Predictive value of immunoglobulin G, activated partial thromboplastin time, platelet, and indirect bilirubin for delayed viral clearance in patients infected with the Omicron variant.

Background: Omicron is the recently emerged highly transmissible severe acute respiratory syndrome coronavirus 2 variant that has caused a dramatic increase in coronavirus disease-2019 infection cases worldwide. This study was to investigate the association between demographic and laboratory findings, and the duration of Omicron viral clearance. Methods: Approximately 278 Omicron cases at the Ruijin Hospital Luwan Branch, Shanghai Jiaotong University School of Medicine were retrospectively analyzed between August 11 and August 31, 2022. Demographic and laboratory data were also collected. The association between demographics, laboratory findings, and duration of Omicron viral clearance was analyzed using Pearson correlation analysis and univariate and multivariate logistic regression. Results: Univariate logistic regression analyses showed that a prolonged viral clearance time was significantly associated with older age and lower immunoglobulin (Ig) G and platelet (PLT) levels. Using multinomial logistic regression analyses, direct bilirubin, IgG, activated partial thromboplastin time (APTT), and PLT were independent factors for longer viral shedding duration. The model combining direct bilirubin, IgG, APTT, and PLT identifies patients infected with Omicron whose viral clearance time was ≥7 days with 62.7% sensitivity and 83.4% specificity. Conclusion: These findings suggest that direct bilirubin, IgG, PLT, and APTT are significant risk factors for a longer viral shedding duration in patients infected with Omicron. Measuring levels of direct bilirubin, IgG, PLT, and APTT is advantageous to identify patients infected with Omicron with longer viral shedding duration.

Differences in clinical characteristics between younger and older patients with COVID-19 and their relationship with the length of hospital stay.

Background: The coronavirus disease 2019 (COVID-19) pandemic is currently threatening the health of individuals worldwide. We compared the clinical characteristics between younger patients (aged <60 years) and older patients (aged ≥60 years) with COVID-19, detected the risk factors associated with a prolonged hospital stay, and examined the treatments commonly used with a particular focus on antiviral therapies. Methods: This retrospective study was conducted at the West Campus, Union Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology (Wuhan, China). The sample consisted of 123 patients admitted to the hospital between 9th February, 2020, and 3rd March, 2020. The data related to the demographics, laboratory findings, and treatment were analyzed to identify discrepancies between younger and older patients and those with and without primary diseases. The risk factors that contribute to a prolonged hospital stay were subsequently identified. Results: Patients aged ≥60 years required longer hospital stay than younger patients (P=0.001). The percentage of lymphocytes was significantly lower in older patients and those with primary diseases (P=0.016 and P=0.042, respectively). The findings revealed that the risk factors that contributed to the length of hospital stay were age, the number of days of illness before hospitalization, white blood cell (WBC) count and albumin levels at admission, a neutrophil fraction at discharge, and antibiotic treatment. Analysis using a model that consisted of the above five risk factors for predicting prolonged hospital stay (>14 days) yielded an area under the ROC (AuROC) curve of 0.716. Antiviral and antibiotic treatments were administered to 97.6% and 39.0% of patients, respectively. The antiviral drugs most commonly administered were traditional Chinese medicine (83.7%) and arbidol (75.6%). Conclusions: In this study, older patients and those with primary diseases were at a higher risk of worse clinical manifestations. The physicians who treat the patients should pay close attention to the risk factors that contribute to the length of hospital stay, which could be used for predicting prolonged hospital stay. Traditional Chinese medicine and arbidol were the most frequently used antiviral drugs. Nevertheless, the extent to which these medications can effectively treat COVID-19 warrants further investigation.

Early Prediction Model for Critical Illness of Hospitalized COVID-19 Patients Based on Machine Learning Techniques.

