Do-not-resuscitate orders and predictive models after intracerebral hemorrhage
Abstract
Objective: To quantify the accuracy of commonly used intracerebral hemorrhage (ICH) predictive models in ICH patients with and without early do-not-resuscitate orders (DNR).
Methods: Spontaneous ICH cases (n = 487) from the Brain Attack Surveillance in Corpus Christi study (2000–2003) and the University of California, San Francisco (June 2001–May 2004) were included. Three models (the ICH Score, the Cincinnati model, and the ICH grading scale [ICH-GS]) were compared to observed 30-day mortality with a χ2 goodness-of-fit test first overall and then stratified by early DNR orders.
Results: Median age was 71 years, 49% were female, median Glasgow Coma Scale score was 12, median ICH volume was 13 cm3, and 35% had early DNR orders. Overall observed 30-day mortality was 42.7% (95% confidence interval [CI] 38.3–47.1), with the average model-predicted 30-day mortality for the ICH Score, Cincinnati model, and ICH-GS at 39.9% (p = 0.005), 40.4% (p = 0.007), and 53.9% (p < 0.001). However, for patients with early DNR orders, the observed 30-day mortality was 83.5% (95% CI 78.0–89.1), with the models predicting mortality of 64.8% (p < 0.001), 57.2% (p < 0.001), and 77.8% (p = 0.02). For patients without early DNR orders, the observed 30-day mortality was 20.8% (95% CI 16.5–25.7), with the models predicting mortality of 26.6% (p = 0.05), 31.4% (p < 0.001), and 41.1% (p < 0.001).
Conclusions: ICH prognostic model performance is substantially impacted when stratifying by early DNR status, possibly giving a false sense of model accuracy when DNR status is not considered. Clinicians should be cautious when applying these predictive models to individual patients.
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Published online: July 7, 2010
Published in print: August 17, 2010
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Zahuranec et al. outline the impact of early do-not-resuscitate (DNR) orders on the accuracy of intracerebral hemorrhage (ICH) predictive models. [1] The authors found that the ICH Score [2], Cincinnati model [3], and ICH grading scale (ICH-GS) [4] underestimated mortality in patients with early DNR orders by 18.7% [2], 26.3% [3], and 5.7% [4] compared to the observed rate of 83.5%. The models overestimated mortality in those without DNR orders by 5.8% [2], 10.6%[3], and 20.3% [4] compared to the observed rate of 20.8%.
As Zahuranec et al. state, DNR status affects the accuracy of predictive models and causes uncertainty in family members. Testing the predictive ability of the models is difficult in cohorts where standardized treatment and life support are provided to all ICH patients. Zahuranec et al [1] indicated that this testing may not be possible where DNR is an option. Countries such as Turkey -where DNR orders are legally banned-provide an optimal setting for testing the validity of these models.
In our prospective series data gathered over 5 years, we retrospectively determined the predictive value of the 3 models and their sub-items on in-hospital mortality rates. The in-hospital mortality rate was 39% among 193 patients (mean age:66 plus or minus 13 years) who underwent cranial CT within 24 hours of symptom onset. The area under the receiver-operating characteristic curve (AUC) was 0.797 (95%CI: 0.733-0.852) for ICH score, 0.739 (95%CI: 0.674-0.802) for the Cincinnati model, and 0.784 (CI: 0.719-0.840) for ICH-GS. All of the models were statistically significant with the lower limit of 95% CI of AUC higher than 0.5, but with a moderate level of accuracy with values close to but less than 0.8.
Our data indicate that admission clinical severity scales provide optimal prognostic accuracies even when applied alone (Glasgow coma scale, AUC: 0.821, 95%CI: 0.760-0.872; NIH stroke scale, AUC: 0.840; 95%CI: 0.781-0.889), and incorporation of other variables to clinical severity scales do not improve predictive power. This may be one reason for the underutilization of the estimated 20 published models. [1,5]
Moderate AUC values indicate that case fatality may not be correctly predicted by these models. [5] We think that the relevance of current models is limited for triaging ICH patients regardless of DNR status.
References
1. Zahuranec DB, Morgenstern LB, Sanchez BN, Resnicow K, White DB, Hemphill JC, 3rd. Do-not-resuscitate orders and predictive models after intracerebral hemorrhage. Neurology 2010 75:626-633.
2.Hemphill JC, 3rd, Bonovich DC, Besmertis L, Manley GT, Johnston SC. The ICH score: a simple, reliable grading scale for intracerebral hemorrhage. Stroke 2001;32:891-897.
3.Broderick JP, Brott TG, Duldner JE, Tomsick T, Huster G. Volume of intracerebral hemorrhage. A powerful and easy-to-use predictor of 30-day mortality. Stroke 1993;24:987-993.
4.Ruiz-Sandoval JL, Chiquete E, Romero-Vargas S, Padilla-Martinez JJ, Gonzalez-Cornejo S. Grading scale for prediction of outcome in primary intracerebral hemorrhages. Stroke 2007;38:1641-1644.
5.Ariesen MJ, Algra A, van der Worp HB, Rinkel GJ. Applicability and relevance of models that predict short term outcome after intracerebral haemorrhage. J Neurol Neurosurg Psychiatry 2005;76:839-844.
Disclosure: The authors report no disclosures.
Editor's Note: The authors of the article were offered the opportunity to respond but declined.