The SOAR (Stroke subtype, Oxford Community Stroke Project classification, Age, prestroke modified Rankin) score strongly predicts early outcomes in acute stroke

Phyo Kyaw Myint, Allan B Clark, Chun Shing Kwok, John Davis, Ramesh Durairaj, Anand K Dixit, Anil K Sharma, Gary A Ford, John F Potter

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Background
Previous prognostic scoring systems in predicting stroke mortality are complex, require multiple measures that vary with time and failed to produce a simple scoring system.

Aims/Hypothesis
The study aims to derive and internally validate a stroke prognostic scoring system to predict early mortality and hospital length of stay.

Methods
Data from a UK multicenter stroke register were examined (1997-2010). Using a prior hypothesis based on our and others observations, we selected five patient-related factors (age, gender, stroke subtype, clinical classification, and prestroke disability) as candidate prognostic indicators. An 8-point score was derived based on multiple logistic regression model using four out of five variables. Performance of the model was assessed by plotting the estimated probability of in-hospital death against the actual probability by testing for overfitting (calibration) and area under the curve methods (discrimination).

Results
The total sample consisted of 12 355 acute stroke patients (ischemic stroke 91·0%). The score predicted both in-patient and seven-day mortality. The crude in-patient mortality were 1·57%, 4·02%, 10·65%, 21·41%, 46·60%, 62·72%, and 75·81% for those who scored 0, 1, 2, 3, 4, 5, and 6, respectively. The calibration of the model revealed no evidence of overfitting (estimated overfitting 0·001). The area under the curve values for both in-hospital and seven-day mortality were 0·79. The score predicted length of stay with a higher score was associated with longer median length of stay in those discharged alive and shorter median length of stay in those who died (P for both <0·001).

Conclusions
A simple 8-point clinical score is highly predictive of acute stroke mortality and length of hospital stay. It could be used as prognostic tool in service planning and also to risk-stratify patients to use these outcomes as markers of stroke care quality across institutions.
Original languageEnglish
Pages (from-to)278-283
Number of pages6
JournalInternational Journal of Stroke
Volume9
Issue number3
Early online date9 Jul 2013
DOIs
Publication statusPublished - Apr 2014

Fingerprint

Stroke
Length of Stay
Mortality
Calibration
Area Under Curve
Logistic Models
Quality of Health Care
Age Factors

Keywords

  • cardiovascular disease
  • length of stay
  • mortality
  • prognosis
  • prognosis score
  • stroke

Cite this

The SOAR (Stroke subtype, Oxford Community Stroke Project classification, Age, prestroke modified Rankin) score strongly predicts early outcomes in acute stroke. / Myint, Phyo Kyaw; Clark, Allan B; Kwok, Chun Shing; Davis, John; Durairaj, Ramesh; Dixit, Anand K; Sharma, Anil K; Ford, Gary A; Potter, John F.

In: International Journal of Stroke, Vol. 9, No. 3, 04.2014, p. 278-283.

Research output: Contribution to journalArticle

Myint, Phyo Kyaw ; Clark, Allan B ; Kwok, Chun Shing ; Davis, John ; Durairaj, Ramesh ; Dixit, Anand K ; Sharma, Anil K ; Ford, Gary A ; Potter, John F. / The SOAR (Stroke subtype, Oxford Community Stroke Project classification, Age, prestroke modified Rankin) score strongly predicts early outcomes in acute stroke. In: International Journal of Stroke. 2014 ; Vol. 9, No. 3. pp. 278-283.
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abstract = "BackgroundPrevious prognostic scoring systems in predicting stroke mortality are complex, require multiple measures that vary with time and failed to produce a simple scoring system.Aims/HypothesisThe study aims to derive and internally validate a stroke prognostic scoring system to predict early mortality and hospital length of stay.MethodsData from a UK multicenter stroke register were examined (1997-2010). Using a prior hypothesis based on our and others observations, we selected five patient-related factors (age, gender, stroke subtype, clinical classification, and prestroke disability) as candidate prognostic indicators. An 8-point score was derived based on multiple logistic regression model using four out of five variables. Performance of the model was assessed by plotting the estimated probability of in-hospital death against the actual probability by testing for overfitting (calibration) and area under the curve methods (discrimination).ResultsThe total sample consisted of 12 355 acute stroke patients (ischemic stroke 91·0{\%}). The score predicted both in-patient and seven-day mortality. The crude in-patient mortality were 1·57{\%}, 4·02{\%}, 10·65{\%}, 21·41{\%}, 46·60{\%}, 62·72{\%}, and 75·81{\%} for those who scored 0, 1, 2, 3, 4, 5, and 6, respectively. The calibration of the model revealed no evidence of overfitting (estimated overfitting 0·001). The area under the curve values for both in-hospital and seven-day mortality were 0·79. The score predicted length of stay with a higher score was associated with longer median length of stay in those discharged alive and shorter median length of stay in those who died (P for both <0·001).ConclusionsA simple 8-point clinical score is highly predictive of acute stroke mortality and length of hospital stay. It could be used as prognostic tool in service planning and also to risk-stratify patients to use these outcomes as markers of stroke care quality across institutions.",
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T1 - The SOAR (Stroke subtype, Oxford Community Stroke Project classification, Age, prestroke modified Rankin) score strongly predicts early outcomes in acute stroke

