Mismatch between midline shift and hematoma thickness as a prognostic factor of mortality in patients sustaining acute subdural hematoma.

brain edema brain injuries prognosis traumatic

Journal

Trauma surgery & acute care open
ISSN: 2397-5776
Titre abrégé: Trauma Surg Acute Care Open
Pays: England
ID NLM: 101698646

Informations de publication

Date de publication:
2021
Historique:
received: 08 02 2021
revised: 05 04 2021
accepted: 11 04 2021
entrez: 9 6 2021
pubmed: 10 6 2021
medline: 10 6 2021
Statut: epublish

Résumé

Acute subdural hematoma (ASDH) is a traumatic lesion commonly found secondary to traumatic brain injury. Radiological findings on CT, such as hematoma thickness (HT) and structures midline shift (MLS), have an important prognostic role in this disease. The relationship between HT and MLS has been rarely studied in the literature. Thus, this study aimed to assess the prognostic accuracy of the difference between MLS and HT for acute outcomes in patients with ASDH in a low-income to middle-income country. This was a post-hoc analysis of a prospective cohort study conducted in a university-associated tertiary-level hospital in Brazil. The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis) statement guidelines were followed. The difference values between MLS and HT (Zumkeller index, ZI) were divided into three categories (<0.00, 0.01-3, and >3). Logistic regression analyses were performed to reveal the OR of categorized ZI in predicting primary outcome measures. A Cox regression was also performed and the results were presented through HR. The discriminative ability of three multivariate models including clinical and radiological variables (ZI, Rotterdam score, and Helsinki score) was demonstrated. A total of 114 patients were included. Logistic regression demonstrated an OR value equal to 8.12 for the ZI >3 category (OR 8.12, 95% CI 1.16 to 40.01; p=0.01), which proved to be an independent predictor of mortality in the adjusted model for surgical intervention, age, and Glasgow Coma Scale (GCS) score. Cox regression analysis demonstrated that this category was associated with 14-day survival (HR 2.92, 95% CI 1.38 to 6.16; p=0.005). A multivariate analysis performed for three models including age and GCS with categorized ZI or Helsinki or Rotterdam score demonstrated area under the receiver operating characteristic curve values of 0.745, 0.767, and 0.808, respectively. The present study highlights the potential usefulness of the difference between MLS and HT as a prognostic variable in patients with ASDH. Level III, epidemiological study.

Sections du résumé

BACKGROUND BACKGROUND
Acute subdural hematoma (ASDH) is a traumatic lesion commonly found secondary to traumatic brain injury. Radiological findings on CT, such as hematoma thickness (HT) and structures midline shift (MLS), have an important prognostic role in this disease. The relationship between HT and MLS has been rarely studied in the literature. Thus, this study aimed to assess the prognostic accuracy of the difference between MLS and HT for acute outcomes in patients with ASDH in a low-income to middle-income country.
METHODS METHODS
This was a post-hoc analysis of a prospective cohort study conducted in a university-associated tertiary-level hospital in Brazil. The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis) statement guidelines were followed. The difference values between MLS and HT (Zumkeller index, ZI) were divided into three categories (<0.00, 0.01-3, and >3). Logistic regression analyses were performed to reveal the OR of categorized ZI in predicting primary outcome measures. A Cox regression was also performed and the results were presented through HR. The discriminative ability of three multivariate models including clinical and radiological variables (ZI, Rotterdam score, and Helsinki score) was demonstrated.
RESULTS RESULTS
A total of 114 patients were included. Logistic regression demonstrated an OR value equal to 8.12 for the ZI >3 category (OR 8.12, 95% CI 1.16 to 40.01; p=0.01), which proved to be an independent predictor of mortality in the adjusted model for surgical intervention, age, and Glasgow Coma Scale (GCS) score. Cox regression analysis demonstrated that this category was associated with 14-day survival (HR 2.92, 95% CI 1.38 to 6.16; p=0.005). A multivariate analysis performed for three models including age and GCS with categorized ZI or Helsinki or Rotterdam score demonstrated area under the receiver operating characteristic curve values of 0.745, 0.767, and 0.808, respectively.
CONCLUSIONS CONCLUSIONS
The present study highlights the potential usefulness of the difference between MLS and HT as a prognostic variable in patients with ASDH.
LEVEL OF EVIDENCE METHODS
Level III, epidemiological study.

Identifiants

pubmed: 34104799
doi: 10.1136/tsaco-2021-000707
pii: tsaco-2021-000707
pmc: PMC8144027
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e000707

Informations de copyright

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: DJFS reports grants and non-financial support from National Institute for Health Research (NIHR), during the conduct of the study. RLOdA reports grants from the National Council for Scientific and Technological Development (CNPq), Brazil, during the conduct of the study. AGK reports grants and non-financial support from NIHR, grants and non-financial support from the School of Clinical Medicine, University of Cambridge, and grants and non-financial support from Royal College of Surgeons of England, during the conduct of the study. WSP reports grants and non-financial support from NIHR, during the conduct of the study.

