the external validation cohort. All 6 variables included in the score were significantly different between patients with ischemic cerebrovascular disease versus stroke mimics. The TM score performed well (area under curve, 0.72; 95{\%} confidence interval, 0.70-0.73; P<0.001), similar to our prior external validation in the Partners National Telestroke Network. Conclusions-The TM score's ability to predict the presence of a stroke mimic during telestroke consultation in these diverse cohorts was similar to its performance in our original cohort. Predictive decision-support tools like the TM score may help highlight key clinical differences between mimics and patients with stroke during complex, time-critical telestroke evaluations.",
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AU - Hubert, Gordian J.

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AU - Majersik, Jennifer J.

AU - Backhaus, Roland

AU - Shepard, L. Wylie

AU - Vedala, Kishore

AU - Schwamm, Lee H.

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N2 - Background and Purpose-Up to 30% of acute stroke evaluations are deemed stroke mimics, and these are common in telestroke as well. We recently published a risk prediction score for use during telestroke encounters to differentiate stroke mimics from ischemic cerebrovascular disease derived and validated in the Partners TeleStroke Network. Using data from 3 distinct US and European telestroke networks, we sought to externally validate the TeleStroke Mimic (TM) score in a broader population. Methods-We evaluated the TM score in 1930 telestroke consults from the University of Utah, Georgia Regents University, and the German TeleMedical Project for Integrative Stroke Care Network. We report the area under the curve in receiveroperating characteristic curve analysis with 95% confidence interval for our previously derived TM score in which lower TM scores correspond with a higher likelihood of being a stroke mimic. Results-Based on final diagnosis at the end of the telestroke consultation, there were 630 of 1930 (32.6%) stroke mimics in the external validation cohort. All 6 variables included in the score were significantly different between patients with ischemic cerebrovascular disease versus stroke mimics. The TM score performed well (area under curve, 0.72; 95% confidence interval, 0.70-0.73; P<0.001), similar to our prior external validation in the Partners National Telestroke Network. Conclusions-The TM score's ability to predict the presence of a stroke mimic during telestroke consultation in these diverse cohorts was similar to its performance in our original cohort. Predictive decision-support tools like the TM score may help highlight key clinical differences between mimics and patients with stroke during complex, time-critical telestroke evaluations.

AB - Background and Purpose-Up to 30% of acute stroke evaluations are deemed stroke mimics, and these are common in telestroke as well. We recently published a risk prediction score for use during telestroke encounters to differentiate stroke mimics from ischemic cerebrovascular disease derived and validated in the Partners TeleStroke Network. Using data from 3 distinct US and European telestroke networks, we sought to externally validate the TeleStroke Mimic (TM) score in a broader population. Methods-We evaluated the TM score in 1930 telestroke consults from the University of Utah, Georgia Regents University, and the German TeleMedical Project for Integrative Stroke Care Network. We report the area under the curve in receiveroperating characteristic curve analysis with 95% confidence interval for our previously derived TM score in which lower TM scores correspond with a higher likelihood of being a stroke mimic. Results-Based on final diagnosis at the end of the telestroke consultation, there were 630 of 1930 (32.6%) stroke mimics in the external validation cohort. All 6 variables included in the score were significantly different between patients with ischemic cerebrovascular disease versus stroke mimics. The TM score performed well (area under curve, 0.72; 95% confidence interval, 0.70-0.73; P<0.001), similar to our prior external validation in the Partners National Telestroke Network. Conclusions-The TM score's ability to predict the presence of a stroke mimic during telestroke consultation in these diverse cohorts was similar to its performance in our original cohort. Predictive decision-support tools like the TM score may help highlight key clinical differences between mimics and patients with stroke during complex, time-critical telestroke evaluations.

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