AU - Myint, Phyo Kyaw

AU - Clark, Allan B

AU - Kwok, Chun Shing

AU - Davis, John

AU - Durairaj, Ramesh

AU - Dixit, Anand K

AU - Sharma, Anil K

AU - Ford, Gary A

AU - Potter, John F

N1 - © 2013 The Authors. International Journal of Stroke © 2013 World Stroke Organization.

PY - 2014/4

Y1 - 2014/4

N2 - BackgroundPrevious prognostic scoring systems in predicting stroke mortality are complex, require multiple measures that vary with time and failed to produce a simple scoring system.Aims/HypothesisThe study aims to derive and internally validate a stroke prognostic scoring system to predict early mortality and hospital length of stay.MethodsData from a UK multicenter stroke register were examined (1997-2010). Using a prior hypothesis based on our and others observations, we selected five patient-related factors (age, gender, stroke subtype, clinical classification, and prestroke disability) as candidate prognostic indicators. An 8-point score was derived based on multiple logistic regression model using four out of five variables. Performance of the model was assessed by plotting the estimated probability of in-hospital death against the actual probability by testing for overfitting (calibration) and area under the curve methods (discrimination).ResultsThe total sample consisted of 12 355 acute stroke patients (ischemic stroke 91·0%). The score predicted both in-patient and seven-day mortality. The crude in-patient mortality were 1·57%, 4·02%, 10·65%, 21·41%, 46·60%, 62·72%, and 75·81% for those who scored 0, 1, 2, 3, 4, 5, and 6, respectively. The calibration of the model revealed no evidence of overfitting (estimated overfitting 0·001). The area under the curve values for both in-hospital and seven-day mortality were 0·79. The score predicted length of stay with a higher score was associated with longer median length of stay in those discharged alive and shorter median length of stay in those who died (P for both <0·001).ConclusionsA simple 8-point clinical score is highly predictive of acute stroke mortality and length of hospital stay. It could be used as prognostic tool in service planning and also to risk-stratify patients to use these outcomes as markers of stroke care quality across institutions.

AB - BackgroundPrevious prognostic scoring systems in predicting stroke mortality are complex, require multiple measures that vary with time and failed to produce a simple scoring system.Aims/HypothesisThe study aims to derive and internally validate a stroke prognostic scoring system to predict early mortality and hospital length of stay.MethodsData from a UK multicenter stroke register were examined (1997-2010). Using a prior hypothesis based on our and others observations, we selected five patient-related factors (age, gender, stroke subtype, clinical classification, and prestroke disability) as candidate prognostic indicators. An 8-point score was derived based on multiple logistic regression model using four out of five variables. Performance of the model was assessed by plotting the estimated probability of in-hospital death against the actual probability by testing for overfitting (calibration) and area under the curve methods (discrimination).ResultsThe total sample consisted of 12 355 acute stroke patients (ischemic stroke 91·0%). The score predicted both in-patient and seven-day mortality. The crude in-patient mortality were 1·57%, 4·02%, 10·65%, 21·41%, 46·60%, 62·72%, and 75·81% for those who scored 0, 1, 2, 3, 4, 5, and 6, respectively. The calibration of the model revealed no evidence of overfitting (estimated overfitting 0·001). The area under the curve values for both in-hospital and seven-day mortality were 0·79. The score predicted length of stay with a higher score was associated with longer median length of stay in those discharged alive and shorter median length of stay in those who died (P for both <0·001).ConclusionsA simple 8-point clinical score is highly predictive of acute stroke mortality and length of hospital stay. It could be used as prognostic tool in service planning and also to risk-stratify patients to use these outcomes as markers of stroke care quality across institutions.

KW - cardiovascular disease

KW - length of stay

KW - mortality

KW - prognosis

KW - prognosis score

KW - stroke

U2 - 10.1111/ijs.12088

DO - 10.1111/ijs.12088

M3 - Article

C2 - 23834262

VL - 9

SP - 278

EP - 283

JO - International Journal of Stroke

JF - International Journal of Stroke

SN - 1747-4930

IS - 3

ER -