Current guidelines for the control of nosocomial transmission of tuberculosis (TB) recommend respiratory isolation for all patients with suspected TB. Application of these guidelines has resulted in many patients without TB being isolated on admission to the hospital, significantly increasing hospital costs. This study was conducted to prospectively validate a clinical decision rule to predict the need for respiratory isolation in inpatients with suspected TB.
A cohort of 516 individuals, who presented to 2 New York City hospitals between January 16, 2001, and September 29, 2002, and who were isolated on admission for clinically suspected TB, were enrolled in the study. Face-to-face interviews were conducted to determine the presence of clinical variables associated with TB in the prediction model, including TB risk factors, clinical symptoms, and findings from physical examination and chest radiography.
Of the 516 patients, 19 were found to have TB (prevalence, 3.7%; 95% confidence interval [CI], 2.2%-5.7%). The prediction rule had a sensitivity of 95% (95% CI, 74%-100%) and a specificity of 35% (95% CI, 31%-40%). Using a prevalence of TB of 3.7%, the positive predictive value was 9.6% and the negative predictive value was 99.7%.
Among inpatients with suspected active pulmonary TB who are isolated on admission to the hospital, a prediction rule based on clinical and chest radiographic findings accurately identified patients at low risk for TB. Approximately one third of the unnecessary episodes of respiratory isolation could have been avoided had the prediction rule been applied. Future studies should assess the feasibility of implementing the rule in clinical practice.
Nosocomial transmission of tuberculosis (TB) has become a major concern in the United States, especially transmission of strains that are resistant to antituberculous agents.1–7 In response to this threat to health care workers and patients, the Centers for Disease Control and Prevention issued guidelines for controlling the transmission of TB in heath care institutions.8 These guidelines are based on early identification and isolation of all patients considered to be at risk for the disease. Specifically, the Centers for Disease Control and Prevention recommendations dictate that patients should be placed in single-bed, negative-pressure rooms until the results of 3 acid-fast bacilli (AFB) smears are negative.
Although these policies have been shown to decrease the rate of TB transmission in certain institutions,9,10 delayed recognition and isolation of patients with active TB stills occurs.11–15 Delayed diagnosis often arises because clinicians vary in their experience with and ability to recognize TB.16,17 Current guidelines have also resulted in many patients at low risk for TB being isolated unnecessarily.18–21 In a low-endemic area, for example, TB was confirmed in only 1 of 92 patients who were isolated.21 As the incidence of TB in the United States continues to decline,22 the problem of excessive isolation may become even more significant. Thus, the present strategy of systematic isolation results in the mismanagement of many patients and generates unnecessary expenses for hospitals.
To address this problem, we developed a decision rule that allows physicians to assess TB risk.20 We used a case-control design to identify clinical and chest radiographic findings associated with the presence of TB; these findings were then used to construct a decision rule. The resulting rule comprises 6 clinical findings: TB risk factors or symptoms (exposure to an individual with TB, institutionalization [prison, shelter, or nursing home] in the past 3 years, homelessness, weight loss [≥10% of body weight], night sweats for ≥3 weeks, symptoms of malaise or weakness for >3 months, and persistent fever), self-reported positive purified protein derivative test results, fever (<38.5°C, 38.5°C-39.0°C, and >39.0°C), shortness of breath, crackles on physical examination, and upper lobe disease on chest radiographs (Table 1). Shortness of breath and crackles on examination are negative predictors in the model because they are associated with the absence of TB. When applied to the derivation population, the decision rule had a sensitivity of 98% and a specificity of 46%.
Clinical prediction rules frequently do not perform as well when tested in patients other than those from whom the rule was derived.23,24 The objective of the present study is to prospectively validate the decision rule. The model was applied to a new set of patients to determine its classification accuracy and its potential to reduce the number of unnecessary episodes of respiratory isolation.