A model to predict the risk of mortality in severely ill COVID-19 patients.

BACKGROUND: To investigate and select the useful prognostic parameters to develop and validate a model to predict the mortality risk for severely and critically ill patients with the coronavirus disease 2019 (COVID-19). METHODS: We established a retrospective cohort of patients with laboratory-confirmed COVID-19 (≥18 years old) from two tertiary hospitals: the People's Hospital of Wuhan University and Leishenshan Hospital between February 16, 2020, and April 14, 2020. The diagnosis of the cases was confirmed according to the WHO interim guidance. The data of consecutive severely and critically ill patients with COVID-19 admitted to these hospitals were analyzed. A total of 566 patients from the People's Hospital of Wuhan University were included in the training cohort and 436 patients from Leishenshan Hospital were included in the validation cohort. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the variables and build the mortality risk prediction model. RESULTS: The prediction model was presented as a nomograph and developed based on identified predictors, including age, chronic lung disease, C-reactive protein (CRP), D-dimer levels, neutrophil-to-lymphocyte ratio (NLR), creatinine, and total bilirubin. In the training cohort, the model displayed good discrimination with an AUC of 0.912 [95% confidence interval (CI): 0.884-0.940] and good calibration (intercept = 0; slope = 1). In the validation cohort, the model had an AUC of 0.922 [95% confidence interval (CI): 0.891-0.953] and a good calibration (intercept = 0.056; slope = 1.161). The decision curve analysis (DCA) demonstrated that the nomogram was clinically useful. CONCLUSION: A risk score for severely and critically ill COVID-19 patients' mortality was developed and externally validated. This model can help clinicians to identify individual patients at a high mortality risk.

Development and implementation of the National Heart, Lung, and Blood Institute COVID-19 common data elements.

Background: Coronavirus Disease 2019 (COVID-19) instigated a flurry of clinical research activity. The unprecedented pace with which trials were launched left an early void in data standardization, limiting the potential for subsequent data pooling. To facilitate data standardization across emerging studies, the National Heart, Lung, and Blood Institute (NHLBI) charged two groups with harmonizing data collection, and these groups collaborated to create a concise set of COVID-19 Common Data Elements (CDEs) for clinical research. Methods: Our iterative approach followed three guiding principles: 1) draw from existing multi-center COVID-19 clinical trials as precedents, 2) incorporate existing data elements and data standards whenever possible, and 3) alignment to data standards that facilitate data sharing and regulatory submission. We also supported rapid implementation of the CDEs in NHLBI-funded studies and iteratively refined the CDEs based on feedback from those study teams. Results: The NHLBI COVID-19 CDEs are publicly available and being used for current COVID-19 clinical trials. CDEs are organized into domains, and each data element is classified within a three-tiered prioritization system. The CDE manual is hosted publicly at https://nhlbi-connects.org/common_data_elements with an accompanying data dictionary and implementation guidance. Conclusions: The NHLBI COVID-19 CDEs are designed to aid data harmonization across studies to achieve the benefits of pooled analyses. We found that organizing CDE development around our three guiding principles focused our efforts and allowed us to adapt as COVID-19 knowledge advanced. As these CDEs continue to evolve, they could be generalized for use in other acute respiratory illnesses.

Management of dermatomyositis patients amidst the COVID-19 pandemic: Two case reports.

