Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard of outpatient and inpatient detection of Covid-19. RT-PCR is a rapid method; however, its accuracy in detection is only ~70–75%. Another approved strategy is computed tomography (CT) imaging. CT imaging has a much higher sensitivity of ~80–98%, but similar accuracy of 70%. To enhance the accuracy of CT imaging detection, we developed an open-source framework, CovidCTNet, composed of a set of deep learning algorithms that accurately differentiates Covid-19 from community-acquired pneumonia (CAP) and other lung diseases. CovidCTNet increases the accuracy of CT imaging detection to 95% compared to radiologists (70%). CovidCTNet is designed to work with heterogeneous and small sample sizes independent of the CT imaging hardware. To facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and model parameter details as open-source. Open-source sharing of CovidCTNet enables developers to rapidly improve and optimize services while preserving user privacy and data ownership.
Background: Appropriate and accurate easy access tools are necessary to overcome complications from malpositioned line tips of peripherally inserted central catheters (PICCs) in critically ill neonates. Ultrasound is a radiationless, cost-beneficial, and time-saving method that allows medical personnel to manipulate the line and correct possible malposition of this tip. In addition, it reduces the need for a second radiography. Objectives: We compared the effectiveness of sonography with radiography for confirmation of the line tip placement. Methods: This prospective descriptive-analytical study was conducted in the Neonatal Intensive Care Unit (NICU) in Tehran Children’s Medical Center (tertiary level), Tehran, Iran. Neonates who were candidates for PICC implantation according to the ward’s protocol were enrolled in the study. Radiography and sonography were performed after catheter insertion by a radiologist blinded to the preliminary radiographic reports. The results of both methods were compared and interpreted by statistical analysis using the chi-square and Pearson correlation tests. Results: A total of 90 infants, 45 (50%) males and 45 (50%) females, were assessed. We noted that 17 (18.8%) cases had malpositioned tips according to the radiographs. Malpositioning of the line tips were identified in 21.1% of cases by sonography (P ≤ 0.05), which indicated a higher accuracy for sonography compared to radiography. Both methods were appropriately correlated regardless of the underlying variables. Sonography had a sensitivity of 100% and specificity of 89.5%, a positive predictive value (PPV) of 97.3%, and a negative predictive value (NPV) of 100%. Conclusions: Our findings show that sonography can be a more accurate, safer bedside tool, with fewer complications compared to radiography in PICC tip placement determination in neonates. Multi-center studies with increased sample sizes should be performed to confirm replacement of radiography by sonography as the gold standard test for confirmation of PICC tip positioning.
Background This study assessed the safety and efficacy of intrathecal injection of umbilical cord tissue mesenchymal stem cells (UCT-MSC) in individuals with cerebral palsy (CP). The diffusion tensor imaging (DTI) was performed to evaluate the alterations in white-matter integrity. Methods Participants (4–14 years old) with spastic CP were assigned in 1:1 ratio to receive either UCT-MSC or sham procedure. Single-dose (2 × 107) cells were administered in the experimental group. Small needle pricks to the lower back were performed in the sham-control arm. All individuals were sedated to prevent awareness. The primary endpoints were the mean changes in gross motor function measure (GMFM)-66 from baseline to 12 months after procedures. The mean changes in the modified Ashworth scale (MAS), pediatric evaluation of disability inventory (PEDI), and CP quality of life (CP-QoL) were also assessed. Secondary endpoints were the mean changes in fractional anisotropy (FA) and mean diffusivity (MD) of corticospinal tract (CST) and posterior thalamic radiation (PTR). Results There were 36 participants in each group. The mean GMFM-66 scores after 12 months of intervention were significantly higher in the UCT-MSC group compared to baseline (10.65; 95%CI 5.39, 15.91) and control (β 8.07; 95%CI 1.62, 14.52; Cohen’s d 0.92). The increase was also seen in total PEDI scores (vs baseline 8.53; 95%CI 4.98, 12.08; vs control: β 6.87; 95%CI 1.52, 12.21; Cohen’s d 0.70). The mean change in MAS scores after 12 months of cell injection reduced compared to baseline (−1.0; 95%CI −1.31, −0.69) and control (β −0.72; 95%CI −1.18, −0.26; Cohen’s d 0.76). Regarding CP-QoL, mean changes in domains including friends and family, participation in activities, and communication were higher than the control group with a large effect size. The DTI analysis in the experimental group showed that mean FA increased (CST 0.032; 95%CI 0.02, 0.03. PTR 0.024; 95%CI 0.020, 0.028) and MD decreased (CST −0.035 × 10-3; 95%CI −0.04 × 10-3, −0.02 × 10-3. PTR −0.045 × 10-3; 95%CI −0.05 × 10-3, −0.03 × 10-3); compared to baseline. The mean changes were significantly higher than the control group. Conclusions The UCT-MSC transplantation was safe and may improve the clinical and imaging outcomes. Trial registration The study was registered with ClinicalTrials.gov (NCT03795974).
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