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doi:10.1378/chest.06-1687
(Chest. 2007; 131:489-496)
© 2007 American College of Chest Physicians
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Discriminating Inhalational Anthrax From Community-Acquired Pneumonia Using Chest Radiograph Findings and a Clinical Algorithm*

Demetrios N. Kyriacou, MD, PhD; Paul R. Yarnold, PhD; Adam C. Stein, BS; Brian P. Schmitt, MD, MPH; Robert C. Soltysik, MS; Regina R. Nelson, BS, RN; Ralph R. Frerichs, DVM, DrPH; Gary A. Noskin, MD; Steven M. Belknap, MD and Charles L. Bennett, MD, PhD

* From the Department of Emergency Medicine (Drs. Kyriacou and Yarnold, Mr. Stein, and Ms. Nelson), the Divisions of Infectious Diseases (Dr. Noskin) and General Internal Medicine (Dr. Belknap), and the Center for Healthcare Studies (Dr. Bennett), Northwestern University Feinberg School of Medicine, Chicago, IL; the Department of Medicine (Dr. Schmitt), Loyola University Medical Center, Maywood, IL; the Jesse Brown VA Medical Center (Mr. Soltysik), Chicago, IL; and the Department of Epidemiology (Dr. Frerichs), UCLA School of Public Health, Los Angeles, CA.

Correspondence to: Demetrios N. Kyriacou, MD, PhD, Northwestern University Feinberg School of Medicine, Department of Emergency Medicine, 259 Erie St, Suite 100, Chicago, IL 60611; e-mail: dkyriacou{at}aol.com

Abstract

Background: Limiting the effects of a large-scale bioterrorist anthrax attack will require rapid and accurate detection of the earliest victims. We undertook this study to improve physicians’ ability to rapidly detect inhalational anthrax victims.

Methods: We conducted a case-control study to compare chest radiograph findings from 47 patients from historical inhalational anthrax cases and 188 community-acquired pneumonia control subjects. We then used classification tree analyses to derive an algorithm of chest radiograph findings and clinical characteristics that accurately and explicitly discriminated between inhalational anthrax and community-acquired pneumonia.

Results: Twenty-two of the 47 patients from historical inhalational anthrax cases (46.8%) had reported chest radiograph findings. All 22 case patients (100%) had mediastinal widening, pleural effusion, or both. However, 16 case patients (72.7%) also had infiltrates. In comparison, all 188 community-acquired control subjects had reported chest radiographs. Of these, 127 control subjects (67.6%) had infiltrates, 43 control subjects (22.9%) had pleural effusions, and 15 control subjects (8.0%) had mediastinal widening. A derived algorithm with three predictor variables (chest radiograph finding of mediastinal widening, altered mental status, and elevated hematocrit) is 100% sensitive (95% confidence interval [CI], 73.5 to 100) and 98.3% specific (95% CI, 95.1 to 99.6). The derivation process used 12 patients with inhalational anthrax and 177 control subjects with community-acquired pneumonia who had information available for all three variables.

Conclusions: There are significant chest radiograph differences between inhalational anthrax and community-acquired pneumonia, but none of the chest radiograph findings are both highly sensitive and highly specific. The derived clinical algorithm can improve physicians’ ability to discriminate inhalational anthrax from community-acquired pneumonia, but its utility is limited to previously healthy individuals and its accuracy may be limited by missing values.

Key Words: algorithm • anthrax • bioterrorist attack

Limiting the effects of a large-scale bioterrorist anthrax attack will require rapid and accurate detection of its earliest victims.1 Unfortunately, early recognition of persons with inhalational anthrax is difficult because its prodrome also characterizes many common acute respiratory illnesses.23 Since rapid diagnostic tests for anthrax are not widely available, victims may not be recognized until the onset of respiratory distress and shock.45 Despite this, physicians are relied on to provide early recognition and reporting of bioterrorism-related anthrax cases.6 Recent directors of the Centers for Disease Control and Prevention (CDC) have stated that, "all clinicians, regardless of their specialty, must have enough basic information about the clinical manifestations of infections caused by the select agents of bioterrorism to raise their suspicion when they see a patient with a compatible illness."7

In addition, public health departments have instituted syndromic surveillance systems to identify the first inhalational anthrax cases from a bioterrorist attack.891011 However, little progress has been made identifying specific sets of clinical characteristics that maximize the effectiveness of a surveillance system in detecting inhalational anthrax. For example, after the bioterrorist anthrax attacks in 2001, the CDC issued guidelines recommending the use of clinical characteristics to discriminate inhalational anthrax from other respiratory illnesses,1213 but an evaluation of these guidelines14 demonstrated that their use would have rapidly detected only one of the 11 cases from 2001.

