Literature DB >> 27601380

Noncontrast Computed Tomography Hypodensities Predict Poor Outcome in Intracerebral Hemorrhage Patients.

Gregoire Boulouis1, Andrea Morotti2, H Bart Brouwers2, Andreas Charidimou2, Michael J Jessel2, Eitan Auriel2, Octavio Pontes-Neto2, Alison Ayres2, Anastasia Vashkevich2, Kristin M Schwab2, Jonathan Rosand2, Anand Viswanathan2, Mahmut E Gurol2, Steven M Greenberg2, Joshua N Goldstein2.   

Abstract

BACKGROUND AND
PURPOSE: Noncontrast computed tomographic (CT) hypodensities have been shown to be associated with hematoma expansion in intracerebral hemorrhage (ICH), but their impact on functional outcome is yet to be determined. We evaluated whether baseline noncontrast CT hypodensities are associated with poor clinical outcome.
METHODS: We performed a retrospective review of a prospectively collected cohort of consecutive patients with primary ICH presenting to a single academic medical center between 1994 and 2016. The presence of CT hypodensities was assessed by 2 independent raters on the baseline CT. Unfavorable outcome was defined as a modified Rankin score >3 at 90 days. The associations between CT hypodensities and unfavorable outcome were investigated using uni- and multivariable logistic regression models.
RESULTS: During the study period, 1342 patients presented with ICH and 800 met restrictive inclusion criteria (baseline CT available for review, and 90-day outcome available). Three hundred and four (38%) patients showed hypodensities on CT, and 520 (65%) patients experienced unfavorable outcome. In univariate analysis, patients with unfavorable outcome were more likely to demonstrate hypodensities (48% versus 20%; P<0.0001). After adjustment for age, admission Glasgow coma scale, warfarin use, intraventricular hemorrhage, baseline ICH volume, and location, CT hypodensities were found to be independently associated with an increase in the odds of unfavorable outcome (odds ratio 1.70, 95% confidence interval [1.10-2.65]; P=0.018).
CONCLUSIONS: The presence of noncontract CT hypodensities at baseline independently predicts poor outcome and comes as a useful and widely available addition to our ability to predict ICH patients' clinical evolution.
© 2016 American Heart Association, Inc.

Entities:  

Keywords:  computed tomography; hematoma expansion; intracerebral hemorrhage; morbidity/mortality; prognosis

Mesh:

Year:  2016        PMID: 27601380      PMCID: PMC5039101          DOI: 10.1161/STROKEAHA.116.014425

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


  23 in total

1.  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

2.  The HEP Score: A Nomogram-Derived Hematoma Expansion Prediction Scale.

Authors:  Xiaoying Yao; Ye Xu; Erica Siwila-Sackman; Bo Wu; Magdy Selim
Journal:  Neurocrit Care       Date:  2015-10       Impact factor: 3.210

3.  Blend Sign on Computed Tomography: Novel and Reliable Predictor for Early Hematoma Growth in Patients With Intracerebral Hemorrhage.

Authors:  Qi Li; Gang Zhang; Yuan-Jun Huang; Mei-Xue Dong; Fa-Jin Lv; Xiao Wei; Jian-Jun Chen; Li-Juan Zhang; Xin-Yue Qin; Peng Xie
Journal:  Stroke       Date:  2015-06-18       Impact factor: 7.914

4.  Density and shape as CT predictors of intracerebral hemorrhage growth.

Authors:  Christen D Barras; Brian M Tress; Soren Christensen; Lachlan MacGregor; Marnie Collins; Patricia M Desmond; Brett E Skolnick; Stephan A Mayer; Joseph P Broderick; Michael N Diringer; Thorsten Steiner; Stephen M Davis
Journal:  Stroke       Date:  2009-03-12       Impact factor: 7.914

5.  Systematic characterization of the computed tomography angiography spot sign in primary intracerebral hemorrhage identifies patients at highest risk for hematoma expansion: the spot sign score.

Authors:  Josser E Delgado Almandoz; Albert J Yoo; Michael J Stone; Pamela W Schaefer; Joshua N Goldstein; Jonathan Rosand; Alexandra Oleinik; Michael H Lev; R Gilberto Gonzalez; Javier M Romero
Journal:  Stroke       Date:  2009-07-02       Impact factor: 7.914

6.  Timing of Occurrence Is the Most Important Characteristic of Spot Sign.

Authors:  Binli Wang; Shenqiang Yan; Mengjun Xu; Sheng Zhang; Keqin Liu; Haitao Hu; Magdy Selim; Min Lou
Journal:  Stroke       Date:  2016-03-29       Impact factor: 7.914

7.  Early neurologic deterioration in intracerebral hemorrhage: predictors and associated factors.

Authors:  R Leira; A Dávalos; Y Silva; A Gil-Peralta; J Tejada; M Garcia; J Castillo
Journal:  Neurology       Date:  2004-08-10       Impact factor: 9.910

8.  Clinician judgment vs formal scales for predicting intracerebral hemorrhage outcomes.

Authors:  David Y Hwang; Cameron A Dell; Mary J Sparks; Tiffany D Watson; Carl D Langefeld; Mary E Comeau; Jonathan Rosand; Thomas W K Battey; Sebastian Koch; Mario L Perez; Michael L James; Jessica McFarlin; Jennifer L Osborne; Daniel Woo; Steven J Kittner; Kevin N Sheth
Journal:  Neurology       Date:  2015-12-16       Impact factor: 9.910

