Background: Data on the coincidence of Tuberculosis (TB) and Coronavirus disease 2019 (COVID-19) are limited. We sought to investigate the clinical characteristics and outcomes of coinfected patients in Henan and identify whether TB disease is associated with an increased risk of intensive care unit (ICU) admission and mortality.
Method: We conducted a retrospective matched cohort study of COVID-19 inpatients involving 41 TB-positive patients with 82 patients without TB. Leveraging data was collected from electronic medical records.
Results: There were no significant differences in clinical manifestations, the need for mechanical ventilation and vasopressors, ICU admission, or in-hospital mortality between 2 groups. TB-positive patients had a lower lymphocyte counts (1.24 ± 0.54 vs. 1.59 ± 0.58, = 0.01), B cells (99/µl vs. 201/µl, < 0.01), CD4+ T cells (382/µl vs. 667/µl, < 0.01), CD8+ T cells (243/µl vs. 423/µl, < 0.01), NK cells (145/µl vs. 216/µl, = 0.01), IL-2 (14.18 ± 11.23 vs. 31.86 ± 34.55, < 0.01) and TNF-α (3.42 ± 2.93 vs. 5.62 ± 3.69, < 0.01). Notably, the TB-positive group had a longer duration of SARS-CoV-2 shedding (67 days vs. 22 days, < 0.01).
Conclusions: Concomitant TB does not significantly impact clinical outcomes of hospitalised patients with acute COVID-19. However, TB-positive patients had longer duration of SARS-COV-2-RNA positivity.
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http://dx.doi.org/10.1080/23744235.2023.2245885 | DOI Listing |
Ann Neurol
January 2025
Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy.
Objective: Despite diagnostic criteria refinements, Parkinson's disease (PD) clinical diagnosis still suffers from a not satisfying accuracy, with the post-mortem examination as the gold standard for diagnosis. Seminal clinicopathological series highlighted that a relevant number of patients alive-diagnosed with idiopathic PD have an alternative post-mortem diagnosis. We evaluated the diagnostic accuracy of PD comparing the in-vivo clinical diagnosis with the post-mortem diagnosis performed through the pathological examination in 2 groups.
View Article and Find Full Text PDFMed Phys
January 2025
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.
Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.
Ann Surg Oncol
January 2025
Department of Surgery, National Defense Medical College, Tokorozawa, Saitama, Japan.
Background: Tumor size (TS) in pancreatic ductal adenocarcinoma (PDAC) is one of the most important prognostic factors. However, discrepancies between TS on preoperative images (TSi) and pathological specimens (TSp) have been reported. This study aims to evaluate the factors associated with the differences between TSi and TSp.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Disease, Shanghai, 200080, China.
The objectives of this study are to construct a deep convolutional neural network (DCNN) model to diagnose and classify meibomian gland dysfunction (MGD) based on the in vivo confocal microscope (IVCM) images and to evaluate the performance of the DCNN model and its auxiliary significance for clinical diagnosis and treatment. We extracted 6643 IVCM images from the three hospitals' IVCM database as the training set for the DCNN model and 1661 IVCM images from the other two hospitals' IVCM database as the test set to examine the performance of the model. Construction of the DCNN model was performed using DenseNet-169.
View Article and Find Full Text PDFClin Rheumatol
January 2025
Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 1 Shuaifuyuan, Beijing, 100730, China.
To synthesize available evidence on predictive factors associated with systemic lupus erythematosus (SLE) flares during pregnancy, we systematically searched MEDLINE, Embase, and the Cochrane Library through January 2024 for observational studies on risk and protective factors of SLE flares during pregnancy. Odds ratios (OR) and mean differences (MD), as well as their 95% confidence intervals (CI) were used to quantify effect sizes. We employed fixed-effect or random-effect models based on heterogeneity assessments (I statistics).
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