CC BY-NC-ND 4.0 · Indian Journal of Neurotrauma 2022; 19(02): 069-077
DOI: 10.1055/s-0041-1727404
Review Article

Predictive Value of Rotterdam Score and Marshall Score in Traumatic Brain Injury: A Contemporary Review

Rakesh Mishra
1   Department of Neurosurgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
,
Harold Enrique Vasquez Ucros
2   Department of Medicina General, Universidad del Sinú - Elias Bechara Zainúm de Cartagena, Cartagena, Colombia
3   Jefe de Investigacion ENCEPHALOS en Consejo LatinoAmericano de Neurointensivismo-CLaNi, Cartagena, Colombia
,
4   Department of Medicina General, Universidad Surcolombiana, Medico Investigador Consejo Latinoamericano de Neurointensivismo - CLaNi, Clinica Sahagún IPS SA, Cordoba, Columbia
,
José Rojas Suarez
5   Department of Medicina Intensiva, Epidemiologia Clinica, Intensive Care Research (GRICIO), Universidad de Cartagena, Corporacion Universitaria Rafael Nuñez, Cartagena, Colombia
,
Luis Rafael Moscote-Salazar
6   Department of Neurosurgery, University of Cartagena, Cartagena de Indias, Colombia
,
7   Department of Neurosurgery, Holy Family Red Crescent Medical College, Dhaka, Bangladesh
,
8   Department of Neurosurgery, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
› Institutsangaben

Abstract

This article conducts a contemporary comparative review of the medical literature to update and establish evidence as to which framework among Rotterdam and Marshall computed tomography (CT)-based scoring systems predicts traumatic brain injury (TBI) outcomes better. The scheme followed was following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines for literature search. The search started on August 15, 2020 and ended on December 31, 2020. The combination terms used were Medical Subject Headings terms, combination keywords, and specific words used for describing various pathologies of TBI to identify the most relevant article in each database. PICO question to guide the search strategy was: “what is the use of Marshall (I) versus Rotterdam score (C) in TBI patients (P) for mortality risk stratification (O).” The review is based on 46 references which included a full review of 14 articles for adult TBI patients and 6 articles for pediatric TBI articles comparing Rotterdam and Marshall CT scores. The review includes 8,243 patients, of which 2,365 were pediatric and 5,878 were adult TBI patients. Marshall CT classification is not ordinal, is more descriptive, has better inter-rater reliability, and poor performance in a specific group of TBI patients requiring decompressive craniectomy. Rotterdam CT classification is ordinal, has better discriminatory power, and a better description of the dynamics of intracranial changes. The two scoring systems are complimentary. A combination of clinical parameters, severity, ischemic and hemodynamic parameters, and CT scoring system could predict the prognosis of TBI patients with significant accuracy. None of the classifications has good evidence for use in pediatric patients.



Publikationsverlauf

Artikel online veröffentlicht:
15. April 2021

© 2021. Neurotrauma Society of India. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Thieme Medical and Scientific Publishers Pvt. Ltd.
A-12, 2nd Floor, Sector 2, Noida-201301 UP, India