Several prior studies15161718 have evaluated the ability of clinical characteristics to discriminate inhalational anthrax from various other illnesses. No study, however, has developed a highly sensitive and highly specific clinical method for explicitly discriminating inhalational anthrax from community-acquired pneumonia, which is the respiratory disease that is most likely to be considered in unrecognized cases of inhalational anthrax.19 Since chest radiography is generally used to assess patients with pneumonia, we undertook this study to determine whether chest radiograph findings can accurately discriminate inhalational anthrax from community-acquired pneumonia. We then mathematically derived an algorithm to enhance the accuracy of clinically discriminating inhalational anthrax from community-acquired pneumonia in order to improve the physician’s ability to rapidly recognize inhalational anthrax victims and to detect a bioterrorist attack.

Materials and Methods

Study Design
We conducted a case-control study to compare the chest radiograph findings of inhalational anthrax case patients and community-acquired pneumonia control subjects. We then conducted classification tree analyses to mathematically derive an algorithm of chest radiograph findings and clinical characteristics that accurately discriminates inhalational anthrax from community-acquired pneumonia. We used patient-specific information from 47 inhalational anthrax cases reported in the medical literature and 188 community-acquired pneumonia control subjects. The Northwestern University Institutional Review Board approved this study.

Selection of Cases
Since inhalational anthrax is extremely rare, we used patient-specific information from 11 bioterrorism-related cases and 36 naturally occurring cases that were identified through an extensive search of the MEDLINE database, textbooks, monographs, and Index Medicus. Only verified cases reported in the English language with sufficient patient-specific information to facilitate statistical comparisons were used. In a prior study,18 we found very few clinical, radiographic, or pathologic differences between bioterrorism-related cases and naturally occurring cases.

Selection of Control Subjects
We used emergency department control subjects because most of the bioterrorism-related case patients from 2001 were initially evaluated in this clinical setting.2021 We chose community-acquired pneumonia as the comparison disease because it is commonly seen in emergency departments and is the disease that is most likely to be considered in patients with unrecognized cases of inhalational anthrax.19 Control subjects were selected consecutively from January 1, 2000, to March 1, 2003, from computerized logs using search terms for presenting complaints and diagnosis of community-acquired pneumonia. Four control subjects were matched to each case patient based on age, gender, and race to maximize efficiency and limit confounding. Potential control subjects were excluded if they had medical conditions that might obscure or alter the clinical manifestations of community-acquired pneumonia. These medical conditions included the following: (1) underlying comorbidity related to immunosuppression, such as HIV/AIDS, transplant surgery, or chemotherapy; (2) cardiac disease, such as congestive heart failure; (3) pulmonary disease, such as asthma, chronic bronchitis, emphysema, sarcoidosis, pulmonary hypertension, or tuberculosis; (4) underlying neurologic manifestations, such as stroke, multiple sclerosis, or quadriplegia; (5) acute psychiatric conditions; and (6) acute alcohol intoxication.

Data Collection
Two trained research assistants (ACS and RRN) used standardized data collection instruments to independently abstract information from the historical reports of the case patients and the medical records of the control subjects. A physician investigator (DNK) then reviewed the abstracted information to reconcile any differences. For the case patients, we used information from their emergency department or hospital admission evaluation that had resulted in the diagnosis of inhalational anthrax. For case patients from the late 1800s and early 1900s who had not been hospitalized, this information was obtained from the most definitive clinical description. For the control subjects, we used information from their emergency department and hospital admission medical records.

