Background: Coronavirus disease 2019 (COVID-19) infection is considered a serious highly infectious disease caused by severe acute respiratory syndrome coronavirus 2, resulting in more than 6.27 million deaths worldwide.
Aim Of The Study: The study aimed to compare clinical characteristics and laboratory findings of COVID-19 patients with complications and without complications and discriminate the important risk factors for the complications and deaths.
Subjects And Methods: This cross-sectional study included 75 confirmed COVID-19 positive patients; out of which 49 were severely-ill cases. Analysis of all patients' clinical and laboratory information on admission including serum ferritin, thrombotic activity (d-dimer), lactate dehydrogenase (LDH), C-reactive protein (CRP), creatinine, aspartate aminotransferase, and alanine aminotransferase were done.
Results: Lymphopenia, tachycardia, tachypnea, elevated CRP, d-dimer, serum ferritin, LDH, and decreased SpO were significantly associated with complicated cases (p < .05 for all). By using multivariate logistic regression analysis models, elevated serum ferritin and tachycardia were significantly correlated with the increased odds of complicated COVID-19 cases (odds ratio [confidence interval 95%] = 10.42 [2.32-46.89] and 8.01 [1.17-55.99]; respectively) (p = .002 and .007, respectively).
Conclusion: Lymphocytopenia, d-dimer, LDH, and CRP levels, which were significantly linked to the severity of COVID-19, were the prognostic biomarkers to predict the disease severity.
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http://dx.doi.org/10.1002/iid3.671 | 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.
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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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