[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

Assessment and Comparison of the Four Most Extensively Validated Prognostic Scales for Intracerebral Hemorrhage: Systematic Review with Meta-analysis

  • Original Article
  • Published:
Neurocritical Care Aims and scope Submit manuscript

Abstract

Background/Objective

Intracerebral hemorrhage (ICH) is a devastating disorder, responsible for 10% of all strokes. Several prognostic scores have been developed for this population to predict mortality and functional outcome. The aim of this study was to determine the four most frequently validated and most widely used scores, assess their discrimination for both outcomes by means of a systematic review with meta-analysis, and compare them using meta-regression.

Methods

PubMed, ISI Web of Knowledge, Scopus, and CENTRAL were searched for studies validating the ICH score, ICH-GS, modified ICH, and the FUNC score in ICH patients. C-statistic was chosen as the measure of discrimination. For each score and outcome, C-statistics were aggregated at four different time points using random effect models, and heterogeneity was evaluated using the I2 statistic. Score comparison was undertaken by pooling all C-statistics at different time points using robust variance estimation (RVE) and performing meta-regression, with the score used as the independent variable.

Results

Fifty-three studies were found validating the original ICH score, 14 studies were found validating the ICH-GS, eight studies were found validating the FUNC score, and five studies were found validating the modified ICH score. Most studies attempted outcome prediction at 3 months or earlier. Pooled C-statistics ranged from 0.76 for FUNC functional outcome prediction at discharge to 0.85 for ICH-GS mortality prediction at 3 months, but heterogeneity was high across studies. RVE showed the ICH score retained the highest discrimination for mortality (c = 0.84), whereas the modified ICH score retained the highest discrimination for functional outcome (c = 0.80), but these differences were not statistically significant.

Conclusions

The ICH score is the most extensively validated score in ICH patients and, in the absence of superior prediction by other scores, should preferably be used. Further studies are needed to validate prognostic scores at longer follow-ups and assess the reasons for heterogeneity in discrimination.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Van Asch CJJ, Luitse MJA, Rinkel GJE, Van Der Tweel I, Algra A, Klijn CJM. Incidence, case fatality, and functional outcome of intracerebral haemorrhage over time, according to age, sex, and ethnic origin : a systematic review and meta-analysis. Lancet Neurol. 2017;9(2):167–76.

    Google Scholar 

  2. Hwang BY, Appelboom G, Kellner CP, et al. Clinical grading scales in intracerebral hemorrhage. Neurocrit Care. 2010;13(1):141–51.

    Article  PubMed  Google Scholar 

  3. Hemphill JC, Greenberg SM, Anderson CS, et al. Guidelines for the Management of Spontaneous Intracerebral Hemorrhage: A Guideline for Healthcare Professionals from the American Heart Association/American Stroke Association. 2015.

  4. Moher D, Liberati A, Tetzlaff J, Altman DG, Altman D. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Altman DG, Royston P. What do we mean by validating a prognostic model? Stat Med. 2000;19(4):453–73.

    Article  CAS  PubMed  Google Scholar 

  6. Moons KGM, de Groot JAH, Bouwmeester W, et al. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med. 2014;11(10):e1001744.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Hanley AJ, McNeil JB. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143:29–36.

    Article  CAS  PubMed  Google Scholar 

  8. Zhou X, Obuchowski N. Statistical methods in diagnostic medicine. New York: Blackwell Publishing, Inc.; 2002.

    Book  Google Scholar 

  9. Tanner-Smith EE, Tipton E. Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in Stata and spss. Res Synth Methods. 2014;5(1):13–30.

    Article  PubMed  Google Scholar 

  10. McGinn TG, Guyatt GH, Wyer PC, et al. Users’ guides to the medical literature. JAMA. 2000;284(1):79.

    Article  CAS  PubMed  Google Scholar 

  11. Stroup DF, Berlin JA, Morton SC, et al. meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA. 2000;283(15):2008–12.

