Top

Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine

Published in:

Open Access 01-12-2017 | Original research

Common intensive care scoring systems do not outperform age and glasgow coma scale score in predicting mid-term mortality in patients with spontaneous intracerebral hemorrhage treated in the intensive care unit

Authors: Marika Fallenius, Markus B. Skrifvars, Matti Reinikainen, Stepani Bendel, Rahul Raj

Published in: Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine | Issue 1/2017

Abstract

Background

Intensive care scoring systems are widely used in intensive care units (ICU) around the world for case-mix adjustment in research and benchmarking. The aim of our study was to investigate the usefulness of common intensive care scoring systems in predicting mid-term mortality in patients with spontaneous intracerebral hemorrhage (ICH) treated in intensive care units (ICU).

Methods

We performed a retrospective observational study including adult patients with spontaneous ICH treated in Finnish ICUs during 2003–2012. We used six-month mortality as the primary outcome of interest. We used logistic regression to customize Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II and Sequential Organ Failure Assessment (SOFA) for six-month mortality prediction. To assess the usefulness of the scoring systems, we compared their discrimination and calibration with two simpler models consisting of age, Glasgow Coma Scale (GCS) score, and premorbid functional status.

Results

Totally 3218 patients were included. Overall six-month mortality was 48%. APACHE II and SAPS II outperformed SOFA (area under the receiver operator curve [AUC] 0.83 and 0.84, respectively, vs. 0.73) but did not show any benefit over the simpler models in terms of discrimination (AUC 0.84, p > 0.05 for all models). SAPS II showed satisfactory calibration (p = 0.058 in the Hosmer-Lemeshow test), whereas all other models showed poor calibration (p < 0.05).

Discussion

In this retrospective multi-center study, we found that SAPS II and APACHE II were of no additional prognostic value to a simple model based on only age and GCS score for patients with ICH treated in the ICU. In fact, the major predictive ability of APACHE II and SAPS II comes from their age and GCS score components. SOFA performed significantly poorer than the other models and is not applicable as a prognostic model for ICH patients. All models displayed poor calibration, highlighting the need for improved prognostic models for ICH patients.

Conclusion

The common intensive care scoring systems did not outperform a simpler model based on only age and GCS score. Thus, the use of previous intensive care scoring systems is not warranted in ICH patients.

Flaherty ML, Haverbusch M, Sekar P, Kissela B, Kleindorfer D, Moomaw CJ, et al. Long-term mortality after intracerebral hemorrhage. Neurology [Internet]. 2006 [cited 2017 Sep 12];66:1182–6. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16636234.

Fogelholm R, Murros K, Rissanen A, Avikainen S. Long term survival after primary intracerebral haemorrhage: a retrospective population based study. J. Neurol. Neurosurg. Psychiatry [Internet]. 2005 [cited 2017 Sep 12];76:1534–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16227546.

Weimar C, Weber C, Wagner M, Busse O, Haberl RL, Lauterbach KW, et al. Management patterns and health care use after intracerebral hemorrhage. a cost-of-illness study from a societal perspective in Germany. Cerebrovasc. Dis. [Internet]. 2003 [cited 2017 Sep 12];15:29–36. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12499708.

Zahuranec DB, Lisabeth LD, Sánchez BN, Smith MA, Brown DL, Garcia NM, et al. Intracerebral hemorrhage mortality is not changing despite declining incidence. Neurology [Internet]. American Academy of Neurology; 2014 [cited 2017 Sep 12];82:2180–6. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24838789.

van Asch CJ, Luitse MJ, Rinkel GJ, van der Tweel I, Algra A, Klijn CJ. 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. [Internet]. 2010 [cited 2017 Sep 12];9:167–176. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20056489.

Hemphill JC, Greenberg SM, Anderson CS, Becker K, Bendok BR, Cushman M, et al. Guidelines for the Management of Spontaneous Intracerebral Hemorrhage. Stroke [Internet]. 2015 [cited 2017 Sep 12]; Available from: http://stroke.ahajournals.org/content/early/2015/05/28/STR.0000000000000069

Maas AIR, Murray GD, Roozenbeek B, Lingsma HF, Butcher I, McHugh GS, et al. Advancing care for traumatic brain injury: findings from the IMPACT studies and perspectives on future research. Lancet Neurol. 2013;

Knaus WA, Draper EA, Wagner DP, Zimmerman JEAPACHEII. A severity of disease classification system. Crit Care Med. 1985;13:818–29.CrossRefPubMed

Le Gall J-R, Lemeshow S, Saulnier F. Simplified acute physiology score ( SAPS II ) based on a European / north American multicenter study. JAMA. 1993;270:2957–63.CrossRefPubMed

10.

Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. [Internet]. 1996 [cited 2017 Sep 12];22:707–710. Available from: http://www.ncbi.nlm.nih.gov/pubmed/8844239.

11.

Pettilä V, Pettilä M, Sarna S, Voutilainen P, Takkunen O. Comparison of multiple organ dysfunction scores in the prediction of hospital mortality in the critically ill. Crit. Care Med. [Internet]. 2002 [cited 2017 Sep 12];30:1705–1711. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12163780

12.

Radholm K, Arima H, Lindley RI, Wang J, Tzourio C, Robinson T, et al. Older age is a strong predictor for poor outcome in intracerebral haemorrhage: the INTERACT2 study. Age Ageing [Internet]. 2015 [cited 2017 Sep 12];44:422–427. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25497513.

13.

Handschu R, Haslbeck M, Hartmann A, Fellgiebel A, Kolominsky-Rabas P, Schneider D, et al. Mortality prediction in critical care for acute stroke: Severity of illness–score or coma–scale? J. Neurol. [Internet]. 2005 [cited 2017 Sep 12];252:1249–1254. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15917980.

14.

Raj R, Skrifvars M, Bendel S, Selander T, Kivisaari R, Siironen J, et al. Predicting six-month mortality of patients with traumatic brain injury: usefulness of common intensive care severity scores. Crit. Care [Internet]. 2014 [cited 2017 Sep 12];18:R60. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24708781.

15.

Raj R, Bendel S, Reinikainen M, Hoppu S, Luoto T, Ala-Kokko T, et al. Traumatic brain injury patient volume and mortality in neurosurgical intensive care units: a Finnish nationwide study. Scand. J. Trauma, Resusc. 2016:24.

16.

Reinikainen M, Mussalo P, Hovilehto S, Uusaro A, Varpula T, Kari A, et al. Association of automated data collection and data completeness with outcomes of intensive care. A new customised model for outcome prediction. Acta Anaesthesiol. Scand. [Internet]. 2012 [cited 2017 mar 1];56:1114–1122. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22384799.

17.

Raj R, Skrifvars MB, Bendel S, Selander T, Kivisaari R, Siironen J, et al. Predicting six-month mortality of patients with traumatic brain injury: usefulness of common intensive care severity scores. Crit Care. 2014;18

18.

Steyerberg EW, Harrell FE, Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J. Clin. Epidemiol. [Internet]. 2001 [cited 2017 Sep 12];54:774–781. Available from: http://www.ncbi.nlm.nih.gov/pubmed/11470385.

19.

Picard RR, Berk KN. Data Splitting. Am. Stat. [Internet]. Taylor & Francis, Ltd.American Statistical Association; 1990 [cited 2017 Sep 12];44:140. Available from: http://www.jstor.org/stable/2684155?origin=crossref

20.

Kahn JM, Kramer AA, Rubenfeld GD. Transferring Critically Ill Patients Out of Hospital Improves the Standardized Mortality Ratio. Chest [Internet]. 2007 [cited 2017 Sep 12];131:68–75. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17218558

21.

Moreno R, Apolone G. Impact of different customization strategies in the performance of a general severity score. Crit. Care Med. [Internet]. 1997 [cited 2017 Sep 12];25:2001–2008. Available from: http://www.ncbi.nlm.nih.gov/pubmed/9403750

22.

Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology [Internet]. 1982 [cited 2017 Sep 12];143:29–36. Available from: http://www.ncbi.nlm.nih.gov/pubmed/7063747

23.

Hosmer DW, Lemeshow S, Sturdivant RX. Applied logistic regression.

24.

Serrano N. Calibration strategies to validate predictive models: is new always better? Intensive Care Med. [Internet]. 2012 [cited 2017 Sep 12];38:1246–1248. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22584794.