 
  • References

  • 1 Rubiano AM, Carney N, Chesnut R, Puyana JC. Global neurotrauma research challenges and opportunities. Nature 2015; 527 (75/78) S193-S197
  • 2 Agrawal A, Savardekar A, Singh M. et al Pattern of reporting and practices for the management of traumatic brain injury: an overview of published literature from India. Neurol India 2018; 66 (04) 976-1002
  • 3 Global Burden of Disease Study 2013 Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015; 386 (9995) 743-800
  • 4 Maas AI, Stocchetti N, Bullock R. Moderate and severe traumatic brain injury in adults. Lancet Neurol 2008; 7 (08) 728-741
  • 5 Charry JD, Falla JD, Ochoa JD. et al External validation of the Rotterdam computed tomography score in the prediction of mortality in severe traumatic brain injury. J Neurosci Rural Pract 2017; 8 (Suppl. 01) S23-S26
  • 6 Perel P, Edwards P, Wentz R, Roberts I. Systematic review of prognostic models in traumatic brain injury. BMC Med Inform Decis Mak 2006; 6: 38
  • 7 Mata-Mbemba D, Mugikura S, Nakagawa A. et al Early CT findings to predict early death in patients with traumatic brain injury: Marshall and Rotterdam CT scoring systems compared in the major academic tertiary care hospital in northeastern Japan. Acad Radiol 2014; 21 (05) 605-611
  • 8 Murray GD, Butcher I, McHugh GS. et al Multivariable prognostic analysis in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007; 24 (02) 329-337
  • 9 Maas AI, Hukkelhoven CW, Marshall LF, Steyerberg EW. Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery 2005; 57 (06) 1173-1182 , discussion 1173–1182
  • 10 Marshall LF, Marshall SB, Klauber MR. et al The diagnosis of head injury requires a classification based on computed axial tomography. J Neurotrauma 1992; 9 (Suppl. 01) S287-S292
  • 11 Pargaonkar R, Kumar V, Menon G, Hegde A. Comparative study of computed tomographic scoring systems and predictors of early mortality in severe traumatic brain injury. J Clin Neurosci 2019; 66: 100-106
  • 12 Deepika A, Prabhuraj AR, Saikia A, Shukla D. Comparison of predictability of Marshall and Rotterdam CT scan scoring system in determining early mortality after traumatic brain injury. Acta Neurochir (Wien) 2015; 157 (11) 2033-2038
  • 13 Liesemer K, Riva-Cambrin J, Bennett KS. et al Use of Rotterdam CT scores for mortality risk stratification in children with traumatic brain injury. Pediatr Crit Care Med 2014; 15 (06) 554-562
  • 14 Waqas M, Shamim MS, Enam SF. et al Predicting outcomes of decompressive craniectomy: use of Rotterdam computed tomography classification and Marshall classification. Br J Neurosurg 2016; 30 (02) 258-263
  • 15 Mohammadifard M, Ghaemi K, Hanif H, Sharifzadeh G, Haghparast M. Marshall and Rotterdam computed tomography scores in predicting early deaths after brain trauma. Eur J Transl Myol 2018; 28 (03) 7542
  • 16 Liberati A, Altman DG, Tetzlaff J. et al The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med 2009; 6 (07) e1000100
  • 17 Bobinski L, Olivecrona M, Koskinen LO. Dynamics of brain tissue changes induced by traumatic brain injury assessed with the Marshall, Morris-Marshall, and the Rotterdam classifications and its impact on outcome in a prostacyclin placebo-controlled study. Acta Neurochir (Wien) 2012; 154 (06) 1069-1079
  • 18 Charry JD, Navarro-Parra S, Solano J, Moscote-Salazar L, Pinzón MA, Tejada JH. Outcomes of traumatic brain injury: the prognostic accuracy of various scores and models. Neurol Neurochir Pol 2019; 53 (01) 55-60
  • 19 Frodsham KM, Fair JE, Frost RB. et al Day-of-injury computed tomography and longitudinal rehabilitation outcomes: a comparison of the Marshall and Rotterdam computed tomography scoring methods. Am J Phys Med Rehabil 2020; 99 (09) 821-829
  • 20 Huang YH, Deng YH, Lee TC, Chen WF. Rotterdam computed tomography score as a prognosticator in head-injured patients undergoing decompressive craniectomy. Neurosurgery 2012; 71 (01) 80-85
  • 21 Lindfors M, Lindblad C, Nelson DW. et al Prognostic performance of computerized tomography scoring systems in civilian penetrating traumatic brain injury: an observational study. Acta Neurochir (Wien) 2019; 161 (12) 2467-2478
  • 22 Majdan M, Brazinova A, Rusnak M, Leitgeb J. Outcome prediction after traumatic brain injury: comparison of the performance of routinely used severity scores and multivariable prognostic models. J Neurosci Rural Pract 2017; 8 (01) 20-29
