br Introduction Tuberculous TB pericarditis accounts for of

Introduction Tuberculous (TB) pericarditis accounts for 50–70% of pericardial disease in Africa (Mayosi et al., 2005, 2006, 2008). Mortality rates range between 17 and 60% (Mayosi et al., 2008; Pusch et al., 2014; Shaw et al., 2010). The Investigation of the Management of Pericarditis (IMPI) registry, a prospective observational study, revealed a case fatality rate of 26% within 6-months of diagnosis (Mayosi et al., 2008). Several host-factors were independent predictors of this early mortality, including the presence of HIV infection, increasing age, and concurrent pulmonary TB (Mayosi et al., 2008). However, these patients were followed up for only 6months, and a definitive TB pericarditis diagnosis was confirmed in only 7% of patients. Thus, factors predictive of long-term outcomes in patients with proven TB pericarditis still need to be identified. Here, we identified factors predictive of long-term outcome using classification and regression tree (CART) analyses. We used CART because we did not want to use a model that pre-specified the important potential predictors. Instead we wanted a distribution- and assumption-free method to identify the predictors in the context of all potential clinical and laboratory factors. We also wanted to rank the predictors, in order to allow clinical decision making as to which factors to modify first to have the largest impact on reducing TB pericarditis mortality. TB pericarditis is considered to be a paucibacillary process, and the large pericardial fluid accumulation is attributed to an tropisetron caused by a few tuberculoproteins (Cherian, 2004; Fowler, 1991). For that reason, the same regimen and doses used for pulmonary TB, and for the same duration, are administered to patients with extra-pulmonary TB including TB pericarditis (Mayosi et al., 2005, 2006, 2008, 2002; Pusch et al., 2014; Shaw et al., 2010; Cherian, 2004; Fowler, 1991). However, the baseline bacillary burden or temporal changes in bacillary load with therapy are yet to be rigorously quantified. These microbial factors are known to be important determinants of outcome in patients on the same type of standard therapy for pulmonary TB (Bowness et al., 2015; Diacon et al., 2010; Chigutsa et al., 2013, 2015). Here, we used the IMPI registry to investigate microbial, clinical, echocardiography and hemodynamic factors as possible predictors of long term death. Uniquely, we had an access to quantitative microbiology information based on liquid culture, which is known to better capture larger populations of Mycobacterium tuberculosis (Mtb) than solid agar techniques.
Methods
Results The laboratory and clinical characteristics of patients at enrolment are shown in Table 1. These were the same in patients with TB confined to pericardium compared to those with TB pericarditis and evidence of TB in another body organ; the only difference was midbrain antiretrovirals were used more commonly in the latter group (4/6 patients) compared to the former (5/38). Cardiac tamponade, either at presentation or in the course of TB therapy, was observed in 3/70 (4%) patients. The CD4+ T cell counts for 53/70 (80%) of patients shown Fig. 1 reflect overall immunosuppression in study patients. The median follow-up duration was 11.97 (range: 0·03–74.73) months. Of the 70 patients, 16 (23%) died during the 75-month follow-up period. The overall mortality rate was 1.43 per 100 person-month follow-up. To put the pericardial Mtb burden into context, 18 sputum samples from 18 randomly chosen patients with pulmonary TB, based on a South African reference laboratory, were compared to 70 pericardial fluid samples from IMPI patients. The pulmonary TB patients had a median age of 40 (range 22–44) years compared to 35 (range 30–71) years of those with pericardial TB (p=0.600). Fig. 2A shows the bacillary burden in terms of TTP, while Fig. 2B shows the bacillary burden as log10CFU/mL based on the more conservative formula. The median TTP for pericardial samples was 22 (range 4 to 58) days and that for sputum was 12 days (p<0.001). Fig. 2B shows that even though overall bacillary burden was significantly higher in sputum samples (mean difference 2.22±0.34log10CFU, p<0.001), the mean baseline bacillary load for pericardial fluid samples (3.86±0.21log10CFU), was substantial and inconsistent with a paucibacillary process. The baseline CFU/mL in pericardial fluid is higher (median=8.55log10CFU/mL) using a different but more stringent modeling approach (Fig. 3).