Systemic Anticoagulation is Associated With Decreased Mortality in COVID-19 Patients: A Propensity Score-Matched Cohort Study (preprint)

Background: Accumulating evidence has revealed that coagulopathy and widespread thrombosis in the lung are common in patients with Coronavirus Disease 2019 (COVID-19). This raises questions about the efficacy and safety of systemic anticoagulation (AC) in COVID-19 patients. Method: This single-center, retrospective, cohort study unselectively reviewed 2272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. Propensity score-matching between patients adjusted for potential covariates was carried out with the patients divided into two groups depending on whether or not they had received AC treatment (AC group, ³7 days of treatment; non-AC group, no treatment). This yielded 164 patients in each group. Result: In-hospital mortality of the AC group was significantly lower than that of the non-AC group (14.0% vs. 28.7%, P =0.001). Treatment with AC was associated with a significantly lower probability of in-hospital death (adjusted HR=0.273, 95% CI, 0.154 to 0.484, P<0.001). The incidence of major bleeding and thrombocytopenia in the two groups was not significantly different. Subgroup analysis showed the following factors were associated with a significantly lower in-hospital mortality in patients who had received AC treatment; severe cases (13.2% vs. 24.6%, P=0.018), critical cases (20.0% vs 82.4%, P=0.003), patients with a D-dimer level ≥0.5 μg/mL (14.8% vs. 33.8, P<0.001), and moderate (16.7% vs. 60.0%, P=0.003) or severe acute respiratory distress syndrome (ARDS) cases at admission (33.3% vs. 86.7%, P=0.004). During the hospital stay, critical cases (38.3% vs. 76.7%, P<0.001) and severe ARDS cases (36.5% vs. 76.3%, P<0.001) who received AC treatment had significantly lower in-hospital mortality. Conclusions: AC treatment decreases the risk of in-hospital mortality, especially in critically ill patients, with no additional significant, major bleeding events or thrombocytopenia being observed.Trials registration - ChiCTR2000039855

A Simple Nomogram for Predicting Failure of Non-Invasive Respiratory Therapies in Adults with COVID-19: A Retrospective Multicenter Study (preprint)

Background: Non-invasive respiratory therapies (NIRTs) (high flow nasal cannula and non-invasive ventilation) are widely used in COVID-19 patients who developed acute respiratory failure. However, use of these therapies may delay initiation of invasive mechanical ventilation in some patients and hence worsen their outcome. This study set out to identify early predictors of NIRT failure and to develop a simple-to-use nomogram and an online calculator identifying patients at high risk of NIRT failure. Methods: A retrospective cohort of 652 COVID-19 patients with ARF who received NIRTs, was used to develop early predictors of NIRT failure, defined as subsequent need for invasive mechanical ventilation or death within 28 days after ICU admission. Multivariate logistic analysis was used to develop the nomogram and ten-fold cross-validation was applied to internally validate the stability of the model. Findings: The failure rate of NITRs was 63% (415/652). The ROX index (ratio of pulse oximetry oxygen saturation/fraction of inspired oxygen to respiratory rate), age, GCS score, and use of vasoprEssors on the first day of NIRTs were independent risk factors for NIRT failure (RAGE factors). Based on the multivariate analysis, the RAGE nomogram for NIRTs failure had a C-statistics of 0 . 83 (95% CI:0 . 80–0 . 87). An internal validation demonstrated that the mean C-statistic remained stable (C-statistics=0 . 84±0 . 03). Internal calibration was excellent (calibration slope=1). Interpretation: The nomogram and online calculator are relatively simple-to-use and able to predict the risk of NIRT failure in COVID-19 patients with acute respiratory failure. Funding Statement: This work was supported by Key Research and Development Plan of Jiangsu Province (BE2018743 and BE2019749) and Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (CIFMS) from Chinese Academy of Medical Sciences (2016-I2M-1-014).Declaration of Interests: All authors have completed the Unified Competing Interest form (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.Ethics Approval Statement: The study was approved by the ethics committee of Jin Yintan Hospital (KY-2020-10.02). Informed consent was waived due to the retrospective and observational nature of the study.