9.  Quantitative CT densitometry for predicting intracerebral hemorrhage growth.

Authors:  C D Barras; B M Tress; S Christensen; M Collins; P M Desmond; B E Skolnick; S A Mayer; S M Davis
Journal:  AJNR Am J Neuroradiol       Date:  2013-01-10       Impact factor: 3.825

10.  Swirl sign in intracerebral haemorrhage: definition, prevalence, reliability and prognostic value.

Authors:  Eufrozina Selariu; Elisabet Zia; Marco Brizzi; Kasim Abul-Kasim
Journal:  BMC Neurol       Date:  2012-09-26       Impact factor: 2.474

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  22 in total

1.  Defining the Optimal Midline Shift Threshold to Predict Poor Outcome in Patients with Supratentorial Spontaneous Intracerebral Hemorrhage.

Authors:  Wen-Song Yang; Qi Li; Rui Li; Qing-Jun Liu; Xing-Chen Wang; Li-Bo Zhao; Peng Xie
Journal:  Neurocrit Care       Date:  2018-06       Impact factor: 3.210

Review 2.  Computed Tomography Imaging Predictors of Intracerebral Hemorrhage Expansion.

Authors:  Xin-Ni Lv; Lan Deng; Wen-Song Yang; Xiao Wei; Qi Li
Journal:  Curr Neurol Neurosci Rep       Date:  2021-03-12       Impact factor: 5.081

Review 3.  Noncontrast Computed Tomography Markers of Intracerebral Hemorrhage Expansion.

Authors:  Gregoire Boulouis; Andrea Morotti; Andreas Charidimou; Dar Dowlatshahi; Joshua N Goldstein
Journal:  Stroke       Date:  2017-03-13       Impact factor: 7.914

4.  Blood pressure reduction and noncontrast CT markers of intracerebral hemorrhage expansion.

Authors:  Andrea Morotti; Gregoire Boulouis; Javier M Romero; H Bart Brouwers; Michael J Jessel; Anastasia Vashkevich; Kristin Schwab; Mohammad Rauf Afzal; Christy Cassarly; Steven M Greenberg; Reneé Hebert Martin; Adnan I Qureshi; Jonathan Rosand; Joshua N Goldstein
Journal:  Neurology       Date:  2017-07-12       Impact factor: 9.910

5.  Location of intracerebral haemorrhage predicts haematoma expansion.

Authors:  Vignan Yogendrakumar; Andrew M Demchuk; Richard I Aviv; David Rodriguez-Luna; Carlos A Molina; Yolanda S Blas; Imanuel Dzialowski; Adam Kobayashi; Jean-Martin Boulanger; Cheemun Lum; Gord Gubitz; Vasantha Padma; Jayanta Roy; Carlos S Kase; Rohit Bhatia; Michael D Hill; Dar Dowlatshahi
Journal:  Eur Stroke J       Date:  2017-06-15

6.  Expansion-Prone Hematoma: Defining a Population at High Risk of Hematoma Growth and Poor Outcome.

Authors:  Qi Li; Yi-Qing Shen; Xiong-Fei Xie; Meng-Zhou Xue; Du Cao; Wen-Song Yang; Rui Li; Lan Deng; Miao Wei; Fa-Jin Lv; Guo-Feng Wu; Zhou-Ping Tang; Peng Xie
Journal:  Neurocrit Care       Date:  2019-06       Impact factor: 3.210

7.  Blend sign predicts poor outcome in patients with intracerebral hemorrhage.

Authors:  Qi Li; Wen-Song Yang; Xing-Chen Wang; Du Cao; Dan Zhu; Fa-Jin Lv; Yang Liu; Liang Yuan; Gang Zhang; Xin Xiong; Rui Li; Yun-Xin Hu; Xin-Yue Qin; Peng Xie
Journal:  PLoS One       Date:  2017-08-22       Impact factor: 3.240

8.  Exploration of Multiparameter Hematoma 3D Image Analysis for Predicting Outcome After Intracerebral Hemorrhage.

Authors:  Pascal Salazar; Mario Di Napoli; Mostafa Jafari; Alibay Jafarli; Wendy Ziai; Alexander Petersen; Stephan A Mayer; Eric M Bershad; Rahul Damani; Afshin A Divani
Journal:  Neurocrit Care       Date:  2020-04       Impact factor: 3.210

9.  The new Hematoma Maturity Score is highly associated with poor clinical outcome in spontaneous intracerebral hemorrhage.

Authors:  Elena Serrano; Antonio López-Rueda; Javier Moreno; Alejandro Rodríguez; Laura Llull; Christian Zwanzger; Laura Oleaga; Sergi Amaro
Journal:  Eur Radiol       Date:  2021-06-20       Impact factor: 5.315

10.  Admission computed tomography radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH-2 trial intracerebral hemorrhage population.

Authors:  Stefan P Haider; Adnan I Qureshi; Abhi Jain; Hishan Tharmaseelan; Elisa R Berson; Tal Zeevi; Shahram Majidi; Christopher G Filippi; Simon Iseke; Moritz Gross; Julian N Acosta; Ajay Malhotra; Jennifer A Kim; Lauren H Sansing; Guido J Falcone; Kevin N Sheth; Seyedmehdi Payabvash
Journal:  Eur J Neurol       Date:  2021-07-18       Impact factor: 6.288

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