RATIONALE: In December 2019, a new epidemic of coronavirus disease 2019 (COVID-19) appeared in Wuhan, Hubei Province, and spread rapidly to other parts of China and worldwide. Although established methods exist for the diagnosis and treatment of COVID-19 infection, the management of dermatomyositis (DM) patients with COVID-19 is unknown. PATIENT CONCERNS: In this article, we describe case reports of 2 patients with DM. The first case was a 67-year-old patient with DM and infected with COVID-19 who was admitted to Leishenshan Hospital for a 1-month history of fever, cough, and expectoration. The second case was a 51-year-old male patient who was admitted to Leishenshan Hospital due to fever with cough, expectoration and shortness of breath for 1 month. DIAGNOSES: The first patient was diagnosed with COVID-19 secondary to DM based on repeated SARS-CoV-2 real-time reverse-transcriptase polymerase-chain-reaction (RT-PCR) test, detailed medical history and chest computed tomography; The second patient was diagnosed with interstitial lung disease associated with anti-MDA5 DM based on the results of antirheumatic and anti-inflammatory therapy and the above 3 methods. INTERVENTIONS AND OUTCOMES: The first patient received supportive and empirical treatment, including antiviral treatment, anti-inflammatory treatment, oxygen therapy and prophylactic anticoagulation therapy. The symptoms and laboratory results got improved after the treatments. He was discharged with thrice negative PCR tests for the SARS-CoV-2 virus. The second patient received a comprehensive treatment, including glucocorticoid and plasma exchange; his symptoms were relieved and improved. LESSONS: These cases suggest that repeated new pathogenic test results for the coronavirus and a detailed diagnosis of the medical history are important means to distinguish these diseases. Increased attention to the individual characteristics of different cases may allow for more effective diagnosis and treatment.

Effect of therapeutic versus prophylactic anticoagulation therapy on clinical outcomes in COVID-19 patients: a systematic review with an updated meta-analysis.

BACKGROUND: Previous studies demonstrate a reduced risk of thrombosis and mortality with anticoagulant treatment in patients with COVID-19 than in those without anticoagulation treatment. However, an open question regarding the efficacy and safety of therapeutic anticoagulation (T-AC) versus a lower dose, prophylaxis anticoagulation (P-AC) in COVID-19 patients is still controversial. METHODS: We systematically reviewed currently available randomized clinical trials (RCTs) and observational studies (OBs) from January 8, 2019, to January 8, 2022, and compared prophylactic and therapeutic anticoagulant treatment in COVID-19 patients. The primary outcomes were risk of mortality, major bleeding, and the secondary outcomes included venous and arterial thromboembolism. Subgroup analysis was also performed between critically ill and non-critically ill patients with COVID-19 and between patients with higher and lower levels of D-dimer. Sensitivity analysis was performed to decrease the bias and the impact of population heterogeneity. RESULTS: We identified 11 RCTs and 17 OBs fulfilling our inclusion criteria. In the RCTs analyses, there was no statistically significant difference in the relative risk of mortality between COVID-19 patients with T-AC treatment and those treated with P-AC (RR 0.95, 95% CI, 0.78-1.15, P = 0.60). Similar results were also found in the OBs analyses (RR 1.21, 95% CI, 0.98-1.49, P = 0.08). The pooling meta-analysis using a random-effects model combined with effect sizes showed that in the RCTs and OBs analyses, patients with COVID-19 who received T-AC treatment had a significantly higher relative risk of the major bleeding event than those with P-AC treatment in COVID-19 patients (RCTs: RR 1.76, 95% CI, 1.19-2.62, P = 0.005; OBs: RR 2.39, 95% CI, 1.56-3.68, P < 0.0001). Compared with P-AC treatment in COVID-19 patients, patients with T-AC treatment significantly reduced the incidence of venous thromboembolism (RR 0.51, 95% CI, 0.39-0.67, P<0.00001), but it is not associated with arterial thrombosis events (RR 0.97, 95% CI, 0.66-1.42, P = 0.87). The subgroup analysis of OBs shows that the mortality risk significantly reduces in critically ill COVID-19 patients treated with T-AC compared with those with P-AC treatment (RR 0.58, 95% CI, 0.39-0.86, P = 0.007), while the mortality risk significantly increases in non-critically ill COVID-19 patients treated with T-AC (RR 1.56, 95% CI, 1.34-1.80, P < 0.00001). In addition, T-AC treatment does not reduce the risk of mortality in COVID-19 patients with high d-dimer levels in RCTs. Finally, the overall sensitivity analysis after excluding two RCTs studies remains consistent with the previous results. CONCLUSIONS: In our integrated analysis of included RCTs and OBs, there is no significant difference between the mortality of T-AC and P-AC treatment in unselected patients with COVID-19. T-AC treatment in COVID-19 patients significantly reduced the incidence of venous thromboembolism but showed a higher risk of bleeding than those with P-AC treatment. In addition, P-AC treatment was superior to T-AC treatment in non-critically ill COVID-19 patients, the evidence supporting the necessity for T-AC treatment in critically ill COVID-19 patients came only from OBs. TRIAL REGISTRATION: Protocol registration: The protocol was registered at PROSPERO (CRD42021293294).

