Systematic Screening for Deep Vein Thrombosis in Critically Ill Inpatients With COVID-19: Impact on the Incidence of Venous Thromboembolism. | LitMetric
Several studies suggest an increased incidence of thrombosis in COVID-19 patients. However, evidence on how to prevent and even treat it is scarce. The aim of this study was to compare the cumulative incidence of venous thromboembolism (VTE) of two different methods for lower extremity deep vein thrombosis (LE-DVT) diagnosis: systematic vs. clinically guided complete compression venous ultrasonography (CCUS). We conducted a monocentric, prospective, open-label, non-randomized study. All consecutive patients admitted in three intensive care units (ICUs) of University Hospital of Toulouse for COVID-19 pneumonia were included: one performed systematic screening for LE-DVT, the others did not. The primary outcome was the 21-day cumulative incidence of VTE. The secondary end points were the 21-day cumulative incidences of major bleeding and death. Among the 78 patients included, 27 (34.6%) underwent systematic screening for DVT 7 ± 2 days after ICU admission. Thirty-two patients (41.0%) were diagnosed with VTE, with a 21-day cumulative incidence of 42.3% (95% CI, 31.4-55.2), without difference between screened and non-screened patients (hazard ratio 1.45, 95% CI, 0.72-2.93). In the screened group, the frequency of isolated DVT was higher (25.9 vs. 5.9%, -value = 0.027), but the frequency of pulmonary embolism was not reduced (25.9 vs. 29.4%, -value = 0.745). The 21-day cumulative incidences of major bleeding and death were 9.6% (95% CI, 4.7-19.2) and 10.3% (95% CI, 5.0-20.8), respectively, without difference between the two groups. A systematic screening for DVT in patients hospitalized in ICU was not associated with a higher diagnosis of VTE or a reduced diagnosis of PE.
Visual analysis of peripheral blood smear slides using medical image analysis is required to diagnose red blood cell (RBC) morphological deformities caused by anemia. The absence of a complete anaemic RBC dataset has hindered the training and testing of deep convolutional neural networks (CNNs) for computer-aided analysis of RBC morphology. We introduce a benchmark RBC image dataset named Anemic RBC (AneRBC) to overcome this problem.
Background: Laparoscopic sleeve gastrectomy (LSG) specimens are histologically analyzed to identify incidental pathologies. However, no guidelines recommend routine histology. This study evaluates the clinical utility of LSG sample analysis and if incidental diagnoses have a significant clinical impact.
Purpose: To evaluate the diagnostic ability and methodological quality of ML models in detecting Pancreatic Ductal Adenocarcinoma (PDAC) in Contrast CT images.
Method: Included studies assessed adults diagnosed with PDAC, confirmed by histopathology. Metrics of tests were interpreted by ML algorithms.
School of Public Health, the key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China.
With the global prevalence of the hand-foot-and-mouth disease (HFMD) epidemic, the development of reliable point-of-care testing (POCT) is crucial for the timely identification and prevention of outbreaks. Isothermal nucleic acid amplification techniques (INAATs) have attracted much attention because of their high efficiency for rapid diagnosis. In this work, we systematically summarize the current status of INAATs for HFMD and discuss advantages and drawbacks of various INAATs for HFMD.
Background/aims: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely affects cognitive functions and memory. Early detection is crucial for timely intervention and improved patient outcomes. However, traditional diagnostic tools, such as MRI and PET scans, are costly and less accessible.