Chest Radiograph Findings
Chest radiograph findings for the inhalational anthrax case patients were classified based on information abstracted from historical reports. Chest radiograph findings for the community-acquired pneumonia control subjects were classified based on information abstracted from the attending radiologists’ final reports. The findings were classified into the following categories: mediastinal widening (including hilar adenopathy) only; pleural effusion only; infiltrate only; mediastinal widening and pleural effusion; mediastinal widening and infiltrate; pleural effusion and infiltrate; mediastinal widening, pleural effusion, and infiltrate; nonspecific findings; and normal. The term infiltrate includes descriptions of focal density, opacity, and consolidation.

Algorithm Model Predictor Variables
For the algorithm model predictor variables, we used chest radiograph findings and clinical characteristics previously assessed for their individual predictive ability to discriminate inhalational anthrax from community-acquired pneumonia.18 These included historical, physical examination, laboratory, and chest radiograph variables representing information commonly obtained by physicians during the evaluation of patients with community-acquired pneumonia. Nausea, vomiting, pallor/cyanosis, diaphoresis, altered mental status (including history or physical examination finding of syncope, confusion, or coma), heart rate > 110 beats/min, temperature > 100.9°F, elevated hematocrit, and the chest radiograph finding of any mediastinal widening were all significantly more frequent in the inhalational anthrax case patients than in the community-acquired pneumonia control subjects.18 These variables were selected for possible inclusion into the derived algorithm.

Statistical Analysis
Proportions of the specific chest radiograph findings in the inhalational anthrax case patients and community-acquired pneumonia control subjects were estimated with exact binomial 95% confidence intervals (CIs). Inhalational anthrax case patients without reported chest radiograph findings were excluded from the analyses. Hierarchical classification tree analyses were used to create a multivariable, nonparametric, nonlinear discrimination model that maximizes the accuracy of disease outcome classification.2223 The model assessed parsimonious sets of predictor variables to derive a clinical algorithm with the greatest ability to discriminate inhalational anthrax from community-acquired pneumonia. To be used in the model derivation, the inhalational anthrax case patients and community-acquired pneumonia control subjects were required to have information available on all predictor variables included in the algorithm. To avoid overfitting, only predictor variables with stable classification performance in a jackknife validity analysis were entered into the model. Once the algorithm was created, we conducted bootstrap validity analyses with 10,000 iterations and 50% resampling to assess their potential cross-generalizability for classifying an independent random sample of patients. Sensitivity and specificity, with exact binomial 95% CI, were calculated for the algorithm.

Results

Twenty-two of the 47 inhalational anthrax case patients (46.8%) had chest radiographs taken with findings reported in their historical accounts. Only these inhalational anthrax case patients were included in our analyses. Their demographic characteristics, year, country, method of exposure, and survival status are presented in Table 1 .20212425262728293031323334353637383940414243 Comparisons of the chest radiograph findings for the inhalational anthrax case patients and the community-acquired pneumonia control subjects are presented in Table 2 . Of the 22 inhalational anthrax case patients with chest radiographs, 18 (81.8%) had mediastinal widening (resulting from mediastinal adenopathy) and 18 (81.8%) had pleural effusions seen on chest radiography. All 22 inhalational anthrax case patients (100%) had mediastinal widening, pleural effusion, or both. In addition, 16 of the inhalational anthrax case patients (72.7%) had infiltrates, but all of these case patients had additional findings of mediastinal widening, pleural effusion, or both. In comparison, all 188 control subjects had reported chest radiographs. Of these community-acquired pneumonia control subjects, 127 (67.6%) had infiltrates, 43 had pleural effusions (22.9%), and 15 (8.0%) had mediastinal widening. Only two control subjects (1.1%) had mediastinal widening as the only chest radiograph finding.