Sera Metabolomics Characterization of Patients at Different Stages in Wuhan Identifies Critical Biomarkers of COVID-19.

We have witnessed the 2-year-long global rampage of COVID-19 caused by the wide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, knowledge about biomarkers of the entire COVID-19 process is limited. Identification of the systemic features of COVID-19 will lead to critical biomarkers and therapeutic targets for early intervention and clinical disease course prediction. Here, we performed a comprehensive analysis of clinical measurements and serum metabolomics in 199 patients with different stages of COVID-19. In particular, our study is the first serum metabolomic analysis of critical rehabilitation patients and critical death patients. We found many differential metabolites in the comparison of metabolomic results between ordinary, severe, and critical patients and uninfected patients. Through the metabolomic results of COVID-19 patients in various stages, and critical rehabilitation patients and critical death patients, we identified a series of differential metabolites as biomarkers, a separate queue and precise distinction, and predicted COVID-19 verification. These differentially expressed metabolites, included 1,2-di-(9Z,12Z-octadecadienoyl)-sn-glycero-3-phosphate, propylparaben, 20-hydroxyeicosatetraenoic acid, triethanolamine, chavicol, disialosyl galactosyl globoside, 1-arachidonoylglycerophosphoinositol, and alpha-methylstyrene, all of which have been identified for the first time as biomarkers in COVID-19 progression. These biomarkers are involved in many pathological and physiological pathways of COVID-19, for example, immune responses, platelet degranulation, and metabolism which might result in pathogenesis. Our results showed valuable information about metabolites obviously altered in COVID-19 patients with different stages, which could shed light on the pathogenesis as well as serve as potential therapeutic agents of COVID-19.

COVID-19 and its effects on the digestive system.

Coronavirus disease 2019 (COVID-19) is caused by infection of the coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with typical respiratory symptoms. SARS-CoV-2 invades not only the respiratory system, but also other organs expressing the cell surface receptor angiotensin converting enzyme 2. In particular, the digestive system is a susceptible target of SARS-CoV-2. Gastrointestinal symptoms of COVID-19 include anorexia, nausea, vomiting, diarrhea, abdominal pain, and liver damage. Patients with digestive damage have a greater chance of progressing to severe or critical illness, a poorer prognosis, and a higher risk of death. This paper aims to summarize the digestive system symptoms of COVID-19 and discuss fecal-oral contagion of SARS-CoV-2. It also describes the characteristics of inflammatory bowel disease patients with SARS-CoV-2 infection and discusses precautions for preventing SARS-CoV-2 infection during gastrointestinal endoscopy procedures. Improved attention to digestive system abnormalities and gastrointestinal symptoms of COVID-19 patients may aid health care providers in the process of clinical diagnosis, treatment, and epidemic prevention and control.

Using the PhenX Toolkit to Select Standard Measurement Protocols for Your Research Study.

