A nucleic acid detection assay combining reverse transcription recombinase-aided amplification with a lateral flow dipstick for the rapid visual detection of porcine deltacoronavirus.

Porcine deltacoronavirus (PDCoV) is an emerging enteropathogen causing severe diarrhoea, dehydration, and death in nursing piglets and enormous economic losses for the global swine industry. Furthermore, it can infect multiple animal species including humans. Therefore, a rapid, definitive diagnostic assay is required for the effective control of this zoonotic pathogen. To identify PDCoV, we developed a nucleic acid detection assay combining reverse transcription recombinase-aided amplification (RT-RAA) with a lateral flow dipstick (LFD) targeting the highly conserved genomic region in the ORF1b gene. The RT-RAA-LFD assay exhibited good PDCoV detection reproducibility and repeatability and could be completed within 11 min. Ten minutes at 40 °C was required for nucleic acid amplification and 1 min at room temperature was needed for the visual LFD readout. The assay specifically detected PDCoV and did not cross-react with any other major swine pathogens. The 95% limit of detection (LOD) was 3.97 median tissue culture infectious dose PDCoV RNA per reaction. This performance was comparable to that of a reference TaqMan-based real-time RT-PCR (trRT-PCR) assay for PDCoV. Of 149 swine small intestine, rectal swab, and serum samples, 71 and 75 tested positive for PDCoV according to RT-RAA-LFD and trRT-PCR, respectively. The diagnostic coincidence rate for both assays was 97.32% (145/149) and the kappa value was 0.946 (p < 0.001). Overall, the RT-RAA-LFD assay is a user-friendly diagnostic tool that can rapidly and visually detect PDCoV.

Severe COVID-19-associated sepsis is different from classical sepsis induced by pulmonary infection with carbapenem-resistant klebsiella pneumonia (CrKP).

PURPOSE: COVID-19 is also referred to as a typical viral septic pulmonary infection by 2019-nCoV. However, little is known regarding its characteristics in terms of systemic inflammation and organ injury, especially compared with classical bacterial sepsis. This article aims to investigate the clinical characteristics and prognosis between COVID-19-associated sepsis and classic bacterial-induced sepsis. METHODS: In this retrospective cohort study, septic patients with COVID-19 in the intensive care unit (ICU) of a government-designed therapy center in Shenzhen, China between January 14, 2020 and March 10, 2020, and septic patients induced by carbapenem-resistant klebsiella pneumonia (CrKP) admitted to the ICU of the Second People's Hospital of Shenzhen, China between January 1, 2014 and October 30, 2019 were enrolled. Demographic and clinical parameters including comorbidities, critical illness scores, treatment, and laboratory data, as well as prognosis were compared between the two groups. Risk factors for mortality and survival rate were analyzed using multivariable logistic regression and survival curve, respectively. RESULTS: A total of 107 patients with COVID-19 and 63 patients with CrKP were enrolled. A direct comparison between the two groups demonstrated more serious degrees of primary lung injury following 2019-nCoV infection (indicated by lower PaO2/FiO2), but milder systemic inflammatory response, lower sequential organ failure assessment score and better functions of the organs like heart, liver, kidney, coagulation, and circulation. However, the acquired immunosuppression presented in COVID-19 patients was more severe, which presented as lower lymphocyte counts (0.8×109/L vs. 0.9×109/L). Moreover, the proportion of COVID-19 patients treated with corticosteroid therapy and extracorporeal membrane oxygenation was larger compared with CrKP patients (78.5% vs. 38.1% and 6.5% vs. 0, respectively) who required less invasive mechanical ventilation (31.6% vs. 54.0%). The incidence of hospitalized mortality and length of ICU stay and total hospital stay were also lower or shorter in viral sepsis (12.1% vs. 39.7%, 6.5 days vs. 23.0 days and 21.0 days vs. 33.0 days, respectively) (all p < 0.001). Similar results were obtained after being adjusted by age, gender, comorbidity and PaO2/FiO2. Lymphocytopenia and high acute physiology and chronic health evaluation II scores were common risk factors for in-hospital death. While the death cases of COVID-19 sepsis mostly occurred at the later stages of patients' hospital stay. CONCLUSION: Critical COVID-19 shares clinical characteristics with classical bacterial sepsis, but the degree of systemic inflammatory response, secondary organ damage and mortality rate are less severe. However, following 2019-nCoV infection, the level of immunosuppression may be increased and thus induce in more death at the later stage of patients' hospitalstay.

