Date Published: February 28, 2019
Publisher: Public Library of Science
Author(s): Duc T. Nguyen, Saroochi Agarwal, Edward A. Graviss, Daniela Flavia Hozbor.
As the most severe form of tuberculosis (TB), TB meningitis (TBM) is still associated with high mortality even in developed countries. In certain areas of the United States (U.S.), more than 50% of the TBM patients die with TB or have neurological sequelae and complications despite the availability of advanced health care. This population-based analysis aimed to determine the risk factors and trends associated with TBM morbidity and mortality using state-wide surveillance data.
De-identified surveillance data of all confirmed TB patients from the state of Texas between 01/2010 and 12/2017 reported to the National TB Surveillance System was analyzed. Spatial distribution of TBM cases was presented by Stata’s Geographic Information Systems mapping. Univariate and multiple generalized linear modeling were used to identify risk factors associated with meningitis morbidity and mortality. Non-parametric testing was used to analyze morbidity and mortality trends.
Among 10,103 TB patients reported in Texas between 2010 and 2017, 192 (1.9%) had TBM. During this 8-year period, the TBM proportion fluctuated between 1.5% and 2.7% with peaks in 2011 (2.7%) and 2016 (2.1%) and an overall non-significant trend (z = -1.32, p = 0.19). TBM had a higher mortality at diagnosis (8.9%), during treatment (14.1%) and overall (22.9%) compared to non-TBM (1.9%, 5.3%, and 7.2%, respectively, p<0.001). While mortality during treatment was unchanged over time in non-TBM patients (z = 0.5, p = 0.62), it consistently increased in TBM patients after 2013 (z = 3.09, p = 0.002). TBM patients had nearly five times the risk for overall death in multivariate analysis [aRR 4.91 (95% CI 3.71, 6.51), p<0.001]. TBM patients were younger, and more likely to present with miliary TB or HIV (+). Age ≥45 years, resident of a long-term care facility, IDU, diabetes, chronic kidney disease, abnormal chest radiography, positive AFB smear or culture and HIV (+) were independently associated with higher mortality. TBM remains challenging in Texas with significantly high mortality. Risk factors determined by multivariate modeling will inform health professionals and lay a foundation for the development of more effective strategies for TBM prevention and management.
In 2017, an estimate of 6.4 million new tuberculosis (TB) patients were reported globally and 14% were diagnosed as extrapulmonary TB (EPTB) . Tuberculous meningitis (TBM), a form of extrapulmonary TB and the most severe TB form, is an infection of the protective membranes (meninges) covering the central nervous system (CNS) by the Mycobacterium tuberculosis (Mtb). The diagnosis for TBM is clinically challenging and TBM treatment is difficult due to the poor blood–brain barrier penetrance of anti-TB medications . The disease is associated with high mortality even in developed countries [3–5]. Despite the availability of advanced health care, more than 50% of TBM patients may have neurological sequelae and complications or die. More than two-thirds of the neurological complications occurred within the initial hospitalization and the mortality ranged from 19.3% to 21.5% [6, 7].
Our analysis using state-wide surveillance data found a significantly higher proportion of TBM in Texas compared with the national average . From 2010 through 2017, no significant decrease was found in the trend of TBM in Texas. While the overall mortality in non-TBM patients significantly decreased over time from 2010 through 2017, trend analysis did not observe a similar trend in the cohort of TBM patients. Importantly, mortality in TBM patients was consistently higher compared with non-TBM patients during the 8 years of surveillance data analyzed.
TBM remains a challenge in Texas with significantly higher mortality despite the availability of advanced health care facilities. The study’s findings confirm the need for more extensive studies to inform clinicians and other health professionals, as well as, develop more practical algorithms to promptly identify patients with higher risks for mortality and effectively manage TBM patients after identification.