The goals of PhenX (consensus measures for Phenotypes and eXposures) are to promote the use of standard measurement protocols and to help investigators identify opportunities for collaborative research and cross-study analysis, thus increasing the impact of individual studies. The PhenX Toolkit (https://www.phenxtoolkit.org/) offers high-quality, well-established measurement protocols to assess phenotypes and exposures in studies with human participants. The Toolkit contains protocols representing 29 research domains and 6 specialty collections of protocols that add depth to the Toolkit in specific research areas (e.g., COVID-19, Social Determinants of Health [SDoH], Blood Sciences Research [BSR], Mental Health Research [MHR], Tobacco Regulatory Research [TRR], and Substance Abuse and Addiction [SAA]). Protocols are recommended for inclusion in the PhenX Toolkit by Working Groups of domain experts using a consensus process that includes input from the scientific community. For each PhenX protocol, the Toolkit provides a detailed description, the rationale for inclusion, and supporting documentation. Users can browse protocols in the Toolkit, search the Toolkit using keywords, or use Browse Protocols Tree to identify protocols of interest. The PhenX Toolkit provides data dictionaries compatible with the database of Genotypes and Phenotypes (dbGaP), Research Electronic Data Capture (REDCap) data submission compatibility, and data collection worksheets to help investigators incorporate PhenX protocols into their study design. The PhenX Toolkit provides resources to help users identify published studies that used PhenX protocols. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Using the PhenX Toolkit to support or extend study design.

Serum Uric Acid Concentrations and Risk of Adverse Outcomes in Patients With COVID-19.

Background: Although hyperuricemia frequently associates with respiratory diseases, patients with severe coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS) can show marked hypouricemia. Previous studies on the association of serum uric acid with risk of adverse outcomes related to COVID-19 have produced contradictory results. The precise relationship between admission serum uric acid and adverse outcomes in hospitalized patients is unknown. Methods: Data of patients affected by laboratory-confirmed COVID-19 and admitted to Leishenshan Hospital were retrospectively analyzed. The primary outcome was composite and comprised events, such as intensive care unit (ICU) admission, mechanical ventilation, or mortality. Logistic regression analysis was performed to explore the association between serum concentrations of uric acid and the composite outcome, as well as each of its components. To determine the association between serum uric acid and in-hospital adverse outcomes, serum uric acid was also categorized by restricted cubic spline, and the 95% confidence interval (CI) was used to estimate odds ratios (OR). Results: The study cohort included 1854 patients (mean age, 58 years; 52% women). The overall mean ± SD of serum levels of uric acid was 308 ± 96 µmol/L. Among them, 95 patients were admitted to ICU, 75 patients received mechanical ventilation, and 38 died. In total, 114 patients reached composite end-points (have either ICU admission, mechanical ventilation or death) during hospitalization. Compared with a reference group with estimated baseline serum uric acid of 279-422 µmol/L, serum uric acid values ≥ 423 µmol/L were associated with an increased risk of composite outcome (OR, 2.60; 95% CI, 1.07- 6.29) and mechanical ventilation (OR, 3.01; 95% CI, 1.06- 8.51). Serum uric acid ≤ 278 µmol/L was associated with an increased risk of the composite outcome (OR, 2.07; 95% CI, 1.18- 3.65), ICU admission (OR, 2.18; 95% CI, 1.17- 4.05]), and mechanical ventilation (OR, 2.13; 95% CI, 1.06- 4.28), as assessed by multivariate analysis. Conclusions: This study shows that the association between admission serum uric acid and composite outcome of COVID-19 patients was U-shaped. In particular, we found that compared with baseline serum uric acid levels of 279-422 µmol/L, values ≥ 423 µmol/L were associated with an increased risk of composite outcome and mechanical ventilation, whereas levels ≤ 278 µmol/L associated with increased risk of composite outcome, ICU admission and mechanical ventilation.

Aberrant cytokine expression in COVID-19 patients: Associations between cytokines and disease severity.

