Development of septic shock and prognostic assessment in critically ill patients with coronavirus disease outside Wuhan, China.

BACKGROUND: The study aims to illustrate the clinical characteristics and development of septic shock in intensive care unit (ICU) patients confirmed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and to perform a comprehensive analysis of the association between septic shock and clinical outcomes in critically ill patients with coronavirus disease (COVID-19). METHODS: Patients confirmed with SARS-CoV-2 infection, who were admitted to the ICU of the Third People's Hospital of Shenzhen from January 1 to February 7, 2020, were enrolled. Clinical characteristics and outcomes were compared between patients with and without septic shock. RESULTS: In this study, 35 critically ill patients with COVID-19 were included. Among them, the median age was 64 years (interquartile range [IQR] 59-67 years), and 10 (28.4%) patients were female. The median ICU length of stay was 16 days (IQR 8-23 days). Three (8.6%) patients died during hospitalization. Nine (25.7%) patients developed septic shock in the ICU, and these patients had a significantly higher incidence of organ dysfunction and a worse prognosis than patients without septic shock. CONCLUSIONS: Septic shock is associated with a poor outcome in critically ill COVID-19 patients and is one of the hallmarks of the severity of patients receiving ICU care. A dysregulated immune response, uncontrolled inflammation, and coagulation disorders are strongly associated with the development and progression of COVID-19-related septic shock.

Validated tool for early prediction of intensive care unit admission in COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic is a global threat caused by the severe acute respiratory syndrome coronavirus-2. AIM: To develop and validate a risk stratification tool for the early prediction of intensive care unit (ICU) admission among COVID-19 patients at hospital admission. METHODS: The training cohort included COVID-19 patients admitted to the Wuhan Third Hospital. We selected 13 of 65 baseline laboratory results to assess ICU admission risk, which were used to develop a risk prediction model with the random forest (RF) algorithm. A nomogram for the logistic regression model was built based on six selected variables. The predicted models were carefully calibrated, and the predictive performance was evaluated and compared with two previously published models. RESULTS: There were 681 and 296 patients in the training and validation cohorts, respectively. The patients in the training cohort were older than those in the validation cohort (median age: 63.0 vs 49.0 years, P < 0.001), and the percentages of male gender were similar (49.6% vs 49.3%, P = 0.958). The top predictors selected in the RF model were neutrophil-to-lymphocyte ratio, age, lactate dehydrogenase, C-reactive protein, creatinine, D-dimer, albumin, procalcitonin, glucose, platelet, total bilirubin, lactate and creatine kinase. The accuracy, sensitivity and specificity for the RF model were 91%, 88% and 93%, respectively, higher than those for the logistic regression model. The area under the receiver operating characteristic curve of our model was much better than those of two other published methods (0.90 vs 0.82 and 0.75). Model A underestimated risk of ICU admission in patients with a predicted risk less than 30%, whereas the RF risk score demonstrated excellent ability to categorize patients into different risk strata. Our predictive model provided a larger standardized net benefit across the major high-risk range compared with model A. CONCLUSION: Our model can identify ICU admission risk in COVID-19 patients at admission, who can then receive prompt care, thus improving medical resource allocation.

Clinical diagnosis of severe COVID-19: A derivation and validation of a prediction rule.

BACKGROUND: The widespread coronavirus disease 2019 (COVID-19) has led to high morbidity and mortality. Therefore, early risk identification of critically ill patients remains crucial. AIM: To develop predictive rules at the time of admission to identify COVID-19 patients who might require intensive care unit (ICU) care. METHODS: This retrospective study included a total of 361 patients with confirmed COVID-19 by reverse transcription-polymerase chain reaction between January 19, 2020, and March 14, 2020 in Shenzhen Third People's Hospital. Multivariate logistic regression was applied to develop the predictive model. The performance of the predictive model was externally validated and evaluated based on a dataset involving 126 patients from the Wuhan Asia General Hospital between December 2019 and March 2020, by area under the receiver operating curve (AUROC), goodness-of-fit and the performance matrix including the sensitivity, specificity, and precision. A nomogram was also used to visualize the model. RESULTS: Among the patients in the derivation and validation datasets, 38 and 9 participants (10.5% and 2.54%, respectively) developed severe COVID-19, respectively. In univariate analysis, 21 parameters such as age, sex (male), smoker, body mass index (BMI), time from onset to admission (> 5 d), asthenia, dry cough, expectoration, shortness of breath, asthenia, and Rox index < 18 (pulse oxygen saturation, SpO2)/(FiO2 × respiratory rate, RR) showed positive correlations with severe COVID-19. In multivariate logistic regression analysis, only six parameters including BMI [odds ratio (OR) 3.939; 95% confidence interval (CI): 1.409-11.015; P = 0.009], time from onset to admission (≥ 5 d) (OR 7.107; 95%CI: 1.449-34.849; P = 0.016), fever (OR 6.794; 95%CI: 1.401-32.951; P = 0.017), Charlson index (OR 2.917; 95%CI: 1.279-6.654; P = 0.011), PaO2/FiO2 ratio (OR 17.570; 95%CI: 1.117-276.383; P = 0.041), and neutrophil/lymphocyte ratio (OR 3.574; 95%CI: 1.048-12.191; P = 0.042) were found to be independent predictors of COVID-19. These factors were found to be significant risk factors for severe patients confirmed with COVID-19. The AUROC was 0.941 (95%CI: 0.901-0.981) and 0.936 (95%CI: 0.886-0.987) in both datasets. The calibration properties were good. CONCLUSION: The proposed predictive model had great potential in severity prediction of COVID-19 in the ICU. It assisted the ICU clinicians in making timely decisions for the target population.

Symptomatic and optimal supportive care of critical COVID-19: A case report and literature review.

