Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage

INTERACT Investigators; Xia Wang; Hisatomi Arima; Rustam Al-Shahi Salman; Mark Woodward; Emma Heeley; Christian Stapf; Pablo M Lavados; Thompson Robinson; Yining Huang; Jiguang Wang; Candice Delcourt; Craig S Anderson

doi:10.1161/STROKEAHA.114.006910

Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage

INTERACT Investigators
, Xia Wang
, Hisatomi Arima
, Rustam Al-Shahi Salman
, Mark Woodward
, Emma Heeley
, Christian Stapf
, Pablo M Lavados
, Thompson Robinson
, Yining Huang
, Jiguang Wang
, Candice Delcourt
, Craig S Anderson

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

Abstract

BACKGROUND AND PURPOSE: We developed and validated a simple algorithm to predict the risk of hematoma growth in acute spontaneous intracerebral hemorrhage (ICH) to better inform clinicians and researchers in their efforts to improve outcomes for patients.

METHODS: We analyzed data from the computed tomography substudies of the pilot and main phases of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trials (INTERACT1 and 2, respectively). The study group was divided into a derivation cohort (INTERACT2, n=964) and a validation cohort (INTERACT1, n=346). Multivariable logistic regression was used to identify factors associated with clinically significant (≥6 mL) increase in hematoma volume at 24 hours after symptom onset. A parsimonious risk score was developed on the basis of regression coefficients derived from the logistic model.

RESULTS: A 24-point BRAIN score was derived from INTERACT2 (C-statistic, 0.73) based on baseline ICH volume (mL per score, ≤10=0, 10-20=5, >20=7), recurrent ICH (yes=4), anticoagulation with warfarin at symptom onset (yes=6), intraventricular extension (yes=2), and number of hours to baseline computed tomography from symptom onset (≤1=5, 1-2=4, 2-3=3, 3-4=2, 4-5=1, >5=0) predicted the probability of ICH growth (ranging from 3.4% for 0 point to 85.8% for 24 points) with good discrimination (C-statistic, 0.73) and calibration (Hosmer-Lemeshow P=0.82) in INTERACT1.

CONCLUSIONS: The simple BRAIN score predicts the probability of hematoma growth in ICH. This could be used to improve risk stratification for research and clinical practice.

CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00226096 and NCT00716079.

Original language	English
Pages (from-to)	376-81
Number of pages	6
Journal	Stroke; a journal of cerebral circulation
Volume	46
Issue number	2
DOIs	https://doi.org/10.1161/STROKEAHA.114.006910
Publication status	Published - Feb 2015

Keywords / Materials (for Non-textual outputs)

Acute Disease
Aged
Algorithms
Brain
Cerebral Hemorrhage
Cohort Studies
Female
Hematoma
Humans
Internationality
Male
Middle Aged
Predictive Value of Tests
Risk Factors
Single-Blind Method

Access to Document

10.1161/STROKEAHA.114.006910

Globalising the BHF REstart or STop Antithrombotics Randomised Trial (RESTART)
Salman, R. (Principal Investigator)
UK-based charities
9/12/13 → 27/06/14
Project: Research

Cite this

INTERACT Investigators, Wang, X., Arima, H., Al-Shahi Salman, R., Woodward, M., Heeley, E., Stapf, C., Lavados, P. M., Robinson, T., Huang, Y., Wang, J., Delcourt, C., & Anderson, C. S. (2015). Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage. Stroke; a journal of cerebral circulation, 46(2), 376-81. https://doi.org/10.1161/STROKEAHA.114.006910

@article{4f4079c94be6435e82cd30195bd85f52,

title = "Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage",

abstract = "BACKGROUND AND PURPOSE: We developed and validated a simple algorithm to predict the risk of hematoma growth in acute spontaneous intracerebral hemorrhage (ICH) to better inform clinicians and researchers in their efforts to improve outcomes for patients.METHODS: We analyzed data from the computed tomography substudies of the pilot and main phases of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trials (INTERACT1 and 2, respectively). The study group was divided into a derivation cohort (INTERACT2, n=964) and a validation cohort (INTERACT1, n=346). Multivariable logistic regression was used to identify factors associated with clinically significant (≥6 mL) increase in hematoma volume at 24 hours after symptom onset. A parsimonious risk score was developed on the basis of regression coefficients derived from the logistic model.RESULTS: A 24-point BRAIN score was derived from INTERACT2 (C-statistic, 0.73) based on baseline ICH volume (mL per score, ≤10=0, 10-20=5, >20=7), recurrent ICH (yes=4), anticoagulation with warfarin at symptom onset (yes=6), intraventricular extension (yes=2), and number of hours to baseline computed tomography from symptom onset (≤1=5, 1-2=4, 2-3=3, 3-4=2, 4-5=1, >5=0) predicted the probability of ICH growth (ranging from 3.4\% for 0 point to 85.8\% for 24 points) with good discrimination (C-statistic, 0.73) and calibration (Hosmer-Lemeshow P=0.82) in INTERACT1.CONCLUSIONS: The simple BRAIN score predicts the probability of hematoma growth in ICH. This could be used to improve risk stratification for research and clinical practice.CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00226096 and NCT00716079.",

keywords = "Acute Disease, Aged, Algorithms, Brain, Cerebral Hemorrhage, Cohort Studies, Female, Hematoma, Humans, Internationality, Male, Middle Aged, Predictive Value of Tests, Risk Factors, Single-Blind Method",