    Article  CAS  PubMed  Google Scholar 

  12. Hemphill JC, Bonovich DC, Besmertis L, Manley GT, Claiborne JS. The ICH score. Stroke. 2001;32:891–7.

    Article  PubMed  Google Scholar 

  13. Adeoye O, Haverbusch M, Woo D, et al. Is ED disposition associated with intracerebral hemorrhage mortality? Am J Emerg Med. 2011;29(4):391–5.

    Article  PubMed  Google Scholar 

  14. Appelboom G, Bruce SS, Han J, et al. Functional outcome prediction following intracerebral hemorrhage. J Clin Neurosci. 2012;19(6):795–8.

    Article  PubMed  Google Scholar 

  15. Chuang YC, Chen YM, Peng SK, Peng SY. Risk stratification for predicting 30-day mortality of intracerebral hemorrhage. Int J Qual Heal Care. 2009;21(6):441–7.

    Article  Google Scholar 

  16. Clarke JL, Johnston SC, Farrant M, Bernstein R, Tong D, Hemphill JC. External validation of the ICH score. Neurocrit Care. 2004;1(1):53–60.

    Article  PubMed  Google Scholar 

  17. Creutzfeld CJ, Becker KJ, Weinstein JR, et al. Do-not-attempt-resuscitation orders and prognostic models for intraparenchymal hemorrhagelic access. Crit Care Med. 2011;39(1):158–62.

    Article  Google Scholar 

  18. Del Brutto OH, Campos X. Validation of intracerebral hemorrhage scores for patients with pontine hemorrhage. Neurology. 2004;62:515–6.

    Article  PubMed  Google Scholar 

  19. Di Napoli M, Godoy DA, Campi V, et al. C-reactive protein level measurement improves mortality prediction when added to the spontaneous intracerebral hemorrhage score. Stroke. 2011;42(5):1230–6.

    Article  PubMed  CAS  Google Scholar 

  20. Faigle R, Marsh EB, Llinas RH, Urrutia VC, Gottesman RF. Race-specific predictors of mortality in intracerebral hemorrhage: differential impacts of intraventricular hemorrhage and age among Blacks and Whites. J Am Heart Assoc. 2016;5(8):1–8.

    Article  CAS  Google Scholar 

  21. Garrett JS, Zarghouni M, Layton KF, Graybeal D, Daoud YA. Validation of clinical prediction scores in patients with primary intracerebral hemorrhage. Neurocrit Care. 2013;19(3):329–35.

    Article  PubMed  Google Scholar 

  22. Ghelmez D, Tuta S, Popa C, Diseases N. Prognostic factors in hypertensive. Rom J Neurol. 2013;12(4):202–5.

    Google Scholar 

  23. Godoy DA, Piñero G, Di Napoli M. Predicting mortality in spontaneous intracerebral hemorrhage: can modification to original score improve the prediction? Stroke. 2006;37(4):1038–44.

    Article  PubMed  Google Scholar 

  24. Hallevi H, Dar NS, Barreto AD, et al. The IVH Score: a novel tool for estimating intraventricular hemorrhage volume: Clinical and research implications. Crit Care Med. 2009;37(3):969-e1.

    Article  PubMed Central  Google Scholar 

  25. Appelboom G, Hwang BY, Bruce SS, et al. Predicting outcome after arteriovenous malformation-associated intracerebral hemorrhage with the original ICH score. World Neurosurg. 2012;78(6):646–50.

    Article  PubMed  Google Scholar 

  26. Heeley E, Anderson CS, Woodward M, et al. Poor utility of grading scales in acute intracerebral hemorrhage: Results from the INTERACT2 trial. Int J Stroke. 2015;10(7):1101–7.

    Article  PubMed  Google Scholar 

  27. Hemphill JC, Farrant M, Neill TA. Prospective validation of the ICH Score for 12-month functional outcome. Neurology. 2009;73(14):1088–94.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Huang KB, Ji Z, Wu YM, Wang SN, Lin ZZ, Pan SY. The prediction of 30-day mortality in patients with primary pontine hemorrhage: a scoring system comparison. Eur J Neurol. 2012;19(9):1245–50.

