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(Circulation. 2002;105:200.)
© 2002 American Heart Association, Inc.

Clinical Investigation and Reports

Predicting Death in Patients With Acute Type A Aortic Dissection

Rajendra H. Mehta, MD MS; Toru Suzuki, MD; Peter G. Hagan, MD; Eduardo Bossone, MD; Dan Gilon, MD; Alfredo Llovet, MD; Luis C. Maroto, MD; Jeanna V. Cooper, MS; Dean E. Smith, PhD; William F. Armstrong, MD; Christoph A. Nienaber, MD; Kim A. Eagle, MD, on Behalf of the International Registry of Acute Aortic Dissection (IRAD) Investigators

From the University of Michigan (R.H.M., P.G.H., J.V.C., D.E., W.F.A., K.A.E.), Ann Arbor; University of Tokyo (T.S.), Japan; Instituto Policlinico San Donato (E.B.), Milan, Italy; Hadassah University Hospital (D.G.), Jerusalem, Israel; Hospital Universitario "12 de Octubre" (A.L., L.C.M.), Madrid, Spain; and University of Rostock (C.A.N.), Germany.

Correspondence to Kim A. Eagle, MD, University of Michigan, 3910 TC, Ann Arbor, MI 48109. E-mail keagle{at}umich.edu

	Abstract

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Background— Given the high mortality rates in patients with type A aortic dissection, predictive tools to identify patients at increased risk of death are needed to assist clinicians for optimal treatment.

Methods and Results— Accordingly, we evaluated 547 patients with this diagnosis enrolled in the International Registry of Acute Aortic Dissection (IRAD) between January 1996 and December 1999. Univariate testing followed by multivariate logistic regression analysis was performed to identify independent predictors of death. In-hospital mortality rate was 32.5% in type A dissection patients. In-hospital complications (neurological deficits, altered mental status, myocardial or mesenteric ischemia, kidney failure, hypotension, cardiac tamponade, and limb ischemia) were increased in patients who died compared with survivors (P<0.05 for all). Logistic regression identified the following presenting variables as predictors of death: age 70 years (OR, 1.70; 95% CI, 1.05 to 2.77; P=0.03), abrupt onset of chest pain (OR 2.60; 95% CI, 1.22 to 5.54; P=0.01), hypotension/shock/tamponade (OR, 2.97; 95% CI, 1.83 to 4.81; P<0.0001), kidney failure (OR, 4.77; 95% CI, 1.80 to 12.6; P=0.002), pulse deficit (OR, 2.03; 95% CI, 1.25 to 3.29, P=0.004), and abnormal ECG (OR, 1.77; 95% CI, 1.06 to 2.95; P=0.03) (area under receiver operating curve, 0.74; Hosmer-Lemeshow statistic, P=0.75).

Conclusions— The in-hospital mortality rate in acute type A aortic dissection is high and can be predicted with the use of a clinical model incorporated in a simple risk prediction tool. This tool can be used to educate patients with dissection about their predicted risk and in clinical research for risk adjustment while comparing outcomes of different therapies.

Key Words: aorta • mortality • surgery • risk factors

	Introduction

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Acute type A aortic dissection is a medical emergency that carries a high mortality rate in absence of surgical treatment.^1–9 Most studies that have evaluated the predictors of death for patients with aortic dissection were restricted to a small number of patients at a single center stretching over a period of years.^5,10–18 Furthermore, these studies have focused their attention on the surgically treated cohort rather than all patients with dissection presenting to their institution.^{10–17,19–21} Most have not distinguished acute from chronic stable,^{5,10–12,14,17,19,21} or type A from B^{11,14,17,19,21} dissection, conditions that have different natural histories and call for different treatment strategies. As such, at present, the predictors of death in large, unselected, consecutive acute type A aortic dissection patients are not well known.

The International Registry of Acute Aortic Dissection (IRAD) represents an opportunity to study a large group of consecutive patients with aortic dissection who presented to hospitals in a broad geographic region.⁷ We conducted a comprehensive analysis of 290 clinical variables and their relation to in-hospital death to identify independent predictors of death. Furthermore, with the use of these identifiers, the goal of this analysis was to create a simple bedside tool that could be used to predict death.

