Case Presentation: A 83-year-old woman of Chinese origin with remote history of breast cancer and pulmonary fibrosis of unknown etiology presented to care with one month of fevers, night sweats, malaise, and cough. After three negative acid-fast bacillus (AFB) smears and CT chest showing chronic right apical scarring during hospital admission, she was discharged on oral antibiotics for suspected community acquired pneumonia and COPD exacerbation. Several weeks later, she was admitted to the hospital with persistent fevers, night sweats, and malaise. Working diagnoses included infectious, malignant, and inflammatory etiologies. Infectious Disease experts were consulted several days into her hospital course and recommended repeat AFB smear with nucleic acid amplification test (NAAT). She was discharged again after three negative AFB smears and with her tuberculosis NAAT result pending. She had planned follow-up after her hospitalization with her primary care provider. Two days after discharge, her primary physician was notified of the positive NAAT result.
Discussion: Factors at multiple levels — patient, provider cognition, diagnostic testing, and health system — likely contributed to the delayed diagnosis of pulmonary tuberculosis for this case. The woman’s complex history of pulmonary fibrosis, COPD, and underlying structural lung damage may have led to anchoring and premature closure on diagnoses other TB. Importantly, given the limited sensitivity of AFB smears alone when pulmonary TB is suspected, providers were likely falsely reassured by negative AFB smears during two different hospital admissions. This erroneous Bayesian reasoning was enabled by the hospital’s TB evaluation algorithm that messaged three negative AFB smears as sufficient for TB “rule-out”. Furthermore, NAAT was not part of the hospital’s TB evaluation algorithm and was a send-out test requiring several days of waiting until the results returned.
Conclusions: Pulmonary TB is a “can’t miss” diagnosis: the individual and public health implications are morbid if diagnosis is missed or delayed. Patient, provider, diagnostic testing, and health system “risk factors” can all contribute to delayed or missed pulmonary TB diagnosis. Providers and institutions must be particularly mindful of the limited test characteristics of microbiological testing for TB. Individual providers should incorporate their pre-test probability of TB when interpreting TB testing results to avoid fallacies in Bayesian reasoning. Hospitals should strongly consider the addition of NAAT to standard “rule-out” algorithms for evaluating pulmonary TB and should educate providers on institution-specific TB testing algorithms.