author = "\{INTERACT Investigators\} and Xia Wang and Hisatomi Arima and \{Al-Shahi Salman\}, Rustam and Mark Woodward and Emma Heeley and Christian Stapf and Lavados, \{Pablo M\} and Thompson Robinson and Yining Huang and Jiguang Wang and Candice Delcourt and Anderson, \{Craig S\}",

note = "{\textcopyright} 2014 American Heart Association, Inc.",

year = "2015",

month = feb,

doi = "10.1161/STROKEAHA.114.006910",

language = "English",

volume = "46",

pages = "376--81",

journal = "Stroke; a journal of cerebral circulation",

issn = "0039-2499",

publisher = "Wolters Kluwer Health",

number = "2",

}

INTERACT Investigators, Wang, X, Arima, H, Al-Shahi Salman, R, Woodward, M, Heeley, E, Stapf, C, Lavados, PM, Robinson, T, Huang, Y, Wang, J, Delcourt, C & Anderson, CS 2015, 'Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage', Stroke; a journal of cerebral circulation, vol. 46, no. 2, pp. 376-81. https://doi.org/10.1161/STROKEAHA.114.006910

TY - JOUR

T1 - Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage

AU - INTERACT Investigators

AU - Wang, Xia

AU - Arima, Hisatomi

AU - Al-Shahi Salman, Rustam

AU - Woodward, Mark

AU - Heeley, Emma

AU - Stapf, Christian

AU - Lavados, Pablo M

AU - Robinson, Thompson

AU - Huang, Yining

AU - Wang, Jiguang

AU - Delcourt, Candice

AU - Anderson, Craig S

PY - 2015/2

Y1 - 2015/2

N2 - BACKGROUND AND PURPOSE: We developed and validated a simple algorithm to predict the risk of hematoma growth in acute spontaneous intracerebral hemorrhage (ICH) to better inform clinicians and researchers in their efforts to improve outcomes for patients.METHODS: We analyzed data from the computed tomography substudies of the pilot and main phases of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trials (INTERACT1 and 2, respectively). The study group was divided into a derivation cohort (INTERACT2, n=964) and a validation cohort (INTERACT1, n=346). Multivariable logistic regression was used to identify factors associated with clinically significant (≥6 mL) increase in hematoma volume at 24 hours after symptom onset. A parsimonious risk score was developed on the basis of regression coefficients derived from the logistic model.RESULTS: A 24-point BRAIN score was derived from INTERACT2 (C-statistic, 0.73) based on baseline ICH volume (mL per score, ≤10=0, 10-20=5, >20=7), recurrent ICH (yes=4), anticoagulation with warfarin at symptom onset (yes=6), intraventricular extension (yes=2), and number of hours to baseline computed tomography from symptom onset (≤1=5, 1-2=4, 2-3=3, 3-4=2, 4-5=1, >5=0) predicted the probability of ICH growth (ranging from 3.4% for 0 point to 85.8% for 24 points) with good discrimination (C-statistic, 0.73) and calibration (Hosmer-Lemeshow P=0.82) in INTERACT1.CONCLUSIONS: The simple BRAIN score predicts the probability of hematoma growth in ICH. This could be used to improve risk stratification for research and clinical practice.CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00226096 and NCT00716079.

AB - BACKGROUND AND PURPOSE: We developed and validated a simple algorithm to predict the risk of hematoma growth in acute spontaneous intracerebral hemorrhage (ICH) to better inform clinicians and researchers in their efforts to improve outcomes for patients.METHODS: We analyzed data from the computed tomography substudies of the pilot and main phases of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trials (INTERACT1 and 2, respectively). The study group was divided into a derivation cohort (INTERACT2, n=964) and a validation cohort (INTERACT1, n=346). Multivariable logistic regression was used to identify factors associated with clinically significant (≥6 mL) increase in hematoma volume at 24 hours after symptom onset. A parsimonious risk score was developed on the basis of regression coefficients derived from the logistic model.RESULTS: A 24-point BRAIN score was derived from INTERACT2 (C-statistic, 0.73) based on baseline ICH volume (mL per score, ≤10=0, 10-20=5, >20=7), recurrent ICH (yes=4), anticoagulation with warfarin at symptom onset (yes=6), intraventricular extension (yes=2), and number of hours to baseline computed tomography from symptom onset (≤1=5, 1-2=4, 2-3=3, 3-4=2, 4-5=1, >5=0) predicted the probability of ICH growth (ranging from 3.4% for 0 point to 85.8% for 24 points) with good discrimination (C-statistic, 0.73) and calibration (Hosmer-Lemeshow P=0.82) in INTERACT1.CONCLUSIONS: The simple BRAIN score predicts the probability of hematoma growth in ICH. This could be used to improve risk stratification for research and clinical practice.CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00226096 and NCT00716079.

KW - Acute Disease

KW - Aged

KW - Algorithms

KW - Brain

KW - Cerebral Hemorrhage

KW - Cohort Studies

KW - Female

KW - Hematoma

KW - Humans

KW - Internationality

KW - Male

KW - Middle Aged

KW - Predictive Value of Tests

KW - Risk Factors

KW - Single-Blind Method

U2 - 10.1161/STROKEAHA.114.006910

DO - 10.1161/STROKEAHA.114.006910

M3 - Article

C2 - 25503550

SN - 0039-2499

VL - 46

SP - 376

EP - 381

JO - Stroke; a journal of cerebral circulation

JF - Stroke; a journal of cerebral circulation

IS - 2

ER -

Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage

Abstract

Keywords / Materials (for Non-textual outputs)

Access to Document

Fingerprint

Projects

Globalising the BHF REstart or STop Antithrombotics Randomised Trial (RESTART)

Cite this