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Background Despite widespread availability of curative therapy, tuberculosis (TB) treatment outcomes remain suboptimal. Clinical prediction models can inform treatment strategies to improve outcomes. Using baseline clinical data, we developed a prediction model for unsuccessful TB treatment outcome and evaluated the incremental value of human immunodeficiency virus (HIV)–related severity and isoniazid acetylator status. Methods Data originated from the Regional Prospective Observational Research for Tuberculosis Brazil cohort, which enrolled newly diagnosed TB patients in Brazil from 2015 through 2019. This analysis included participants with culture-confirmed, drug-susceptible pulmonary TB who started first-line anti-TB therapy and had ≥12 months of follow-up. The end point was unsuccessful TB treatment: composite of death, treatment failure, regimen switch, incomplete treatment, or not evaluated. Missing predictors were imputed. Predictors were chosen via bootstrapped backward selection. Discrimination and calibration were evaluated with c-statistics and calibration plots, respectively. Bootstrap internal validation estimated overfitting, and a shrinkage factor was applied to improve out-of-sample prediction. Incremental value was evaluated with likelihood ratio–based measures. Results Of 944 participants, 191 (20%) had unsuccessful treatment outcomes. The final model included 7 baseline predictors: hemoglobin, HIV infection, drug use, diabetes, age, education, and tobacco use. The model demonstrated good discrimination (c-statistic = 0.77; 95% confidence interval,.73–.80) and was well calibrated (optimism-corrected intercept and slope, –0.12 and 0.89, respectively). HIV-related factors and isoniazid acetylation status did not improve prediction of the final model. Conclusions Using information readily available at treatment initiation, the prediction model performed well in this population. The findings may guide future work to allocate resources or inform targeted interventions for high-risk patients. [ABSTRACT FROM AUTHOR]

Background Severity stratification scores developed in intensive care units (ICUs) are used in interventional studies to identify the most critically ill. Studies that evaluate accuracy of these scores in ICU patients admitted with pneumonia are lacking. This study aims to determine performance of severity scores as predictors of mortality in critically ill patients admitted with pneumonia. Methods Prospective cohort study in a general ICU in Brazil. ICU severity scores (Simplified Acute Physiology Score 3 [SAPS 3] and Sepsis-Related Organ Failure Assessment [qSOFA]), prognostic scores of pneumonia (CURB-65 [confusion, urea, respiratory rate, blood pressure, age] and CRB-65 [confusion, respiratory rate, blood pressure, age]), and clinical and epidemiological variables in the first 6 hours of hospitalization were analyzed. Results Two hundred patients were included between 2015 and 2018, with a median age of 81 years (interquartile range, 67–90 years) and female predominance (52%), primarily admitted from the emergency department (65%) with community-acquired pneumonia (CAP, 80.5%). SAPS 3, CURB-65, CRB-65,and qSOFA all exhibited poor performance in predicting mortality. Multivariate regression identified variables independently associated with mortality that were used to develop a novel pneumonia-specific ICU severity score (Pneumonia Shock score) that outperformed SAPS 3, CURB-65, and CRB-65. The Shock score was validated in an external multicenter cohort of critically ill patients admitted with CAP. Conclusions We created a parsimonious score that accurately identifies patients with pneumonia at highest risk of ICU death. These findings are critical to accurately stratify patients with severe pneumonia in therapeutic trials that aim to reduce mortality. [ABSTRACT FROM AUTHOR]

Background Diagnosis of active tuberculosis (ATB) currently relies on detection of Mycobacterium tuberculosis (Mtb). Identifying patients with extrapulmonary TB (EPTB) remains challenging because microbiological confirmation is often not possible. Highly accurate blood-based tests could improve diagnosis of both EPTB and pulmonary TB (PTB) and timely initiation of anti-TB therapy. Methods A case-control study was performed using discriminant analyses to validate an approach using Mtb-specific CD4+T-cell activation markers in blood to discriminate PTB and EPTB from latent TB infection (LTBI) as well as EPTB from PTB in 270 Brazilian individuals. We further tested the effect of human immunodeficiency virus (HIV) coinfection on diagnostic performance. Frequencies of interferon-γ +CD4+T cells expressing CD38, HLADR, and/or Ki67 were assessed by flow cytometry. Results EPTB and PTB were associated with higher frequencies of CD4+T cells expressing CD38, HLADR, or Ki67 compared with LTBI (all P values <.001). Moreover, frequencies of HLADR+ (P =.03) or Ki67+ (P <.001) cells accurately distinguished EPTB from PTB. HIV infection did not affect the capacity of these markers to distinguish ATB from LTBI or EPTB from PTB. Conclusions Cell activation markers in Mtb-specific CD4+T cells distinguished ATB from LTBI and EPTB from PTB, regardless of HIV infection status. These parameters provide an attractive approach for developing blood-based diagnostic tests for both active and latent TB. [ABSTRACT FROM AUTHOR]

Background The role of genetic polymorphisms in latent tuberculosis (TB) infection and progression to active TB is not fully understood. Methods We tested the single-nucleotide polymorphisms (SNPs) rs5743708 (TLR2), rs4986791 (TLR4), rs361525 (TNFA), rs2430561 (IFNG) rs1143627 (IL1B) as risk factors for tuberculin skin test (TST) conversion or development of active TB in contacts of active TB cases. Contacts of microbiologically confirmed pulmonary TB cases were initially screened for longitudinal evaluation up to 24 months, with clinical examination and serial TST, between 1998 and 2004 at a referral center in Brazil. Data and biospecimens were collected from 526 individuals who were contacts of 177 active TB index cases. TST conversion was defined as induration ≥5 mm after a negative TST result (0 mm) at baseline or month 4 visit. Independent associations were tested using logistic regression models. Results Among the 526 contacts, 60 had TST conversion and 44 developed active TB during follow-up. Multivariable regression analysis demonstrated that male sex (odds ratio [OR]: 2.3, 95% confidence interval [CI]: 1.1–4.6), as well as SNPs in TLR4 genes (OR: 62.8, 95% CI: 7.5–525.3) and TNFA (OR: 4.2, 95% CI: 1.9–9.5) were independently associated with TST conversion. Moreover, a positive TST at baseline (OR: 4.7, 95% CI: 2.3–9.7) and SNPs in TLR4 (OR: 6.5, 95% CI: 1.1–36.7) and TNFA (OR: 12.4, 95% CI:5.1–30.1) were independently associated with incident TB. Conclusions SNPs in TLR4 and TNFA predicted both TST conversion and active TB among contacts of TB cases in Brazil. [ABSTRACT FROM AUTHOR]