Cytokines play pleiotropic, antagonistic, and collaborative in viral disease. The high morbidity and mortality of coronavirus disease 2019 (COVID-19) make it a significant threat to global public health. Elucidating its pathogenesis is essential to finding effective therapy. A retrospective study was conducted on 71 patients hospitalized with COVID-19. Data on cytokines, T lymphocytes, and other clinical and laboratory characteristics were collected from patients with variable disease severity. The effects of cytokines on the overall survival (OS) and event-free survival (EFS) of patients were analyzed. The critically severe and severe patients had higher infection indexes and significant multiple organ function abnormalities than the mild patients (P < 0.05). IL-6 and IL-10 were significantly higher in the critically severe patients than in the severe and mild patients (P < 0.05). IL-6 and IL-10 were closely associated with white blood cells, neutrophils, T lymphocyte subsets, D-D dimer, blood urea nitrogen, complement C1q, procalcitonin C-reactive protein. Moreover, the IL-6 and IL-10 levels were closely correlated to dyspnea and dizziness (P < 0.05). The patients with higher IL-10 levels had shorter OS than the group with lower levels (P < 0.05). The older patients with higher levels of single IL-6 or IL-10 tended to have shorter EFS (P < 0.05), while the patients who had more elevated IL-6 and IL-10 had shorter OS (P < 0.05). The Cox proportional hazard model revealed that IL-6 was the independent factor affecting EFS. IL-6 and IL-10 play crucial roles in COVID-19 prognosis.

Case Report: The Coronavirus Disease 2019 (COVID-19) Pneumonia With Multiple Thromboembolism.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out in Wuhan, China, in late December 2019 and has since spread rapidly around the world. Severe coronavirus disease 2019 (COVID-19) pneumonia patients have abnormal blood coagulation function, but their thromboembolism prevalence is still unknown. We reported a case of a 49-year-old man infected with COVID-19, presenting with fever, chest pain, limb weakness, myalgia, and dyspnea. The patient was diagnosed with severe COVID-19 pneumonia, pulmonary thromboembolism (PTE), deep vein thrombosis (DVT), and cerebral infarction. He received supportive and empirical treatment including anticoagulant treatment, anti-inflammatory treatment, oxygen supply, and inhalation therapy. The patient's symptoms, CT images, and laboratory results improved after treatment, and a throat swab was reported to be negative for SARS-CoV-2 virus by polymerase chain reaction (PCR) test. However, on day 51 of illness onset, CT reexamination demonstrated hemorrhagic infarction. Anticoagulant therapy was discontinued temporarily. After the patient tested negative for SARS-CoV-2 virus by PCR test six more times, he was discharged and remained in home quarantine. This case highlights the importance of clinician attentiveness to the appearance of multiple thromboembolism, especially in patients with severe pulmonary damage. It also emphasizes the diagnostic value of early CT imaging and the need for effective treatment once thrombotic events occur.

Selection of an Optimal Combination Panel to Better Triage COVID-19 Hospitalized Patients.

PURPOSE: It is difficult to predict the prognosis of COVID-19 patients at the disease onset. This study was designed to add new biomarkers into conventional inflammatory panels to build an optimal combination panel, to better triage patients and predict their outcomes. PATIENTS AND METHODS: Biochemical parameters representing multi-organ functions, cytokines, acute-phase proteins, and other inflammatory markers were measured in COVID-19 patients on hospital admission. Receiver operating characteristic (ROC) curves, logistic regression, event-free survival (EFS), and Cox analyses were performed to screen and compare the predictive capabilities of the new panel in patients with different illness severity and outcome. RESULTS: This study included 120 patients with COVID-19, consisting of 32 critical, 28 severe, and 60 mild/moderate patients. Initial levels of the selected biomarkers showed a significant difference in the three groups, all of which influenced patient outcome and EFS to varying degrees. Cox proportional hazard model revealed that procalcitonin (PCT) and interleukin 10 (IL-10) were independent risk factors, while superoxide dismutase (SOD) was an independent protective factor influencing EFS. In discriminating the critical and mild patients, a panel combining PCT, IL-6, and neutrophil (NEUT) yielded the best diagnostic performance with an AUC of 0.99, the sensitivity of 90.60% and specificity of 100%. In distinguishing between severe and mild patients, SOD's AUC of 0.89 was higher than any other single biomarker. In differentiating the critical and severe patients, the combination of white blood cell count (WBC), PCT, IL-6, IL-10, and SOD achieved the highest AUC of 0.95 with a sensitivity of 75.00% and specificity of 100%. CONCLUSION: The optimal combination panel has a substantial potential to better triage COVID-19 patients on admission. Better triage of patients will benefit the rational use of medical resources.