Development and external validation of a prognostic multivariable model on admission for hospitalized patients with COVID-19 (preprint)

Background: COVID-19 pandemic has developed rapidly and the ability to stratify the most vulnerable patients is vital. However, routinely used severity scoring systems are often low on diagnosis, even in non-survivors. Therefore, clinical prediction models for mortality are urgently required. Methods: We developed and internally validated a multivariable logistic regression model to predict inpatient mortality in COVID-19 positive patients using data collected retrospectively from Tongji Hospital, Wuhan (299 patients). External validation was conducted using a retrospective cohort from Jinyintan Hospital, Wuhan (145 patients). Nine variables commonly measured in these acute settings were considered for model development, including age, biomarkers and comorbidities. Backwards stepwise selection and bootstrap resampling were used for model development and internal validation. We assessed discrimination via the C statistic, and calibration using calibration-in-the-large, calibration slopes and plots. Findings: The final model included age, lymphocyte count, lactate dehydrogenase and SpO2 as independent predictors of mortality. Discrimination of the model was excellent in both internal (c=0.89) and external (c=0.98) validation. Internal calibration was excellent (calibration slope=1). External validation showed some over-prediction of risk in low-risk individuals and under-prediction of risk in high-risk individuals prior to recalibration. Recalibration of the intercept and slope led to excellent performance of the model in independent data. Interpretation: COVID-19 is a new disease and behaves differently from common critical illnesses. This study provides a new prediction model to identify patients with lethal COVID-19. Its practical reliance on commonly available parameters should improve usage of limited healthcare resources and patient survival rate.

Analysis and Prediction of False Negative Results for SARS-CoV-2 Detection with Pharyngeal Swab Specimen in COVID-19 Patients: A Retrospective Study (preprint)

Background: False negative results of SARS-CoV-2 nucleic acid detection pose threats to COVID-19 patients and medical workers alike. Objective: To develop multivariate models to determine clinical characteristics that contribute to false negative results of SARS-CoV-2 nucleic acid detection, and use them to predict false negative results as well as time windows for testing positive. Design: Retrospective Cohort Study (Ethics number of Tongji Hospital: No. IRBID: TJ-20200320) Setting: A database of outpatients in Tongji Hospital (University Hospital) from 15 January 2020 to 19 February 2020. Patients: 1,324 outpatients with COVID-19 Measurements: Clinical information on CT imaging reports, blood routine tests, and clinic symptoms were collected. A multivariate logistic regression was used to explain and predict false negative testing results of SARS-CoV-2 detection. A multivariate accelerated failure model was used to analyze and predict delayed time windows for testing positive. Results: Of the 1,324 outpatients who diagnosed of COVID-19, 633 patients tested positive in their first SARS-CoV-2 nucleic acid test (47.8%), with a mean age of 51 years (SD=14.9); the rest, which had a mean age of 47 years (SD=15.4), tested negative in the first test. Ground glass opacity in a CT imaging report was associated with a lower chance of false negatives (aOR, 0.56), and reduced the length of time window for testing positive by 26%. Consolidation was associated with a higher chance of false negatives (aOR, 1.57), and extended the length of time window for testing positive by 44%. In blood routine tests, basophils (aOR, 1.28) and eosinophils (aOR, 1.29) were associated with a higher chance of false negatives, and were found to extend the time window for testing positive by 23% and 41%, respectively. Age and gender also affected the significantly. Limitation: Data were generated in a large single-center study. Conclusion: Testing outcome and positive window of SARS-CoV-2 detection for COVID-19 patients were associated with CT imaging results, blood routine tests, and clinical symptoms. Taking into account relevant information in CT imaging reports, blood routine tests, and clinical symptoms helped reduce a false negative testing outcome. The predictive AFT model, what we believe to be one of the first statistical models for predicting time window of SARS-CoV-2 detection, could help clinicians improve the accuracy and efficiency of the diagnosis, and hence, optimizes the timing of nucleic acid detection and alleviates the shortage of nucleic acid detection kits around the world. Primary Funding Source: None.