BACKGROUND: Coronavirus disease 2019 (COVID-19) severity is classified as asymptomatic, mild, moderate, severe, and critical. Mild cases account for a large percentage of cases in the epidemic and typically exhibit a favorable prognosis. However, a 49%-67% mortality is noted in critical cases. No COVID-19-specific drug has been reported to date, and symptomatic and optimal supportive care, including oxygenation, anti-coinfection treatments, and ventilation, represent the mainstay of treatment for this disease, especially in critical patients. CASE SUMMARY: In the above-mentioned context, we share our experience with the treatment of one critical COVID-19 case and review the relevant literature. CONCLUSION: Timely tracheal intubation, reasonable mechanical ventilation support, appropriate anti-infection treatment, and early anticoagulation and immunity support are key factors in the successful treatment of this case.

The Clinical Features and Prognostic Assessment of SARS-CoV-2 Infection-Induced Sepsis Among COVID-19 Patients in Shenzhen, China.

Background: The outbreak of the novel coronavirus disease (COVID-19) that began in December 2019 has posed a great threat to human health and caused a significant loss of life. In Shenzhen, 465 patients were confirmed to have COVID-19 as of August 31, 2020. In the present study, we aimed to describe the clinical characteristics of COVID-19 patients in Shenzhen and identify risk factors for the development of viral sepsis. Methods: In this retrospective study, patients who were confirmed to have a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and were admitted to the Third People's Hospital of Shenzhen from January 11 to April 27, 2020 were included in the cohort. Clinical data were extracted and followed up to May 10, 2020, by using predesigned data collection forms. Results: A total of 422 hospitalized COVID-19 patients were enrolled in this study, including 97 (23%) patients with viral sepsis at hospital admission and 325 (77%) non-septic patients. Patients with sepsis were much older than those without sepsis (57 vs. 43 years, P < 0.001) and presented with more comorbidities. Septic patients showed multiple organ dysfunction and significant abnormalities in immune- and inflammation-related biomarkers, and had poorer outcomes when compared to those without sepsis. Increased levels of interleukin-6, blood urea nitrogen, and creatine kinase were associated with the development of SARS-CoV-2-induced sepsis, and an elevated production of interleukin-6 was found to be an independent risk factor for the progression to critical illness among septic COVID-19 patients. Conclusions: SARS-CoV-2 infection-induced sepsis is critically involved in the severity and prognosis of COVID-19 patients by characterizing both aberrant immune response and uncontrolled inflammation. The development of sepsis might contribute to multiple organ dysfunction and poor outcomes in COVID-19 patients during hospitalization.

Coronavirus disease 2019 (COVID-19) associated coagulopathy and its impact on outcomes in Shenzhen, China: A retrospective cohort study.

BACKGROUND: Early detection of suspected critical patients infected with coronavirus disease 2019 (COVID-19) is very important for the treatment of patients. This study aimed to investigate the role of COVID-19 associated coagulopathy (CAC) to preview and triage. METHODS AND RESULTS: A cohort study was designed from government designated COVID-19 treatment center. CAC was defined as International Society on Thrombosis and Haemostasis (ISTH) score ≥2. Data from 117 patients COVID-19 were reviewed on admission. The primary and secondary outcomes were admission to Intensive Care Unit (ICU), the use of mechanical ventilation, vital organ dysfunction, discharges of days 14, 21 and 28 from admission and hospital mortality. Among them, admission to ICU was increased progressively from 16.1% in patients with non-CAC to 42.6% in patients with CAC (P < 0.01). Likely, invasive ventilation and noninvasive ventilation were increased from 1.8%, 21.4% in patients with non-CAC to 21.3%, 52.5% in patients with CAC, respectively (P < 0.01). The incidences of acute hepatic injury and acute respiratory distress syndrome in non-CAC and CAC were 28.6% vs. 62.3%, 8.9% vs. 27.9%, respectively (P < 0.01). The discharges of days 14, 21 and 28 from admission were more in non-CAC than those of CAC (P < 0.05). Multiple logistic regression results showed that ISTH score ≥2 was obviously associated with the admission to ICU (OR 4.07, 95% CI 1.47-11.25 P = 0.007) and the use of mechanical ventilation (OR 5.54, 95% CI 2.01-15.28 P = 0.001) in patients with COVID-19. CONCLUSION: All results show ISTH score ≥2 is an important indicator to preview and triage for COVID-19 patients.

First case of COVID-19 complicated with fulminant myocarditis: a case report and insights.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been demonstrated to be the cause of pneumonia. Nevertheless, it has not been reported as the cause of acute myocarditis or fulminant myocarditis. CASE PRESENTATION: A 63-year-old male was admitted with pneumonia and cardiac symptoms. He was genetically confirmed as having COVID-19 according to sputum testing on the day of admission. He also had elevated troponin I (Trop I) level (up to 11.37 g/L) and diffuse myocardial dyskinesia along with a decreased left ventricular ejection fraction (LVEF) on echocardiography. The highest level of interleukin-6 was 272.40 pg/ml. Bedside chest radiographs showed typical ground-glass changes indicative of viral pneumonia. Laboratory test results for viruses that cause myocarditis were all negative. The patient conformed to the diagnostic criteria of the Chinese expert consensus statement for fulminant myocarditis. After receiving antiviral therapy and mechanical life support, Trop I was reduced to 0.10 g/L, and interleukin-6 was reduced to 7.63 pg/mL. Moreover, the LVEF of the patient gradually recovered to 68%. The patient died of aggravation of secondary infection on the 33rd day of hospitalization. CONCLUSION: COVID-19 patients may develop severe cardiac complications such as myocarditis and heart failure. This is the first report of COVID-19 complicated with fulminant myocarditis. The mechanism of cardiac pathology caused by COVID-19 needs further study.