	Methods

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International Registry of Acute Aortic Dissection
The inception and structure of IRAD has been described previously.⁷ In brief, 18 large referral centers in 6 countries agreed to participate in the ongoing registry, which was established in 1996. The main purpose of IRAD was to assess the etiological factors, modes of presentation, clinical features, treatment, and outcome of patients with aortic dissection in the current era. Beginning January 1, 1996, consecutive patients with acute aortic dissection (both type A and type B) presenting to IRAD sites were enrolled in the registry. Consecutive patients were identified prospectively at presentation or retrospectively by searching hospital discharge diagnosis records and/or surgical, pathology, and echocardiography databases. Diagnosis was suspected on the basis of the history and physical examination and was confirmed by imaging study findings, visualization at surgery, and/or postmortem examination.

Patient Selection
All patients with acute type A aortic dissection enrolled in IRAD from January 1, 1996, to December 31, 1999, were included for the purpose of this analysis. Acute type A dissection was defined as any dissection that involved the ascending aorta with presentation within 14 days of symptom onset.^13,22

Data Collection
Data were assembled with the use of a standardized data form on patient demographics, history, clinical presentations, physical findings, imaging studies results, details of medical and surgical treatment, and patient outcomes. Completed data entry forms were forwarded by the participating IRAD sites to the coordinating center at the University of Michigan. Data forms were reviewed for analytical internal validity, and external validation was performed through a random (5%) field selection and error audit. Data were scanned electronically into an Access database.

Clinical Events
Chart review was used to document in-hospital clinical events and in-hospital death. Standard American College of Cardiology/American Heart Association definitions were used to denote various in-hospital complications.²³ Abrupt-onset pain was defined as documentation in patients’ charts of sudden severe tearing pain in the chest, neck, or back, with maximum intensity at onset and that brought the patient to medical attention. An ECG was noted as abnormal if it showed pathologic Q waves, ST-segment deviation, T-wave inversions, left bundle-branch block, or left ventricular hypertrophy.

Statistical Analysis
Summary statistics are presented as frequencies and percentages, mean±SD, or as median and interquartile ranges. In all cases, missing data were not defaulted to negative, and denominators reflect only cases reported. Associations of death among nominal variables were compared by means of ² tests and 2-sided Fisher exact tests. Continuous univariate predictors for death were tested by means of t tests or Wilcoxon Mann-Whitney tests as appropriate.

Predictive Modeling
Iterative logistic regression modeling for in-hospital death with the likelihood ratio test used for model selection was performed. Initial modeling used elements marginally suggestive of an unadjusted association to in-hospital death (defined as P<0.20). Variables were reviewed for clinical significance before testing. Diagnostic routines (Hosmer-Lemeshow test for lack of fit, change in deviance, and likelihood ratio test) were used on final model selection. SAS 8.1 was used for all analyses.

Development of a Simple Bedside Risk Prediction Tool
The variables found to be significantly associated with in-hospital death in the "best" regression model were assigned a score equal to their coefficients in the fitted model (natural log of their odds ratios rounded to the nearest decimal) (Appendix). The sum of this numerical score in an individual patient could then be used to predict his or her in-hospital death. A risk prediction tool that plotted the various score levels against the corresponding predicted death was developed to aid clinicians in predicting in-hospital death for patients with type A aortic dissection.

	Results

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Overall Characteristics of IRAD Patients
Of the total of 874 patients with aortic dissection (both type A and B) in IRAD, 547 patients had type A aortic dissection (62.5%) (Tables 1 through 3). Their mean age was 61.9±14.1 years, with a majority being men (65.5%). Two thirds of patients presented initially to an outside hospital and were transferred to an IRAD center for further treatment. Nearly 79.7% of patients underwent surgery for repair of aortic dissection. The reason for medical treatment was not specified in 5% of patients by their caring physician, whereas the remaining patients were treated medically for comorbid conditions (55%), old age (17%, all but one patient >70 years of age; mean age, 79.9±5.8 years), refusal by the patient (14%), having only intramural hematoma (7%), and extensive dissection involving the descending aorta (17%). In-hospital death occurred in one third of patients (32.5%) and was 26.9% in surgically treated patients versus 56.2% in those treated medically without surgery. The cause of death was not specified in 33.3% of these patients, whereas rupture accounted for a third of death (33.3%), followed by neurological deficit (13.9%), visceral ischemia/kidney failure (11.5%) and cardiac tamponade (7.9%) in the remaining.