Evaluation of the clinical characteristics of suspected or confirmed cases of COVID-19 during home care with isolation: A new retrospective analysis based on O2O (preprint)

Summary Background The recent outbreak of the novel coronavirus in December 2019 (COVID-19) has activated top-level response nationwide. We developed a new treatment model based on the online-to-offline (O2O) model for the home isolated patients, because in the early stages the medical staff were insufficient to cope with so many patients. Methods In this single-centered, retrospective study, we enrolled 48 confirmed/suspected COVID-19 patients who underwent home isolation in Wuhan between January 6 and January 31, 2020. By WeChat and online document editing all patients were treated with medical observation scale. The clinical indications such as Fever, Muscle soreness, Dyspnea and Lack of strength were collected with this system led by medical staff in management, medicine, nursing, rehabilitation and psychology. Findings The mean(SD) age of 48 patients was 39.08(13.88) years, 35(72.9%) were women. Compared with non-hospitalized patients, inpatients were older([≥]8805;70years, 2.4% vs 33.3%, P<0.04). All inpatients had fever, 50% inpatients had coughs and showed infiltration in both lungs at the time of diagnosis. 33.3% inpatients exhibited negative changes in their CT results at initial diagnosis. The body temperature of non-hospitalized patients with mild symptoms returned to normal by day 4-5. While dyspnea peaked on day 6 for non-hospitalized patients with mild symptoms, it persisted in hospitalized patients and exacerbated over time. The lack of strength and muscle soreness were both back to normal by day 4 for non-hospitalized patients. Interpretation Monitoring the trends of symptoms is more important for identifying severe cases. Excessive laboratory data and physical examination are not necessary for the evaluation of patients with mild symptoms. The system we developed is the first to convert the subjective symptoms of patients into objective scores. This type of O2O, subjective-to-objective strategy may be used in regions with similar highly infectious diseases to minimize the possibility of infection among medical staff.

Clinical and immunologic features in severe and moderate forms of Coronavirus Disease 2019 (preprint)

Background Since late December, 2019, an outbreak of pneumonia cases caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, and continued to spread throughout China and across the globe. To date, few data on immunologic features of Coronavirus Disease 2019 (COVID-19) have been reported. Methods In this single-centre retrospective study, a total of 21 patients with pneumonia who were laboratory-confirmed to be infected with SARS-CoV-2 in Wuhan Tongji hospital were included from Dec 19, 2019 to Jan 27, 2020. The immunologic characteristics as well as their clinical, laboratory, radiological features were compared between 11 severe cases and 10 moderate cases. Results Of the 21 patients with COVID-19, only 4 (19%) had a history of exposure to the Huanan seafood market. 7 (33.3%) patients had underlying conditions. The average age of severe and moderate cases was 63.9 and 51.4 years, 10 (90.9%) severe cases and 7 (70.0%) moderate cases were male. Common clinical manifestations including fever (100%, 100%), cough (70%, 90%), fatigue (100%, 70%) and myalgia (50%, 30%) in severe cases and moderate cases. PaO2/FiO2 ratio was significantly lower in severe cases (122.9) than moderate cases (366.2). Lymphocyte counts were significantly lower in severe cases (7000 million/L) than moderate cases (11000 million/L). Alanine aminotransferase, lactate dehydrogenase levels, high-sensitivity C-reactive protein and ferritin were significantly higher in severe cases (41.4 U/L, 567.2 U/L, 135.2 mg/L and 1734.4 ug/L) than moderate cases (17.6 U/L, 234.4 U/L, 51.4 mg/L and 880.2 ug /L). IL-2R, TNF- and IL-10 concentrations on admission were significantly higher in severe cases (1202.4 pg/mL, 10.9 pg/mL and 10.9 pg/mL) than moderate cases (441.7 pg/mL, 7.5 pg/mL and 6.6 pg/mL). Absolute number of total T lymphocytes, CD4+T cells and CD8+T cells decreased in nearly all the patients, and were significantly lower in severe cases (332.5, 185.6 and 124.3 million/L) than moderate cases (676.5, 359.2 and 272.0 million/L). The expressions of IFN-{gamma} by CD4+T cells tended to be lower in severe cases (14.6%) than moderate cases (23.6%). Conclusion The SARS-CoV-2 infection may affect primarily T lymphocytes, particularly CD4+T cells, resulting in significant decrease in number as well as IFN-{gamma} production, which may be associated with disease severity. Together with clinical characteristics, early immunologic indicators including diminished T lymphocytes and elevated cytokines may serve as potential markers for prognosis in COVID-19.