  • 23 Munakomi S, Bhattarai B, Srinivas B, Cherian I. Role of computed tomography scores and findings to predict early death in patients with traumatic brain injury: a reappraisal in a major tertiary care hospital in Nepal. Surg Neurol Int 2016; 7: 23
  • 24 Raj R, Siironen J, Skrifvars MB, Hernesniemi J, Kivisaari R. Predicting outcome in traumatic brain injury: development of a novel computerized tomography classification system (Helsinki computerized tomography score). Neurosurgery 2014; 75 (06) 632-646 , discussion 646–647
  • 25 Malec JF, Brown AW, Leibson CL. et al The Mayo classification system for traumatic brain injury severity. J Neurotrauma 2007; 24 (09) 1417-1424
  • 26 Jennett B, Bond M. Assessment of outcome after severe brain damage. Lancet 1975; 1 (7905) 480-484
  • 27 Teasdale G, Jennett B. Assessment of coma and impaired consciousness. A practical scale. Lancet 1974; 2 (7872) 81-84
  • 28 Mishra RK, Munivenkatappa A, Prathyusha V, Shukla DP, Devi BI. Clinical predictors of abnormal head computed tomography scan in patients who are conscious after head injury. J Neurosci Rural Pract 2017; 8 (01) 64-67
  • 29 Marshall LF, Marshall SB, Klauber MR. et al A new classification of head injury based on computerized tomography. J Neurosurg 1991; 75: S14
  • 30 Chesnut RM. Management and prognosis of severe traumatic brain injury. Part 2. Early indicators of prognosis in severe traumatic brain injury. J Neurotrauma 2000; 17: 557-627
  • 31 Lobato RD, Gomez PA, Alday R. et al Sequential computerized tomography changes and related final outcome in severe head injury patients. Acta Neurochir (Wien) 1997; 139 (05) 385-391
  • 32 Munakomi S. A comparative study between Marshall and Rotterdam CT scores in predicting early deaths in patients with traumatic brain injury in a major tertiary care hospital in Nepal. Chin J Traumatol 2016; 19 (01) 25-27
  • 33 Nelson DW, Nyström H, MacCallum RM. et al Extended analysis of early computed tomography scans of traumatic brain injured patients and relations to outcome. J Neurotrauma 2010; 27 (01) 51-64
  • 34 Chun KA, Manley GT, Stiver SI. et al Interobserver variability in the assessment of CT imaging features of traumatic brain injury. J Neurotrauma 2010; 27 (02) 325-330
  • 35 Creeden S, Ding VY, Parker JJ. et al Interobserver agreement for the computed tomography severity grading scales for acute traumatic brain injury. J Neurotrauma 2020; 37 (12) 1445-1451
  • 36 Bullock MRCR, Ghajar J, Gordon D. et al Guidelines for the surgical management of traumatic brain injury. Neurosurgery 2006; 58 (Suppl. 01) S2-S62
  • 37 Perel P, Arango M, Clayton T. et al MRC CRASH Trial Collaborators. Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ 2008; 336 (76/41) 425-429
  • 38 Thelin EP, Nelson DW, Vehviläinen J. et al Evaluation of novel computerized tomography scoring systems in human traumatic brain injury: an observational, multicenter study. PLoS Med 2017; 14 (08) e1002368
  • 39 Haque A, Dhanani Z, Ali A. et al Outcome of traumatic brain injury in children by using Rotterdam score on computed tomography. J Ayub Med Coll Abbottabad 2018; 30 (01) 140-142
  • 40 Mikkonen ED, Skrifvars MB, Reinikainen M. et al Validation of prognostic models in intensive care unit-treated pediatric traumatic brain injury patients. J Neurosurg Pediatr 2019; 1-8
  • 41 Talari HR, Hamidian Y, Moussavi N. et al The prognostic value of Rotterdam computed tomography score in predicting early outcomes among children with traumatic brain injury. World Neurosurg 2019; 125: e139-e145
  • 42 Hale AT, Stonko DP, Brown A. et al Machine-learning analysis outperforms conventional statistical models and CT classification systems in predicting 6-month outcomes in pediatric patients sustaining traumatic brain injury. Neurosurg Focus 2018; 45 (05) E2
  • 43 Katar S, Aydin Ozturk P, Ozel M. et al The use of Rotterdam CT score for prediction of outcomes in pediatric traumatic brain injury patients admitted to emergency service. Pediatr Neurosurg 2020; 55 (05) 237-243
  • 44 Garza N, Toussi A, Wilson M, Shahlaie K, Martin R. The increasing age of TBI patients at a single level 1 trauma center and the discordance between GCS and CT Rotterdam scores in the elderly. Front Neurol 2020; 11: 112
  • 45 Tjahjadi M, Arifin MZ, Gill AS, Faried A. Early mortality predictor of severe traumatic brain injury: a single center study of prognostic variables based on admission characteristics. Indian J Neurotrauma 2013; 10: 3-8