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  		Table 1.. Demographic Characteristics of Inhalational Anthrax Case Patients With Reported Chest Radiograph Findings*

 

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  		Table 2.. Distribution of Chest Radiograph Findings Between Inhalational Anthrax and Community-Acquired Pneumonia*

 
The derived algorithm of chest radiograph findings and clinical characteristics explicitly maximizes sensitivity and specificity for clinically discriminating inhalational anthrax from community-acquired pneumonia (Fig 1 ). This algorithm includes only three variables (chest radiograph finding of mediastinal widening, altered mental status, and raised hematocrit of > 45%) and is 100% sensitive (95% CI, 73.5 to 100) and 98.3% specific (95% CI, 95.1 to 99.6). The derivation process used 12 of the 47 inhalational anthrax case patients and 177 of the 188 matched community-acquired pneumonia control subjects who had information concerning all three variables included in the model.


Figure 1
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  		Figure 1.. Clinical algorithm for discriminating inhalational anthrax from community-acquired pneumonia. The sensitivity for inhalational anthrax is 100% (95% CI, 73.5 to 100), and the specificity for community-acquired pneumonia is 98.3% (95% CI, 95.1 to 99.6).

 
Discussion

We demonstrated that chest radiograph findings of inhalational anthrax are significantly different from those of community-acquired pneumonia. Unfortunately, none of these findings (alone or in combination) is both highly sensitive and highly specific for discriminating inhalational anthrax from community-acquired pneumonia. For example, the chest radiograph finding of mediastinal widening or pleural effusion (with or without any other finding) is 100% sensitive but only 71.8% specific. Conversely, the chest radiograph finding of mediastinal widening (with or without any other finding) is 92.0% specific, but only 81.8% sensitive.

Consequently, we derived an algorithm with additional clinical characteristics to improve the differentiation of inhalation anthrax from community-acquired pneumonia beyond the use of chest radiograph findings alone. Although the predictive ability of our algorithm is excellent, the CI of the sensitivity estimate is relatively wide because its derivation was based on information from the limited number of inhalational anthrax case patients who had information for all three predictor variables in the model. Since information for all three predictor variables was available for the vast majority of the matched community-acquired pneumonia control subjects, CI for the estimated specificity of our algorithm was comparatively narrow.

Three studies have also developed clinical schemes for discriminating inhalational anthrax from other diseases. Kuehnert et al15 developed clinical scoring systems based on the 11 bioterrorism-related case patients to discriminate inhalational anthrax from influenza-like illness with a sensitivity of 100% and a specificity of 96.1%, and community-acquired pneumonia with a sensitivity of 81.8% and specificity of 81.2%. Hupert et al16 developed a screening protocol for potential victims of a bioterrorist attack that compared historical case patients of inhalational anthrax and patients with "viral respiratory tract infections," but did not stipulate estimates of sensitivity and specificity. Howell et al17 developed a scoring system of symptoms and signs based on only two case patients to discriminate patients with inhalational anthrax from subjects with "all known symptoms and clinical presentations of acute pulmonary anthrax." This scoring system had a reported sensitivity of 100% and a specificity of 99.8%.

A main advantage of our mathematically derived algorithm is that it explicitly discriminates inhalational anthrax from community-acquired pneumonia, the most likely alternative infectious respiratory illness to be considered in the evaluation of patients with inhalational anthrax in the emergency department setting. The scoring system developed by Kuehnert et al15 for discriminating inhalational anthrax explicitly from community-acquired pneumonia is neither very sensitive nor specific and thus lacked useful clinical accuracy. Hupert et al16 and Howell et al17 did not specifically compare their inhalational anthrax case patients with community-acquired pneumonia control subjects.

We used an algorithmic approach to provide a clear format for symbolizing the decision-making solution for the problem of discriminating inhalational anthrax from community-acquired pneumonia.44 Algorithms have been successfully used in medicine for clinical teaching, evaluating clinical performance, constructing protocols, describing standards of care, and selecting the most cost-effective medical care strategies.44454647 The accuracy of our algorithm likely results from using classification tree analyses for its mathematical derivation, rather than an ad hoc derivation. Classification tree analyses have become increasingly popular in clinical research because these statistical methods readily lend themselves to the development of clinically useful diagnostic and screening algorithms.48 Our specific method of classification tree analysis, multivariable optimal discriminant analysis, has been developed over several years and has been successfully employed in several studies.2223495051