    Article  PubMed  Google Scholar 

  29. Huang BR, Liao CC, Huang WH, et al. Prognostic factors of spontaneous intracerebral haemorrhage in haemodialysis patients and predictors of 30-day mortality. Intern Med J. 2008;38(7):568–74.

    Article  CAS  PubMed  Google Scholar 

  30. Hwang DY, Dell CA, Sparks MJ, et al. Clinician judgment vs formal scales for predicting intracerebral hemorrhage outcomes. Neurology. 2016;86(2):126–33.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Ji R, Shen H, Pan Y, et al. A novel risk score to predict 1-year functional outcome after intracerebral hemorrhage and comparison with existing scores. Crit Care. 2013;17(1466–609X (Electronic)):275.

    Article  Google Scholar 

  32. Khan M, Baird GL, Elias R, et al. Comparison of intracerebral hemorrhage volume calculation methods and their impact on scoring tools. J Neuroimaging. 2017;27(1):144–8.

    Article  PubMed  Google Scholar 

  33. Lei C, Wu B, Liu M, Zhang S, Yuan R. Cerebral amyloid angiopathy-related intracerebral hemorrhage score for predicting outcome. Curr Neurovasc Res. 2016;13(2):156–62.

    Article  PubMed  Google Scholar 

  34. Masotti L, Lorenzini G, Di Napoli M, Godoy DA. Prognostic ability of four clinical grading scores in spontaneous intracerebral hemorrhage. Acta Neurol Belg. 2017;117(1):325–7.

    Article  PubMed  Google Scholar 

  35. Matchett SC, Castaldo J, Wasser TE, Baker K, Mathiesen C, Rodgers J. Predicting mortality after intracerebral hemorrhage: comparison of scoring systems and influence of withdrawal of care. J Stroke Cerebrovasc Dis. 2006;15(4):144–50.

    Article  PubMed  Google Scholar 

  36. Ariesen MJ, Algra A, van der Worp HB, Rinkel GJE. Applicability and relevance of models that predict short term outcome after intracerebral haemorrhage. J Neurol Neurosurg Psychiatry. 2005;76(6):839–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Muengtaweepongsa S, Seamhan B. Predicting mortality rate with ICH score in Thai intracerebral hemorrhage patients. Neurol Asia. 2013;18(2):131–5.

    Google Scholar 

  38. Naidech AM, Bernstein RA, Bassin SL, et al. How patients die after intracerebral hemorrhage. Neurocrit Care. 2009;11(1):45–9.

    Article  PubMed  Google Scholar 

  39. Neidert MC, Lawton MT, Mader M, et al. The AVICH score: a novel grading system to predict clinical outcome in arteriovenous malformation-related intracerebral hemorrhage. World Neurosurg. 2016;92:292–7.

    Article  PubMed  Google Scholar 

  40. Panchal HN, Shah MS, Shah DS. Intracerebral hemorrhage score and volume as an independent predictor of mortality in primary intracerebral hemorrhage patients. Indian J Surg. 2015;77(Suppl 2):302–4.

    Article  PubMed  Google Scholar 

  41. Parry-Jones AR, Abid KA, Di Napoli M, et al. Accuracy and clinical usefulness of intracerebral hemorrhage grading scores: a direct comparison in a UK population. Stroke. 2013;44(7):1840–5.

    Article  PubMed  Google Scholar 

  42. Patriota GC, Da Silva JM, Santos Barcellos ACE, et al. Determining ich score: can we go beyond? Arq Neuropsiquiatr. 2009;67(3 A):605–8.

    Article  PubMed  Google Scholar 

  43. Peng SY, Chuang YC, Kang TW, Tseng KH. Random forest can predict 30-day mortality of spontaneous intracerebral hemorrhage with remarkable discrimination. Eur J Neurol. 2010;17(7):945–50.

    Article  PubMed  Google Scholar 

  44. Romano LM, Ioli PL, Gonorazky SE, et al. Desarollo y validación de la escala predictiva de mortalidad (REC-HPC) en la hemorragia intracerebral primaria. Neurol Argentina. 2009;1(2):75–81.