Severe COVID-19-associated sepsis is different from classical sepsis induced by pulmonary infection with carbapenem-resistant klebsiella pneumonia (CrKP)

Purpose COVID-19 is also referred to as a typical viral septic pulmonary infection by 2019-nCoV. However, little is known regarding its characteristics in terms of systemic inflammation and organ injury, especially compared with classical bacterial sepsis. This article aims to learn the clinical characteristics and prognosis between COVID-19-associated sepsis and classic bacterial-induced sepsis. Methods In this retrospective cohort study, septic patients with COVID-19 in the intensive care unit (ICU) of a government-designed therapy center in Shenzhen, China between Jan 14, 2020 and Mar 10, 2020, and septic patients induced by carbapenem-resistant klebsiella pneumonia (CrKP) admitted at the ICU of the Second People’s Hospital of Shenzhen, China between Jan 1, 2014 and Oct 30, 2019, were enrolled. Demographic & clinical parameters including comorbidities, critical illness scores, treatment, and laboratory data, as well as prognosis were compared between the two groups. Risk factors for mortality and survival rate were analyzed using multivariable logistic regression and survival curve. Results A total of 107 patients with COVID-19 and 63 patients with CrKP were enrolled. A direct comparison between the two groups demonstrated more serious degrees of primary lung injury following 2019-nCoV infection (indicated by lower PaO2/FiO2) but milder systemic inflammatory response, lower sequential organ failure assessment (SOFA) score and better functions of the organs like heart, liver, kidney, coagulation, and circulation. However, the acquired immunosuppression presented in COVID-19 patients was more severe, which presented as lower lymphocyte counts. Moreover, the proportion of COVID-19 patients treated with corticosteroid therapy and extracorporeal membrane oxygenation was larger compared with CrKP patients who required less invasive mechanical ventilation. The incidence of hospitalized mortality and length of ICU stay and total hospital stay were also lower or shorter in viral sepsis. Similar results were obtained after being adjusted by age, gender, comorbidity and PaO2/FiO2. Lymphocytopenia and high acute physiology and chronic health evaluation II (APACH II) scores were common risk factors for in-hospital death. While the death cases of COVID-19 sepsis mostly occurred at the later stages of patients’ hospital stay. Conclusion Critical COVID-19 shares clinical characteristics with classical bacterial sepsis, but the degree of systemic inflammatory response, secondary organ damage and mortality rate are less severe. However, following 2019-nCoV infection, the level of immunosuppression may be increased and thus induce in more death at the later stage of patients’ hospital stay.

CT radiomics facilitates more accurate diagnosis of COVID-19 pneumonia: compared with CO-RADS.

BACKGROUND: Limited data was available for rapid and accurate detection of COVID-19 using CT-based machine learning model. This study aimed to investigate the value of chest CT radiomics for diagnosing COVID-19 pneumonia compared with clinical model and COVID-19 reporting and data system (CO-RADS), and develop an open-source diagnostic tool with the constructed radiomics model. METHODS: This study enrolled 115 laboratory-confirmed COVID-19 and 435 non-COVID-19 pneumonia patients (training dataset, n = 379; validation dataset, n = 131; testing dataset, n = 40). Key radiomics features extracted from chest CT images were selected to build a radiomics signature using least absolute shrinkage and selection operator (LASSO) regression. Clinical and clinico-radiomics combined models were constructed. The combined model was further validated in the viral pneumonia cohort, and compared with performance of two radiologists using CO-RADS. The diagnostic performance was assessed by receiver operating characteristics curve (ROC) analysis, calibration curve, and decision curve analysis (DCA). RESULTS: Eight radiomics features and 5 clinical variables were selected to construct the combined radiomics model, which outperformed the clinical model in diagnosing COVID-19 pneumonia with an area under the ROC (AUC) of 0.98 and good calibration in the validation cohort. The combined model also performed better in distinguishing COVID-19 from other viral pneumonia with an AUC of 0.93 compared with 0.75 (P = 0.03) for clinical model, and 0.69 (P = 0.008) or 0.82 (P = 0.15) for two trained radiologists using CO-RADS. The sensitivity and specificity of the combined model can be achieved to 0.85 and 0.90. The DCA confirmed the clinical utility of the combined model. An easy-to-use open-source diagnostic tool was developed using the combined model. CONCLUSIONS: The combined radiomics model outperformed clinical model and CO-RADS for diagnosing COVID-19 pneumonia, which can facilitate more rapid and accurate detection.