The coronavirus diseases 2019 (COVID-19) pneumonia with spontaneous pneumothorax: a case report.

BACKGROUND: The outbreak of the novel coronavirus (COVID-19) that was firstly reported in Wuhan, China, with cases now confirmed in more than 100 countries. However, COVID-19 pneumonia with spontaneous pneumothorax is unknown. CASE PRESENTATION: We reported a case of 66-year-old man infected with COVID-19, presenting with fever, cough and myalgia; The patient received supportive and empirical treatment including antiviral treatment, anti-inflammatory treatment, oxygen supply and inhalation therapy; The symptoms, CT images, laboratory results got improved after the treatments, and a throat swab was negative for COVID-19 PCR test; However, on the hospital day 30, the patient presented with a sudden chest pain and dyspnea. CT showed a 30-40% left-sided pneumothorax. Immediate thoracic closed drainage was performed and his dyspnea was rapidly improved. With five more times negative PCR tests for SARS-CoV-2 virus, the patient was discharged and home quarantine. CONCLUSION: This case highlights the importance for clinicians to pay attention to the appearance of spontaneous pneumothorax, especially patients with severe pulmonary damage for a long course, as well as the need for early image diagnose CT and effective treatment once pneumothorax occurs.

The role of isolation rooms, facemasks and intensified hand hygiene in the prevention of nosocomial COVID-19 transmission in a pulmonary clinical setting.

From December 25, 2019 to January 31, 2020, 33 cases of the coronavirus disease 2019 (COVID-19) were identified in the Department of Respiratory and Critical Care Medicine of Zhongnan Hospital of Wuhan University, China, yet none of the affiliated HCWs was infected. Here we analyzed the infection control measures used in three different departments in the Zhongnan Hospital of Wuhan University and correlated the measures with the corresponding infection data of HCWs affiliated with these departments. We found that three infection control measures, namely the isolation of the presumed positive patients, the use of facemasks and intensified hand hygiene play important roles in preventing nosocomial transmission of COVID-19.

Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China.

BACKGROUND: In late December 2019, an outbreak of acute respiratory illness, coronavirus disease 2019 (COVID-19), emerged in Wuhan, China. We aimed to study the epidemiology, clinical features and short-term outcomes of patients with COVID-19 in Wuhan, China. METHODS: We performed a single center, retrospective case series study in 221 patients with laboratory confirmed SARS-CoV-2 pneumonia at a university hospital, including 55 severe patients and 166 non-severe patients, from January 2, 2020 to February 10, 2020. RESULTS: Of the 221 patients with COVID-19, the median age was 55.0 years and 48.9% were male and only 8 (3.6%) patients had a history of exposure to the Huanan Seafood Market. Compared to the non-severe pneumonia patients, the median age of the severe patients was significantly older, and they were more likely to have chronic comorbidities. Most common symptoms in severe patients were high fever, anorexia and dyspnea. On admission, 33.0% patients showed leukopenia and 73.8% showed lymphopenia. In addition, the severe patients suffered a higher rate of co-infections with bacteria or fungus and they were more likely to developing complications. As of February 15, 2020, 19.0% patients had been discharged and 5.4% patients died. 80% of severe cases received ICU (intensive care unit) care, and 52.3% of them transferred to the general wards due to relieved symptoms, and the mortality rate of severe patients in ICU was 20.5%. CONCLUSIONS: Patients with elder age, chronic comorbidities, blood leukocyte/lymphocyte count, procalcitonin level, co-infection and severe complications might increase the risk of poor clinical outcomes.