    Google Scholar 

  45. Ruiz-Sandoval JL, Chiquete E, Romero-Vargas S, Padilla-Martínez JJ, González-Cornejo S. Grading scale for prediction of outcome in primary intracerebral hemorrhages. Stroke. 2007;38(5):1641–4.

    Article  PubMed  Google Scholar 

  46. Safatli DA, Gunther A, Schlattmann P, Schwarz F, Kalff R, Ewald C. Predictors of 30-day mortality in patients with spontaneous primary intracerebral hemorrhage. Surg Neurol Int. 2016;7(8):S510–7.

    PubMed  PubMed Central  Google Scholar 

  47. Barbieri A, Pinna C, Basso GP, et al. Specificity and reliability of prognostic indexes in intensive care evaluation: The spontaneous cerebral haemorrhage case. J Eval Clin Pract. 2009;15(2):242–5.

    Article  PubMed  Google Scholar 

  48. Stein M, Luecke M, Preuss M, Boeker DK, Joedicke A, Oertel MF. Spontaneous intracerebral hemorrhage with ventricular extension and the grading of obstructive hydrocephalus: the prediction of outcome of a special life-threatening entity. Neurosurgery. 2010;67(5):1243–51.

    Article  PubMed  Google Scholar 

  49. Stein M, Luecke M, Preuss M, Scharbrodt W, Joedicke A, Oertel MF. The prediction of 30-day mortality and functional outcome in spontaneous intracerebral hemorrhage with secondary ventricular hemorrhage: a score comparison. Acta Neurochir (Wien). 2011;112:10–2.

    Google Scholar 

  50. Takahashi O, Cook EF, Nakamura T, Saito J, Ikawa F, Fukui T. Risk stratification for in-hospital mortality in spontaneous intracerebral haemorrhage: a Classification and Regression Tree analysis. QJM. 2006;99(11):743–50.

    Article  CAS  PubMed  Google Scholar 

  51. Tao W-D, Wang J, Schlaug G, Liu M, Selim MH. A comparative study of fractional anisotropy measures and ICH score in predicting functional outcomes after intracerebral hemorrhage. Neurocrit Care. 2014;21(3):417–25.

    Article  PubMed  Google Scholar 

  52. Vial F, Brunser A, Lavados P, Illanes S. Intraventricular bleeding and hematoma size as predictors of infection development in intracerebral hemorrhage: a prospective cohort study. J Stroke Cerebrovasc Dis. 2016;25(11):2708–11.

    Article  PubMed  Google Scholar 

  53. Wei ZJ, Ou YQ, Li X, Li H. The 90-day prognostic value of copeptin in acute intracerebral hemorrhage. Neurol Sci. 2014;35(11):1673–9.

    Article  PubMed  Google Scholar 

  54. Weimar C, Benemann J, Diener H-C, German Stroke Study Collaboration. Development and validation of the Essen Intracerebral Haemorrhage Score. J Neurol Neurosurg Psychiatry. 2006;77(5):601–5.

    Article  CAS  PubMed  Google Scholar 

  55. Yang X, Ren W, Zu H, Dong Q. Evaluate the serum cortisol in patients with intracerebral hemorrhage. Clin Neurol Neurosurg. 2014;123:127–30.

    Article  PubMed  Google Scholar 

  56. Zahuranec DB, Morgenstern LB, Sánchez BN, Resnicow K, White DB, Hemphill JC. Do-not-resuscitate orders and predictive models after intracerebral hemorrhage. Neurology. 2010;75(7):626–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Ziai WC, Siddiqui AA, Ullman N, et al. Early therapy intensity level (TIL) predicts mortality in spontaneous intracerebral hemorrhage. Neurocrit Care. 2015;23(2):188–97.

    Article  CAS  PubMed  Google Scholar 

  58. Behrouz R, Hafeez S, Mutgi SA, Zakaria A, Miller CM. Hypomagnesemia in intracerebral hemorrhage. World Neurosurg. 2015;84(6):1929–32.