Références

J Neurosurg. 1995 Sep;83(3):445-52
pubmed: 7666221
PLoS Med. 2008 Aug 5;5(8):e165; discussion e165
pubmed: 18684008
Scand J Trauma Resusc Emerg Med. 2011 Oct 24;19:62
pubmed: 22024376
Neurosurg Rev. 2018 Apr;41(2):483-488
pubmed: 28685310
World Neurosurg. 2012 Sep-Oct;78(3-4):306-11
pubmed: 22120569
Br Med J (Clin Res Ed). 1983 Oct 22;287(6400):1173-6
pubmed: 6414615
World Neurosurg. 2011 May-Jun;75(5-6):586-91
pubmed: 21704911
World Neurosurg. 2019 Jun;126:e944-e952
pubmed: 30876998
Nat Rev Neurol. 2013 Apr;9(4):231-6
pubmed: 23443846
Biometrics. 1988 Sep;44(3):837-45
pubmed: 3203132
Lancet Neurol. 2019 Feb;18(2):136-137
pubmed: 30663604
BMJ. 2008 Feb 23;336(7641):425-9
pubmed: 18270239
J Neurotrauma. 2019 Feb 15;36(4):517-522
pubmed: 29943683
J Int Med Res. 2009 Jul-Aug;37(4):983-95
pubmed: 19761680
Br J Neurosurg. 2000 Apr;14(2):110-6
pubmed: 10889882
J Neurotrauma. 2015 Aug 15;32(16):1246-53
pubmed: 25752340
Surg Neurol. 1993 Jul;40(1):22-5
pubmed: 8322172
Neurosurgery. 2014 Dec;75(6):632-46; discussion 646-7
pubmed: 25181434
J Neurotrauma. 2012 May 1;29(7):1306-12
pubmed: 22150207
J Neurotrauma. 1998 Aug;15(8):587-97
pubmed: 9726258
J Neurosurg. 2012 Aug;117(2):324-33
pubmed: 22631691
BMC Med. 2015 Jan 06;13:1
pubmed: 25563062
J Neurosurg. 1991 Feb;74(2):212-8
pubmed: 1988590
J Neurotrauma. 2007 Feb;24(2):303-14
pubmed: 17375995
J Trauma. 2006 May;60(5):1010-7; discussion 1017
pubmed: 16688063
Br J Neurosurg. 1995;9(6):769-73
pubmed: 8719833
Neurosurgery. 2006 Mar;58(3 Suppl):S16-24; discussion Si-iv
pubmed: 16710968
Biom J. 2005 Aug;47(4):428-41
pubmed: 16161802
Br J Oral Maxillofac Surg. 2012 Jun;50(4):298-308
pubmed: 21530028
Neurol India. 2001 Mar;49(1):3-10
pubmed: 11303234
Br J Neurosurg. 2013 Jun;27(3):330-3
pubmed: 23530712
J Neurotrauma. 2015 Mar 1;32(5):359-65
pubmed: 25026366
J Neurosurg. 1989 Dec;71(6):858-63
pubmed: 2585078
J Trauma Acute Care Surg. 2012 Nov;73(5):1348-54
pubmed: 23117390
Acta Neurochir (Wien). 1993;121(3-4):95-9
pubmed: 8512021
Neurosurg Rev. 1997;20(4):239-44
pubmed: 9457718
Neurosurgery. 2020 Sep 1;87(3):427-434
pubmed: 32761068
J Neurosurg. 2010 May;112(5):1139-45
pubmed: 19575576
Brain Res. 2016 Jun 1;1640(Pt A):36-56
pubmed: 26740405
World Neurosurg. 2018 Mar;111:e120-e134
pubmed: 29248778
Sci Rep. 2020 Dec 11;10(1):21787
pubmed: 33311523
Neurosurgery. 1996 Oct;39(4):708-12; discussion 712-3
pubmed: 8880762
Turk Neurosurg. 2017;27(2):187-191
pubmed: 27593776
Neurosurgery. 2007 Jul;61(1 Suppl):222-30; discussion 230-1
pubmed: 18813167
Neurol Med Chir (Tokyo). 2014;54(11):887-94
pubmed: 25367584
Acta Neurochir (Wien). 2016 Aug;158(8):1465-72
pubmed: 27294774
Neurosurgery. 2005 Dec;57(6):1173-82; discussion 1173-82
pubmed: 16331165
Bull World Health Organ. 2004 Oct;82(10):802-3
pubmed: 15643806
Int J Epidemiol. 2009 Apr;38(2):452-8
pubmed: 18782898
Neurol Res. 2006 Jun;28(4):445-52
pubmed: 16759448
J Korean Neurosurg Soc. 2009 Mar;45(3):143-50
pubmed: 19352475
BMC Neurol. 2015 Oct 24;15:220
pubmed: 26496765
PLoS Med. 2017 Aug 3;14(8):e1002368
pubmed: 28771476
J Neurotrauma. 2008 Jun;25(6):629-39
pubmed: 18491950

Auteurs

Matheus Rodrigues de Souza (MR)

Department of Medicine, Mato Grosso State University, Caceres, Mato Grosso, Brazil.

Caroline Ferreira Fagundes (CF)

Department of Medicine, Mato Grosso State University, Caceres, Mato Grosso, Brazil.

Davi Jorge Fontoura Solla (DJF)

Department of Neurology, University of São Paulo, São Paulo, Brazil.
Department of Neurology, University of Cambridge, Cambridge, UK.

Gustavo Carlos Lucena da Silva (GCL)

Department of Medicine, Mato Grosso State University, Caceres, Mato Grosso, Brazil.

Rafaela Borin Barreto (RB)

Department of Medicine, Mato Grosso State University, Caceres, Mato Grosso, Brazil.

Manoel Jacobsen Teixeira (MJ)

Department of Neurology, University of São Paulo, São Paulo, Brazil.

Robson Luis Oliveira de Amorim (RL)

Department of Neurology, University of São Paulo, São Paulo, Brazil.

Angelos G Kolias (AG)

Department of Clinical Neuroscience - Division of Neurosurgery, Addenbrooke's Hospital, Cambridge, UK.

Daniel Godoy (D)

Intensive Care Unit, San Juan Bautista Hospital, San Fernando del Valle de Catamarca, Argentina.

Wellingson Silva Paiva (WS)

Department of Neurology, University of São Paulo, São Paulo, Brazil.
Department of Neurology, University of Cambridge, Cambridge, UK.

Classifications MeSH