25.

Kramer AA, Zimmerman JE. Assessing the calibration of mortality benchmarks in critical care: The Hosmer-Lemeshow test revisited*. Crit. Care Med. [Internet]. 2007 [cited 2017 Sep 12];35:2052–2056. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17568333.

26.

Finazzi S, Poole D, Luciani D, Cogo PE, Bertolini G. Calibration Belt for Quality-of-Care Assessment Based on Dichotomous Outcomes. Gravenor M, editor. PLoS One [Internet]. 2011 [cited 2017 Sep 12];6:e16110. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21373178

27.

Nattino G, Finazzi S, Bertolini G. A new test and graphical tool to assess the goodness of fit of logistic regression models. Stat. Med. [Internet]. 2016 [cited 2017 Sep 12];35:709–720. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26439593

28.

Krinsley JS, Wasser T, Kang G, Bagshaw SM. Pre-admission functional status impacts the performance of the APACHE IV model of mortality prediction in critically ill patients. Crit. Care [Internet]. BioMed Central; 2017 [cited 2017 Sep 12];21:110. Available from: http://ccforum.biomedcentral.com/articles/10.1186/s13054-017-1688-z

29.

Huang K-B, Ji Z, Wu Y-M, Wang S-N, Lin Z-Z, Pan S-Y. The prediction of 30-day mortality in patients with primary pontine hemorrhage: a scoring system comparison. Eur. J. Neurol. [Internet]. 2012 [cited 2017 Sep 12];19:1245–1250. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22524995.

30.

Huang Y, Chen J, Zhong S, Yuan J. Role of APACHE II scoring system in the prediction of severity and outcome of acute intracerebral hemorrhage. Int. J. Neurosci. [Internet]. 2016 [cited 2017 Sep 12];126:1020–1024. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26393395

31.

Vincent J-L, Moreno R. Clinical review: Scoring systems in the critically ill. Crit. Care [Internet]. 2010 [cited 2017 Sep 12];14:207. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20392287.

32.

Zurasky JA, Aiyagari V, Zazulia AR, Shackelford A, Diringer MN. Early mortality following spontaneous intracerebral hemorrhage. Neurology [Internet]. 2005 [cited 2017 Sep 12];64:725–727. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15728302

33.

Van Calster B, Steyerberg EW, Harrell FH. Risk Prediction for Individuals. JAMA [Internet]. John Wiley & Sons, Hoboken, NJ; 2015 [cited 2017 Sep 12];314:1875. Available from: http://jama.jamanetwork.com/article.aspx?doi=10.1001/jama.2015.12215

34.

Hemphill JC, Bonovich DC, Besmertis L, Manley GT, Johnston SC. The ICH score: a simple, reliable grading scale for intracerebral hemorrhage. Stroke [Internet]. 2001 [cited 2017 Oct 5];32:891–7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/11283388.

Title: Common intensive care scoring systems do not outperform age and glasgow coma scale score in predicting mid-term mortality in patients with spontaneous intracerebral hemorrhage treated in the intensive care unit
Authors: Marika Fallenius
Markus B. Skrifvars
Matti Reinikainen
Stepani Bendel
Rahul Raj
Publication date: 01-12-2017
Publisher: BioMed Central
Published in: Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine / Issue 1/2017
Electronic ISSN: 1757-7241
DOI: https://doi.org/10.1186/s13049-017-0448-z

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Common intensive care scoring systems do not outperform age and glasgow coma scale score in predicting mid-term mortality in patients with spontaneous intracerebral hemorrhage treated in the intensive care unit

Abstract

Background

Methods

Results

Discussion

Conclusion

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Discussion

Conclusion

Please log in to get access to this content

Other articles of this Issue 1/2017

The Anticoagulated trauma patient in the age of the direct oral anticoagulants: a Canadian perspective

We need to include bystander first aid in trauma research

The association of patient and trauma characteristics with the health-related quality of life in a Dutch trauma population

Development of the major trauma case review tool

Barriers and facilitators towards implementing the Sepsis Six care bundle (BLISS-1): a mixed methods investigation using the theoretical domains framework

Community first responders and responder schemes in the United Kingdom: systematic scoping review