Study of Thoracic CT in COVID-19: The STOIC Project.

Background There are conflicting data regarding the diagnostic performance of chest CT for COVID-19 pneumonia. Disease extent at CT has been reported to influence prognosis. Purpose To create a large publicly available data set and assess the diagnostic and prognostic value of CT in COVID-19 pneumonia. Materials and Methods This multicenter, observational, retrospective cohort study involved 20 French university hospitals. Eligible patients presented at the emergency departments of the hospitals involved between March 1 and April 30th, 2020, and underwent both thoracic CT and reverse transcription-polymerase chain reaction (RT-PCR) testing for suspected COVID-19 pneumonia. CT images were read blinded to initial reports, RT-PCR, demographic characteristics, clinical symptoms, and outcome. Readers classified CT scans as either positive or negative for COVID-19 based on criteria published by the French Society of Radiology. Multivariable logistic regression was used to develop a model predicting severe outcome (intubation or death) at 1-month follow-up in patients positive for both RT-PCR and CT, using clinical and radiologic features. Results Among 10 930 patients screened for eligibility, 10 735 (median age, 65 years; interquartile range, 51-77 years; 6147 men) were included and 6448 (60%) had a positive RT-PCR result. With RT-PCR as reference, the sensitivity and specificity of CT were 80.2% (95% CI: 79.3, 81.2) and 79.7% (95% CI: 78.5, 80.9), respectively, with strong agreement between junior and senior radiologists (Gwet AC1 coefficient, 0.79). Of all the variables analyzed, the extent of pneumonia at CT (odds ratio, 3.25; 95% CI: 2.71, 3.89) was the best predictor of severe outcome at 1 month. A score based solely on clinical variables predicted a severe outcome with an area under the curve of 0.64 (95% CI: 0.62, 0.66), improving to 0.69 (95% CI: 0.6, 0.71) when it also included the extent of pneumonia and coronary calcium score at CT. Conclusion Using predefined criteria, CT reading is not influenced by reader's experience and helps predict the outcome at 1 month. ClinicalTrials.gov identifier: NCT04355507 Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Rubin in this issue.

Biofilms busters to improve the detection of Borrelia using PCR.

Lyme disease is an affection caused by a spirochete infection called Borrelia Burgdorferi which may harbor a varied and misleading clinical symptomatology. The serology tests commonly used for diagnosis show a wide sensitivity varying from 34% to 70,5%, leaving many infected patients with false negative tests. Alternative techniques such as polymerase chain reaction (PCR) could be helpful but not conclusive enough. Using biofilm busters, such as stevia and serratiopeptidase, could lead to bacterial blood release, thus increasing the spirochete load, making PCR test more sensitive, thus improving the patient's diagnosis and management.