Diagnostic Value of Cerebrospinal Fluid T-SPOT.TB for Tuberculousis Meningitis in China.

The aim of this study was to evaluate the diagnostic value of the cerebrospinal fluid (CSF) T-SPOT.TB test for the diagnosis of TB meningitis (TBM). A retrospective analysis of 96 patients with manifested meningitis was conducted; T-SPOT.TB test was performed for diagnosing TBM to determine the diagnostic sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). A receiver operating characteristic (ROC) curve was also drawn to assess the diagnostic accuracy. The sensitivity, specificity, PPV, and NPV of CSF T-SPOT.TB test were 97.8%, 78.0%, 80.3%, and 97.5%, respectively, for 52 patients (54.2%) of the 96 enrolled patients. The area under the curve (AUC) was 0.910, and the sensitivities of CSF T-SPOT.TB for patients with stages I, II, and III of TBM were 96.7%, 97.2%, and 98.9%, respectively. CSF T-SPOT.TB test is a rapid and accurate diagnostic method with higher sensitivity and specificity for diagnosing TBM.

Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in YunnanBorder Regions.

Objective: This study employs the Geographically and Temporally Weighted Regression (GTWR) model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks, emphasizing the spatial-temporal variability of these factors in border regions. Methods: We conducted a descriptive analysis of dengue fever's temporal-spatial distribution in Yunnan border areas. Utilizing annual data from 2013 to 2019, with each county in the Yunnan border serving as a spatial unit, we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region. Results: The GTWR model, proving more effective than Ordinary Least Squares (OLS) analysis, identified significant spatial and temporal heterogeneity in factors influencing dengue fever's spread along the Yunnan border. Notably, the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence, meteorological variables, and imported cases across different counties. Conclusion: In the Yunnan border areas, local dengue incidence is affected by temperature, humidity, precipitation, wind speed, and imported cases, with these factors' influence exhibiting notable spatial and temporal variation.