    Article  PubMed  Google Scholar 

  59. Zweifel C, Katan M, Schuetz P, et al. Copeptin is associated with mortality and outcome in patients with acute intracerebral hemorrhage. BMC Neurol. 2010;10:34.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Suthar N, Patel K, Saparia C, Parikh A. Study of clinical and radiological profile and outcome in patients of intracranial hemorrhage. Ann Afr Med. 2016;15(2):69–77.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Liu H, Zen Y, Li J, et al. Optimal treatment determination on the basis of haematoma volume and intra-cerebral haemorrhage score in patients with hypertensive putaminal haemorrhages: a retrospective analysis of 310 patients. BMC Neurol. 2014;14(1):141.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Bhatia R, Singh H, Singh S, et al. A prospective study of in-hospital mortality and discharge outcome in spontaneous intracerebral hemorrhage. Neurol India. 2013;61(3):244–8.

    Article  PubMed  Google Scholar 

  63. Bruce SS, Appelboom G, Piazza M, et al. A comparative evaluation of existing grading scales in intracerebral hemorrhage. Neurocrit Care. 2011;15(3):498–505.

    Article  PubMed  Google Scholar 

  64. Chen HS, Hsieh CF, Chau TT, Yang CD, Chen YW. Risk factors of in-hospital mortality of intracerebral hemorrhage and comparison of ICH scores in a Taiwanese population. Eur Neurol. 2011;66(1):59–63.

    Article  PubMed  Google Scholar 

  65. Cheung RTF, Zou LY. Use of the original, modified, or new intracerebral hemorrhage score to predict mortality and morbidity after intracerebral hemorrhage. Stroke. 2003;34(7):1717–22.

    Article  PubMed  Google Scholar 

  66. Ruiz-Sandoval JL, Chiquete E, Garate-Carrillo A, et al. Spontaneous intracerebral hemorrhage in Mexico: results from a Multicenter Nationwide Hospital-based Registry on Cerebrovascular Disease (RENAMEVASC). Rev Neurol. 2011;53(12):705–12.

    PubMed  Google Scholar 

  67. Rost NS, Smith EE, Chang Y, et al. Prediction of functional outcome in patients with primary intracerebral hemorrhage: The FUNC score. Stroke. 2008;39(8):2304–9.

    Article  PubMed  Google Scholar 

  68. Garrett JS, Zarghouni M, Layton KF, Graybeal D, Daoud YA. Validation of clinical prediction scores in patients with primary intracerebral hemorrhage. Neurocrit Care. 2013;19:329–35.

    Article  PubMed  Google Scholar 

  69. Mittal MK, Lele A. Predictors of poor outcome at hospital discharge following a spontaneous intracerebral hemorrhage. Int J Neurosci. 2011;121(5):267–70.

    Article  PubMed  Google Scholar 

  70. Barret RJ, Hussain R, Coplin WM, et al. Frameless stereotactic aspiration and thrombolysis of spontaneous intracerebral hemorrhage. Neurocrit Care. 2005;3(1):237–45.

    Article  Google Scholar 

  71. Brouwers HB, Chang Y, Falcone GJ, et al. Predicting hematoma expansion after primary intracerebral hemorrhage. JAMA Neurol. 2014;71(2):158–64.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Cerillo A, Vizioli L, Falivene R, Mottolese C, Bernini FP, Tedeschi G. Intracerebral hemorrhage: an attempt of statistical assessment for operability. Acta Neurol (Napoli). 1981;3(4):572–86.

    CAS  Google Scholar 

  73. Edwards DF, Hollingsworth H, Zazulia A, Diringer M. Artificial neural networks improve the prediction of mortality in intracerebral hemorrhage. Neurology. 1999;53(2):351–7.

    Article  CAS  PubMed  Google Scholar 

  74. Lukić S, Ćojbasić Ž, Perić Z, et al. Artificial neural networks based early clinical prediction of mortality after spontaneous intracerebral hemorrhage. Acta Neurol Belg. 2012;112(4):375–82.

