Parametric Modeling of Stroke Recurrence

M. A. Foulkes; R. L. Sacco; J. P. Mohr; D. B. Hier; T. R. Price; P. A. Wolf; Daniel Hier

doi:10.1159/000110354

Parametric Modeling of Stroke Recurrence

M. A. Foulkes
, R. L. Sacco
, J. P. Mohr
, D. B. Hier
, T. R. Price
, P. A. Wolf
, Daniel Hier

Missouri University of Science and Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Stroke Recurrence Has Been Investigated Primarily with Respect to Prognostic Factors Predictive of Recurrence. Several Parametric Functions Are Considered in Modeling the Distribution of Ischemic Stroke Recurrences Recorded within the Stroke Data Bank. a Linear Hazard Function is Shown to Be the Best- Fitting Function among Those Considered. This Method of Parametric Modeling May Lead to a More Informed Approach to Treatment of Ischemic Stroke and Secondary Prevention and May Enhance Future Investigations of Prognostic Factors as Well. © 1994 S. Karger AG, Basel.

Original language	American English
Journal	Neuroepidemiology
Volume	13
DOIs	https://doi.org/10.1159/000110354
State	Published - Jan 1 1994

Keywords

Ischemic stroke
Mathematical modeling
Recurrence

Disciplines

Chemistry

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https://doi.org/10.1159/000110354

Cite this

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title = "Parametric Modeling of Stroke Recurrence",

abstract = " Stroke Recurrence Has Been Investigated Primarily with Respect to Prognostic Factors Predictive of Recurrence. Several Parametric Functions Are Considered in Modeling the Distribution of Ischemic Stroke Recurrences Recorded within the Stroke Data Bank. a Linear Hazard Function is Shown to Be the Best- Fitting Function among Those Considered. This Method of Parametric Modeling May Lead to a More Informed Approach to Treatment of Ischemic Stroke and Secondary Prevention and May Enhance Future Investigations of Prognostic Factors as Well. {\textcopyright} 1994 S. Karger AG, Basel.",

keywords = "Ischemic stroke, Mathematical modeling, Recurrence",

author = "Foulkes, \{M. A.\} and Sacco, \{R. L.\} and Mohr, \{J. P.\} and Hier, \{D. B.\} and Price, \{T. R.\} and Wolf, \{P. A.\} and Daniel Hier",

year = "1994",

month = jan,

day = "1",

doi = "10.1159/000110354",

language = "American English",

volume = "13",

journal = "Neuroepidemiology",

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TY - JOUR

T1 - Parametric Modeling of Stroke Recurrence

AU - Foulkes, M. A.

AU - Sacco, R. L.

AU - Mohr, J. P.

AU - Hier, D. B.

AU - Price, T. R.

AU - Wolf, P. A.

AU - Hier, Daniel

PY - 1994/1/1

Y1 - 1994/1/1

N2 - Stroke Recurrence Has Been Investigated Primarily with Respect to Prognostic Factors Predictive of Recurrence. Several Parametric Functions Are Considered in Modeling the Distribution of Ischemic Stroke Recurrences Recorded within the Stroke Data Bank. a Linear Hazard Function is Shown to Be the Best- Fitting Function among Those Considered. This Method of Parametric Modeling May Lead to a More Informed Approach to Treatment of Ischemic Stroke and Secondary Prevention and May Enhance Future Investigations of Prognostic Factors as Well. © 1994 S. Karger AG, Basel.

AB - Stroke Recurrence Has Been Investigated Primarily with Respect to Prognostic Factors Predictive of Recurrence. Several Parametric Functions Are Considered in Modeling the Distribution of Ischemic Stroke Recurrences Recorded within the Stroke Data Bank. a Linear Hazard Function is Shown to Be the Best- Fitting Function among Those Considered. This Method of Parametric Modeling May Lead to a More Informed Approach to Treatment of Ischemic Stroke and Secondary Prevention and May Enhance Future Investigations of Prognostic Factors as Well. © 1994 S. Karger AG, Basel.

KW - Ischemic stroke

KW - Mathematical modeling

KW - Recurrence

UR - https://scholarsmine.mst.edu/chem_facwork/3287

UR - https://doi.org/10.1159/000110354

U2 - 10.1159/000110354

DO - 10.1159/000110354

M3 - Article

C2 - 8190202

VL - 13

JO - Neuroepidemiology

JF - Neuroepidemiology

ER -

Parametric Modeling of Stroke Recurrence

Abstract

Keywords

Disciplines

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