View this table: [in this window] [in a new window]   Table 1. Demographics and History for Patients With Type A Aortic Dissection

View this table: [in this window] [in a new window]   Table 2. Clinical Presentations, Signs, and Diagnostic Imaging Results of All Patients With Type A Aortic Dissection

View this table: [in this window] [in a new window]   Table 3. In-Hospital Treatments and Complications in Patients With Type A Aortic Dissection

Univariate Predictors of In-Hospital Death for All Patients With Type A Aortic Dissection
Clinical characteristics that showed significant association included advanced age, female sex, abrupt onset and migratory chest pain, hypotension/shock/tamponade on presentation, and evidence of neurological or pulse deficits at presentation (Tables 1 through 3). Furthermore, the presence of a widened mediastinum on chest radiography, electrocardiographic evidence of new Q waves and/or ST-segment deviations, or a lack of a normal ECG were associated with higher in-hospital mortality rates. As expected, complications such as neurological deficit, myocardial ischemia, hypotension, kidney failure, and limb ischemia were also more frequent in patients who died than in those who survived. On the other hand, a medical history of hypertension, diabetes, aneurysm, or heart surgery was similar in the two groups of patients.

Predictive Model for In-Hospital Death
Independent predictors of in-hospital death are as shown in Table 4. The area under the receiver operating curve for the model was 0.74, suggesting good model discrimination. The deviance probability value was 0.12, and the Hosmer-Lemeshow statistic was not significant, indicating little departure from a perfect fit (²=4.3; df=7; P=0.75). Figure 1 plots expected deaths versus observed deaths over the risk categories.

View this table: [in this window] [in a new window]   Table 4. Prediction Models

View larger version (15K): [in this window] [in a new window]   Figure 1. Observed vs predicted death for acute type A aortic dissection.

Variables Score and the Bedside Risk Prediction Tool
The risk variables and their allocated scores are listed in Table 4. Kidney failure was given the highest score (1.6), whereas sex was given the lowest score (0.3), with other variable scores being in between these values [hypotension/shock/tamponade (1.1), abrupt onset of pain (1.0), age 70 (0.5), and abnormal ECG on presentation (0.6)]. There was a good agreement between observed and predicted death over score categories (Figure 2.). The simple bedside risk prediction tool is shown in the Appendix and in Table 4.

View larger version (48K): [in this window] [in a new window]   Figure 2. Observed vs predicted death for acute type A aortic dissection based on risk score. Note that as the score increases, the predicted and observed mortality rates increased.

	Discussion

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High In-Hospital Mortality Rates in Patients With Type A Acute Aortic Dissection
The present study shows that in-hospital mortality rates in patients with type A acute aortic dissection remain high, with nearly 1 of 3 patients dying, even in centers that have extensive expertise and interest in the treatment of these high-risk patients. Furthermore, it identifies rupture of the dissecting aorta to be the cause of death in roughly one third of these patients. This high mortality rate in an era of advanced surgical techniques and increasing expertise of anesthesiologists, cardiologists, and cardiac and vascular surgeons in treating this disorder may be a result of inclusion in this study of all patients seen at these sites rather than patients selected to undergo surgery. The inclusion of patients who were too ill for surgery or died before they received surgical repair may explain part of the increased mortality rate. Also, the mean age of the patients in the present study was higher than that in any of the prior investigations, and because age is an important predictor of adverse outcomes, this may also have contributed to higher mortality rate in our study.

Clinical Variables Associated With High In-Hospital Mortality Rates and Their Implications
Our study identified several clinical variables to be important predictors of death in patients with acute type A dissection (Table 3) that are similar to those reported in prior studies (Table 4). ^{5,11–14,16,17,24} The similarities of variables predicting in-hospital death in these prior reports and our study support the clinical relevancy of the current predictive model. That older age is associated with worse outcomes is not surprising and is consistent with prior reports.^11,13,14 Abrupt onset of chest, neck, or back pain may be a manifestation of more sudden, severe, and extensive tearing and thus may have independently predicted greater risk of death in our study.

