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BackgroundTreating complicated urinary tract infections (cUTIs) caused by ESBL-producing Enterobacterales represents a significant clinical challenge. The present study was thus developed to explore the relative efficacy of β-lactam/β-lactamase inhibitors (BLBLIs) and carbapenems for the treatment of hospitalized patients suffering from cUTIs caused by BLBLI-susceptible ceftriaxone-non-susceptible Enterobacterales.MethodsData from 557 patients from four Chinese teaching hospitals diagnosed with cUTIs caused by ceftriaxone-non-susceptible Enterobacterales from January 2017 to May 2022 were retrospectively assessed.ResultThe 30 day rate of treatment failure, defined by unresolved symptoms or mortality, was 10.4% (58/557). Independent predictors of 30 day treatment failure included immunocompromised status, bacteraemia, septic shock, lack of infection source control and appropriate empirical treatment. When data were controlled for potential confounding variables, BLBLI treatment exhibited a comparable risk of 14 day (OR 1.61, 95% CI 0.86–3.00, P = 0.133) and 30 day treatment failure (OR 1.45, 95% CI 0.66–3.15, P = 0.354) relative to carbapenem treatment for the overall cohort of patients. In contrast, BLBLI treatment in immunocompromised patients was associated with an elevated risk of both 14 day (OR 3.18, 95% CI 1.43–7.10, P = 0.005) and 30 day treatment failure (OR 3.06, 95% CI 1.07–8.80, P = 0.038) relative to carbapenem treatment.ConclusionsThese results suggested that carbapenem treatment may be superior to BLBLI treatment for immunocompromised patients suffering from cUTIs caused by ceftriaxone-non-susceptible Enterobacterales species. However, these results will need to be validated in appropriately constructed randomized controlled trials to ensure appropriate patient treatment.

Background and Objectives. The identification of reliable biomarkers is critical to the diagnosis and prevention of progression from latent tuberculosis infection (LTBI) to active tuberculosis (ATB). This study was thus developed to identify key hub genes capable of differentiating between LTBI and ATB through a weighted gene coexpression network analysis (WGCNA) approach. Methods. Three Gene Expression Omnibus (GEO) microarray datasets (GSE19491, GSE98461, and GSE152532) were downloaded, with GSE19491 and GSE98461 then being merged to form a training dataset. Hub genes capable of differentiating between ATB and LTBI were then identified through differential expression analyses and a WGCNA analysis of this training dataset. Receiver operating characteristic (ROC) curves were then used to gauge to the diagnostic accuracy of these hub genes in the test dataset (GSE152532). Gene expression-based immune cell infiltration and the relationship between such infiltration and hub gene expression were further assessed via a single-sample gene set enrichment analysis (ssGSEA). Results. In total, 485 differentially expressed genes were analyzed, with the WGCNA approach yielding 8 coexpression models. Of these, the black module was the most closely correlated with ATB. In total, five hub genes (FBXO6, ATF3, GBP1, GBP4, and GBP5) were identified as potential biomarkers associated with LTBI progression to ATB based on a combination of differential expression and LASSO analyses. The area under the ROC curve values for these five genes ranged from 0.8 to 0.9 in the test dataset, and ssGSEA revealed the expression of these genes to be negatively correlated with lymphocyte activity but positively correlated with myeloid and inflammatory cell activity. Conclusion. The five hub genes identified in this study may play a novel role in tuberculosis-related immunopathology and offer value as novel biomarkers differentiating LTBI from ATB.

There are few nomograms for the prognosis of Chinese patients with triple-negative breast cancer (TNBC).To construct and validate a nomogram for overall survival (OS) of Chinese TNBC patients after surgery.This study used the data of SEER*stat 8.3.5 and selected Chinese patients with TNBC operated on between 2010 and 2015. Univariate and multivariate Cox proportional hazard regression models were used. The identified variables were integrated to form a predictive nomogram and risk stratification model; it was assessed with C-indexes and calibration curves.The median and maximal OS of the 336 patients was 39 and 83 mo, respectively. The multivariate analysis showed that age (The nomogram provided prognostic superiority over the traditional tumor, node and metastasis system. It could help clinicians make individual OS or risk predictions for Chinese TNBC patients after surgery.