Literature DB >> 25503550

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

Xia Wang1, Hisatomi Arima1, Rustam Al-Shahi Salman1, Mark Woodward1, Emma Heeley1, Christian Stapf1, Pablo M Lavados1, Thompson Robinson1, Yining Huang1, Jiguang Wang1, Candice Delcourt1, Craig S Anderson2.   

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.
© 2014 American Heart Association, Inc.

Entities:  

Keywords:  clinical trial; intracerebral hemorrhage

Mesh:

Year:  2014        PMID: 25503550     DOI: 10.1161/STROKEAHA.114.006910

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  26 in total

1.  Decompressive craniectomy for intracerebral haematoma: the influence of additional haematoma evacuation.

Authors:  Alexis Hadjiathanasiou; Patrick Schuss; Inja Ilic; Valeri Borger; Hartmut Vatter; Erdem Güresir
Journal:  Neurosurg Rev       Date:  2017-09-27       Impact factor: 3.042

2.  Association Between Hypodensities Detected by Computed Tomography and Hematoma Expansion in Patients With Intracerebral Hemorrhage.

Authors:  Gregoire Boulouis; Andrea Morotti; H Bart Brouwers; Andreas Charidimou; Michael J Jessel; Eitan Auriel; Octávio Pontes-Neto; Alison Ayres; Anastasia Vashkevich; Kristin M Schwab; Jonathan Rosand; Anand Viswanathan; Mahmut E Gurol; Steven M Greenberg; Joshua N Goldstein
Journal:  JAMA Neurol       Date:  2016-08-01       Impact factor: 18.302

3.  Intensive Care Unit Admission for Patients in the INTERACT2 ICH Blood Pressure Treatment Trial: Characteristics, Predictors, and Outcomes.

Authors:  Katja E Wartenberg; Xia Wang; Paula Muñoz-Venturelli; Alejandro A Rabinstein; Pablo M Lavados; Craig S Anderson; Thompson Robinson
Journal:  Neurocrit Care       Date:  2017-06       Impact factor: 3.210

4.  Combination of Intra-Hematomal Hypodensity on CT and BRAIN Scoring Improves Prediction of Hemorrhage Expansion in ICH.

Authors:  Joshua VanDerWerf; Donna Kurowski; James Siegler; Taneeta Ganguly; Brett Cucchiara
Journal:  Neurocrit Care       Date:  2018-08       Impact factor: 3.210

Review 5.  The Pathophysiology of Intracerebral Hemorrhage Formation and Expansion.

Authors:  Frieder Schlunk; Steven M Greenberg
Journal:  Transl Stroke Res       Date:  2015-06-16       Impact factor: 6.829

6.  Predicting Intracerebral Hemorrhage Expansion With Noncontrast Computed Tomography: The BAT Score.

Authors:  Andrea Morotti; Dar Dowlatshahi; Gregoire Boulouis; Fahad Al-Ajlan; Andrew M Demchuk; Richard I Aviv; Liyang Yu; Kristin Schwab; Javier M Romero; M Edip Gurol; Anand Viswanathan; Christopher D Anderson; Yuchiao Chang; Steven M Greenberg; Adnan I Qureshi; Jonathan Rosand; Joshua N Goldstein
Journal:  Stroke       Date:  2018-04-18       Impact factor: 7.914

Review 7.  Impact of Recent Studies for the Treatment of Intracerebral Hemorrhage.

Authors:  Jochen A Sembill; Hagen B Huttner; Joji B Kuramatsu
Journal:  Curr Neurol Neurosci Rep       Date:  2018-08-20       Impact factor: 5.081

8.  Noncontrast computer tomography-based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model.

Authors:  Huihui Xie; Shuai Ma; Xiaoying Wang; Xiaodong Zhang
Journal:  Eur Radiol       Date:  2019-08-05       Impact factor: 5.315

9.  External Validation of Hematoma Expansion Scores in Spontaneous Intracerebral Hemorrhage in an Asian Patient Cohort.

Authors:  Jia Xu Lim; Julian Xinguang Han; Angela An Qi See; Voon Hao Lew; Wan Ting Chock; Vin Fei Ban; Sohil Pothiawala; Winston Eng Hoe Lim; Louis Elliot McAdory; Michael Lucas James; Nicolas Kon Kam King
Journal:  Neurocrit Care       Date:  2019-04       Impact factor: 3.210

Review 10.  Predicting Intracerebral Hemorrhage Growth With the Spot Sign: The Effect of Onset-to-Scan Time.

Authors:  Dar Dowlatshahi; H Bart Brouwers; Andrew M Demchuk; Michael D Hill; Richard I Aviv; Lee-Anne Ufholz; Michael Reaume; Max Wintermark; J Claude Hemphill; Yasuo Murai; Yongjun Wang; Xingquan Zhao; Yilong Wang; Na Li; Takatoshi Sorimachi; Mitsunori Matsumae; Thorsten Steiner; Timolaos Rizos; Steven M Greenberg; Javier M Romero; Jonathan Rosand; Joshua N Goldstein; Mukul Sharma
Journal:  Stroke       Date:  2016-02-04       Impact factor: 7.914

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