A common theme in prior publications as well as in our study is that rupture and complications such as hypotension, shock, cardiac tamponade, pulse deficits, and kidney failure confer an even higher mortality rate. These findings may have obvious therapeutic implications, which in turn may result in a significant effect on the overall patient survival. Aggressive surgical correction of the dissecting aneurysm may not only help prevent rupture but also is the only option that will provide a reasonable chance of survival to these individuals with otherwise dismal outcome. Many complications in patients with acute aortic type A dissection may be similarly prevented by earlier and more aggressive surgical treatment. If complications have already developed, attempts should be made to try and minimize their deleterious effect by establishing effective visceral (renal, cerebral, mesenteric) blood flow and relieving organ ischemia in a timely fashion either through surgery or by percutaneous techniques such as fenestration and/or endoluminal stents followed by definitive surgical repair. This latter approach is less invasive and can quickly restore vital organ perfusion so that the patient with malperfusion can be stabilized and then go on to have a successful repair. Preliminary results of this approach at our institution as well as other sites have been encouraging.^25–28

Risk Prediction Bedside Tool for Predicting Death
The present study incorporated variables at presentation that were independently associated with death into a simple risk prediction tool that is relatively accurate in predicting risk of death in patients with acute type A aortic dissection (Table 4). The model risk prediction estimates should help clinicians while making recommendations about different treatment options for individual patients with type A dissection. Like risk prediction tools for other cardiovascular diseases, this tool should be used by physicians for counseling patients and their families in helping them to understand their predicted risk and to have realistic expectations in terms of outcomes, especially in those deemed to be at high risk for in-hospital death. Model predictions should not necessarily be used to deny aggressive treatment in such patients who otherwise have a dismal prognosis. Finally, the prediction tool should be helpful in evaluating effects of new approaches and diagnostic methods as IRAD goes forward.

Uniqueness of the Present Study
Important differences between our study and prior investigations need to be highlighted. Most prior studies included a small number of patients from a single center with type A and B acute or chronic aortic dissection, whereas our analysis was performed on a large number of patients with only acute type A dissection presenting to 18 different IRAD sites. Furthermore, unselected consecutive patients with type A aortic dissection, irrespective of treatment strategies (surgical or medical), were analyzed in contrast to most prior investigations, which evaluated only the surgical cohort (Table 5). Thus, the findings of our study can be generalized to patients with acute type A dissection having a broad spectrum of clinical presentation across diverse medical institutions. Finally, this study provides an important risk prediction tool that allows accurate estimation of a patient’s in-hospital risk of death at the bedside through the use of readily available clinical information at presentation. This tool could also be valuable in outcome research to estimate risk-adjusted outcomes while comparing different subgroups of patients with type A dissection.

View this table: [in this window] [in a new window]   Table 5. Studies Predicting Death in Patients With Type A Aortic Dissection

Limitations of Our Study
The results of our study should not be generalized to patients with chronic stable type A dissection or to patients who are selected to undergo surgery. We measured only one easily and reliably measurable outcome domain, in-hospital death, which, although important to patients, is not sufficient for the full evaluation of patients with type A aortic dissection. Our focus on death as the only outcome should not diminish the importance of other outcome variables such as nonfatal adverse events, patient functional status, patient satisfaction, and resource use. Future studies are needed to address the best approach for evaluating the predictors of these other domains.

Conclusions
Our study supports prior observations that acute type A dissection is associated with high morbidity and mortality rates despite recent advances in treatment. This study further indicates that multiple factors affect in-hospital death and help to identify these predictors. In addition, it provides a useful, simple, bedside risk prediction tool that could be used by physicians not only for determining the prognosis of patients and counseling them and their families regarding their risks but also as a research tool to better understand the impact of newer diagnostic and therapeutic technological advances in the treatment of patients with acute type A aortic dissection.

Appendix
Score=Age · 0.5331 + Sex · 0.3244 + Abrupt Onset Chest Pain at Presentation · 0.9569 + Pulse Deficit at Presentation · 0.7089 + Abnormal ECG at Presentation · 0.5714 · Renal Failure at Presentation or Before Surgery · 1.5616 + Hypotension/Shock/Tamponade at Presentation · 1.0876, with Age an indicator for Age 70; Sex an indicator with female=1, male=0; and the other variables being indicators for respective conditions. Note logit (probability of in-hospital death)=Score + (-2.94), where -2.94 is the intercept.

Received August 8, 2001; revision received November 2, 2001; accepted November 5, 2001.

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