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OBJECTIVE To establish the diagnostic nomogram for tuberculous pleurisy (TP) based on TB-interferon-gamma release assays (TB-IGRA), as well as clinical and peripheral blood characteristics.MATERIAL AND METHODS Patients who underwent TB-IGRA tests during hospitalisation and were finally diagnosed, were retrospectively and continuously enrolled. TP was divided into confirmed TP (cTP) and presumptive TP (pTP), and corresponding diagnostic nomograms were established.RESULTS A total of 1283 patients were enrolled (median age 49 years, range 14-96; males 63.1%). The area under the curve (AUC) of TB-IGRA was 0.81 (95%CI 0.77-0.84) for cTP (n = 272) and 0.74 (95%CI 0.71-0.78) for pTP (n = 644). The false-positive and negative rates of TB-IGRA among non-TP and cTP were respectively 32.4% and 16.8%. Based on LASSO analysis, we then selected respectively 12 and 10 predictors from clinical and peripheral blood characteristics to establish cTP and pTP nomograms (TB-IGRA was selected). The cTP and pTP nomograms had an AUC of 0.93 (95%CI 0.90-0.95) and 0.92 (95%CI 0.90-0.94) in the training group, and 0.91 (95%CI 0.87-0.96) and 0.93 (95%CI 0.89-0.96) in the validation group, respectively, which were superior to TB-IGRA test alone.CONCLUSION Novel predictive nomograms with less invasiveness were provided based on TB-IGRA test to assist differential diagnosis of TP and non-TP patients.BACKGROUND Secondhand smoke (SHS) exposure cause of morbidity and mortality, especially in non-smokers and children. This study tested the effectiveness of an intervention for reducing exposure to SHS in homes by creating smoke-free environment where 1 to 5-year old infants reside.METHODS A cluster randomised controlled trial was conducted in a rural geographic area of Thailand, with 47 villages assigned to either an intervention or a comparison group. The intervention consisted of self-education and infographic material, together with 45 text messages delivered via short message service. The control group received the self-education after the intervention at 3 months. The primary outcome was assessed by parent´s self-reported in exposure to SHS in home. Multiple logistic regression was used to test the effect of the intervention.RESULTS The effects of the intervention increased the likelihood of a reducing exposure to SHS at home by 1.8-fold (95%CI 1.04 to 3.11). The average number of days of SHS exposure at home (7 days) also decreased by -1.25-fold (95%CI -1.85 to -0.66) in the intervention group.CONCLUSION The effectiveness of the intervention in reducing SHS exposure at home by a creating a smoke-free environment was observed to be statistically significant.INTRODUCTION Patients being treated for TB may suffer reductions in health-related quality of life (HRQoL). This study aims to assess the extent of such reductions and the trajectory of HRQoL over the course of treatment in rural Malawi.METHODS We collected patient demographic and socioeconomic status, TB-related characteristics, and HRQoL data (i.e., EQ-5D and a visual analogue scale VAS) from adults (age ≥18 years) being treated for TB in 12 primary health centers and one hospital in rural Thyolo District, Malawi, from 2014 to 2016. Associations between HRQoL and patient characteristics were estimated using multivariable linear regression.RESULTS Inpatients (n = 197) consistently showed lower median HRQoL scores and suffered more severe health impairments during hospitalization than outpatients (n = 156) (EQ5D and VAS 0.79, 55 vs. 0.84, 70). UGT8-IN-1 mw Longer treatment duration was associated with higher HRQoL among outpatients (EQ5D 0.034 increase per 2 months, 95%CI 0.012-0.057). We found no substantial associations between patients´ demographic and socioeconomic characteristics and HRQoL in this setting.CONCLUSION HRQoL scores among patients receiving treatment for TB in rural Malawi differ by clinical setting and duration of treatment, with greater impairment among inpatients and those early in their treatment course.Following the introduction of new effective antifibrotic drugs, interest in fibrosing interstitial lung diseases (FILD) has been renewed. In this context, radiological evaluation of FILD plays a cardinal role. Radiological diagnosis is possible in about 50% of the cases, which allows the initiation of effective therapy, thereby avoiding invasive procedures such as surgical lung biopsy. Usual interstitial pneumonia (UIP) pattern may be diagnosed based on clinical, radiological, and pathological data. High-resolution computed tomography features of UIP have been widely described in literature; however, interpreting them remains challenging, even with specific expertise on the subject. Diagnostic difficulties are understandable given the continuous evolution of FILD classifications and their complexity. Both early-stage diseases and advanced or combined patterns are not easily classifiable, and many end up being labelled 'indeterminate´ or 'unclassifiable´. Especially in these cases, optimal patient management involves collaboration and communication between different specialists. Here, we discuss the most critical aspects of radiological interpretation in FILD diagnosis based on the most recent classifications. We believe that the clinicians´ awareness of radiological diagnostic issues of FILD would improve comprehension and dialogue between physicians and radiologists, leading to better clinical practice.Randomized clinical trials represent the gold standard in therapeutic research. Nevertheless, observational cohorts of patients treated for multidrug-resistant TB (MDR-TB) or rifampin-resistant TB (RR-TB) also play an important role in generating evidence to guide drug-resistant TB care. Generally, summary exposure classifications (e.g., 'ever vs. never´, 'exposed at baseline´) have been used to characterize drug exposure in the absence of detailed longitudinal data on MDR-TB regimen changes. These summary classifications, along with an absence of data on covariates that change throughout the course of treatment, constrain researchers´ ability to answer the most relevant questions while accounting for known biases. In this paper, we highlight the importance of regimen changes in improving inference from observational studies of longer MDR-TB treatment regimens, and offer an overview of the data and analytic strategies required to do so.

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