Since our algorithm was based on retrospectively collected information, it may be limited for two main reasons. First, our measurements of the predictor variables were from historical reports of the case patients and medical records of the control subjects, and are inherently subject to potential bias resulting from misclassified predictor variables and missing values. To limit misclassification, we used trained research assistants and a standardized data collection instrument to abstract information regarding the predictor variables from the historical reports of the case patients and from the medical records of the control subjects. We also reported our results based solely on observed data (ie, complete-case data) because the assessment of missing values would require information beyond the observed data that are not available and the methods for handling missing values can also result in biased estimations.5253 In addition, the clinical manifestation of inhalational anthrax can change rapidly, with symptoms and signs that are not initially present developing quickly.54

Second, a small proportion of our community-acquired pneumonia control subjects did not have definitive chest radiograph findings of pneumonia. While chest radiography is considered to be the "gold standard" for the diagnosis of pneumonia,55 its sensitivity and specificity are not well known, and case patients can present without a definitive infiltrate.56 For example, a large study of hospitalized adults with suspected pneumonia from 2004 found that approximately one third of the initial chest radiograph findings these patients were reported as "no pneumonia."57 In addition, there is considerable interobserver variation in the radiographic interpretation of suspected community-acquired pneumonia.5859 This especially applies to the recognition of mediastinal adenopathy and pleural effusions (which are prone to misinterpretation due to positioning or exposure variances), emphasizing the immense benefit of CT scans for the diagnosis of inhalational anthrax.40 Nonetheless, our community-acquired pneumonia control subjects had similar proportions of fever, cough, chest pain, and chest radiograph findings compared with subjects of studies of community-acquired pneumonia, suggesting that our control subjects accurately reflect the diverse clinicopathologic spectrum of this disease in the general population.60

Improving physicians’ ability to recognize inhalational anthrax victims in clinical settings enhances surveillance methods to detect an anthrax attack and save thousands of lives.2619 In fact, the CDC describes outbreak detection as the overriding purpose of syndromic surveillance for terrorism preparedness.9 Despite this goal, bioterrorism surveillance systems do not have standard syndromic case definitions, and most systems do not report sensitivities and specificities for detecting bioterrorism-related victims.6162 Systems that are not sensitive will fail to recognize cases and to detect attacks, while systems that are not specific will falsely report cases and trigger unnecessary public health responses. Our algorithm, in addition to the methods from prior studies, may help in the development of more accurate case definitions for the syndromic surveillance of anthrax. Information from all of the above-mentioned studies should be used to improve clinical detection and screening methods for discriminating inhalational anthrax from several acute respiratory illnesses.

Unfortunately, the implementation of any clinical method for recognizing inhalational anthrax is problematic because of its extremely rare occurrence and exceedingly low pretest probability. Nevertheless, algorithms that recognize possible inhalational anthrax victims would still be helpful to emergency and primary care physicians, pulmonary specialists, and radiologists. For example, the chest radiograph finding of mediastinal widening can be caused by many pathologic processes. However, mediastinal widening in a patient with fever, vomiting, altered mental status, or elevated hematocrit significantly narrows the list of potential causes, including inhalational anthrax. Because our algorithm was not prospectively assessed against a variety of inhalational pneumonias, its true utility is limited to otherwise previously healthy individuals specifically in the setting of an unexpected cluster of case patients presenting acutely to primary care offices or emergency departments. It may be possible to further reduce the number of false-positive reports of inhalational anthrax cases by including rapid laboratory tests that are currently being developed.636465 In this case, algorithms would still be useful in determining which patients with respiratory complaints should undergo the rapid tests. Future studies, using prospectively collected clinical information from control subjects with a broader spectrum of acute respiratory illnesses, should be conducted to corroborate, modify, or refute our findings.

Footnotes

Abbreviations: CDC = Centers for Disease Control and Prevention; CI = confidence interval

This study was supported by a Northwestern Memorial Hospital Excellence in Academic Medicine grant from the State of Illinois Department of Public Aid, a grant from the Department of Veterans Affairs (VA IIR 02–080-1), and a grant from the National Cancer Institute (1R01CA 102713-01).

The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Received for publication July 5, 2006. Accepted for publication September 1, 2006.

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