    Article  PubMed  Google Scholar 

  75. Romano LM, Ioli P, Gonorazky S. Variables predictivas de letalidad y validacíon externa de la escala original de hemorragia intracerebral espontánea. Rev Neurol Argentina. 2007;32:94–9.

    Google Scholar 

  76. Tuhrim S, Dambrosia J, Price T, et al. Intracerebral hemorrhage: external validation and extension of a model for prediction of 30-day survival. Ann Neurol. 1991;29(6):658–63.

    Article  CAS  PubMed  Google Scholar 

  77. Tuhrim S, Horowitz D, Sacher M, Godbold J. Volume of ventricular blood is an important determinant of outcome in supratentorial intracerebral hemorrhage. Crit Care Med. 1999;27(3):617–21.

    Article  CAS  PubMed  Google Scholar 

  78. Weimar C, Roth M, Willig V, Kostopoulos P, Benemann J, Diener HC. Development and validation of a prognostic model to predict recovery following intracerebral hemorrhage. J Neurol. 2006;253(6):788–93.

    Article  PubMed  Google Scholar 

  79. Weimar C, Ziegler A, Sacco RL, Diener HC, König IR. Predicting recovery after intracerebral hemorrhage–an external validation in patients from controlled clinical trials. J Neurol. 2009;256(3):464–9.

    Article  PubMed  Google Scholar 

  80. Zorilla JP, Sousa L, Ioli P, et al. Variables predictivas de letalidad y rendimiento de la escala ReC-HPC en hemorragia intracerebral primaria en pacientes anticoagulados. Neurol Argentina. 2011;3(2):94–9.

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank Dr Laura Stapleton for proofreading the final manuscript for clarity and conciseness.

Funding

There were no sources of funding for the current study.

Author information

Authors and Affiliations

  1. Department of Internal Medicine, Vila Nova de Gaia Hospital Centre, Rua Conceição Fernandes, 4434-502, Vila Nova de Gaia, Portugal

    Tiago Gregório, Sara Pipa & Gabriel Atanásio

  2. Stroke Unit, Vila Nova de Gaia Hospital Centre, Rua Conceição Fernandes, 4434-502, Vila Nova de Gaia, Portugal

    Tiago Gregório

  3. Intensive Care Department, Algarve University Hospital Centre, Rua Leão Penedo, 8000-386, Faro, Portugal

    Pedro Cavaleiro

  4. Department of Internal Medicine, São João Hospital Centre, Alameda Prof. Hernani Monteiro, 4200-319, Porto, Portugal

    Inês Albuquerque & Paulo Castro Chaves

  5. Stroke Unit, São João Hospital Centre, Alameda Prof. Hernani Monteiro, 4200-319, Porto, Portugal

    Paulo Castro Chaves

  6. Department of Surgery and Physiology, Faculty of Medicine, University of Porto, Alameda Prof. Hernani Monteiro, 4200-319, Porto, Portugal

    Paulo Castro Chaves

  7. Centre for Health Technology and Services Research and Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Alameda Prof. Hernani Monteiro, 4200-319, Porto, Portugal

    Luís Azevedo

Authors
  1. Tiago Gregório
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sara Pipa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pedro Cavaleiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gabriel Atanásio
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Inês Albuquerque
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Paulo Castro Chaves
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Luís Azevedo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

TG conceived and designed the project, acquired, analyzed and interpreted the data, and wrote the manuscript; SP, PC, GA, and IA acquired data; PCC analyzed and interpreted data; LA designed the project, analyzed, and interpreted data; all authors critically reviewed and approved the final version of the manuscript.

Corresponding author

Correspondence to Tiago Gregório.

Ethics declarations

Conflicts of interest

The authors declare they have no conflicts of interest.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 12 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gregório, T., Pipa, S., Cavaleiro, P. et al. Assessment and Comparison of the Four Most Extensively Validated Prognostic Scales for Intracerebral Hemorrhage: Systematic Review with Meta-analysis. Neurocrit Care 30, 449–466 (2019). https://doi.org/10.1007/s12028-018-0633-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12028-018-0633-6

Keywords

Search

Navigation