Motivation: Patients with novel coronavirus disease 2019 (COVID-19) worsen into critical illness suddenly is a matter of great concern. Early identification and effective triaging of patients with a high risk of developing critical illness COVID-19 upon admission can aid in improving patient care, increasing the cure rate, and mitigating the burden on the medical care system. This study proposed and extended classical least absolute shrinkage and selection operator (LASSO) logistic regression to objectively identify clinical determination and risk factors for the early identification of patients at high risk of progression to critical illness at the time of hospital admission. Methods: In this retrospective multicenter study, data of 1,929 patients with COVID-19 were assessed. The association between laboratory characteristics measured at admission and critical illness was screened with logistic regression. LASSO logistic regression was utilized to construct predictive models for estimating the risk that a patient with COVID-19 will develop a critical illness. Results: The development cohort consisted of 1,363 patients with COVID-19 with 133 (9.7%) patients developing the critical illness. Univariate logistic regression analysis revealed 28 variables were prognosis factors for critical illness COVID-19 (p < 0.05). Elevated CK-MB, neutrophils, PCT, α-HBDH, D-dimer, LDH, glucose, PT, APTT, RDW (SD and CV), fibrinogen, and AST were predictors for the early identification of patients at high risk of progression to critical illness. Lymphopenia, a low rate of basophils, eosinophils, thrombopenia, red blood cell, hematocrit, hemoglobin concentration, blood platelet count, and decreased levels of K, Na, albumin, albumin to globulin ratio, and uric acid were clinical determinations associated with the development of critical illness at the time of hospital admission. The risk score accurately predicted critical illness in the development cohort [area under the curve (AUC) = 0.83, 95% CI: 0.78-0.86], also in the external validation cohort (n = 566, AUC = 0.84). Conclusion: A risk prediction model based on laboratory findings of patients with COVID-19 was developed for the early identification of patients at high risk of progression to critical illness. This cohort study identified 28 indicators associated with critical illness of patients with COVID-19. The risk model might contribute to the treatment of critical illness disease as early as possible and allow for optimized use of medical resources.

Severe Patients With ARDS With COVID-19 Treated With Extracorporeal Membrane Oxygenation in China: A Retrospective Study.

Background: The novel coronavirus disease 2019 (COVID-19) pandemic has become a global health crisis affecting over 200 countries worldwide. Extracorporeal membrane oxygenation (ECMO) has been increasingly used in the management of COVID-19-associated end-stage respiratory failure. However, the exact effect of ECMO in the management of these patients, especially with regards to complications and mortality, is unclear. Methods: This is the largest retrospective study of ECMO treated COVID-19 patients in China. A total of 50 ECMO-treated COVID-19 patients were recruited. We describe the main characteristics, the clinical features, ventilator parameters, ECMO-related variables and management details, and complications and outcomes of COVID-19 patients with severe acute respiratory distress syndrome (ARDS) that required ECMO support. Results: For those patients with ECMO support, 21 patients survived and 29 died (mortality rate: 58.0%). Among those who survived, PaO2 (66.3 mmHg [59.5-74.0 mmHg] and PaO2/FiO2 (68.0 mmHg [61.0-76.0 mmHg]) were higher in the survivors than those of non-survivors (PaO2: 56.8 mmHg (49.0-65.0 mmHg), PaO2/FiO2 (58.2 mmHg (49.0-68.0 mmHg), all P < 0.01) prior to ECMO. Patients who achieved negative fluid balance in the early resuscitation phase (within 3 days) had a higher survival rate than those who did not (P = 0.0003). Conclusions: In this study of 50 cases of ECMO-treated COVID-19 patients, a low PO2/FIO2 ratio before ECMO commencement may indicate a poor prognosis. Negative fluid balance in the early resuscitation phase during ECMO treatment was a predictor of increased survival post-ECMO treatment.

Extracorporeal membrane oxygenation (ECMO) for critically ill patients with coronavirus disease 2019 (COVID-19): A retrospective cohort study.

PURPOSE: The role of extracorporeal membrane oxygenatio (ECMO) for rescue therapy of respiratory failure in critically ill coronavirus disease 2019 (COVID-19) patients remains controversial. We aimed to evaluate the clinical outcomes of ECMO in the treatment of COVID-19 compared with conventional ventilation support. METHODS: In this retrospective cohort study, data were collected on extremely critical patients with COVID-19 from January 2020 to March 2020 in intensive care unit of a hospital in charge by national rescue team in Wuhan, China, the epicenter of pandemic. Patients were classified into the ECMO group and the conventional ventilation non-ECMO group. Clinical characteristics, technical characteristics, laboratory results, mortality, and complications of the two groups were analyzed. RESULTS: 88 patients with extremely critical COVID-19 were screened; 34 received ECMO support and 31 received conventional ventilation support. Both groups had comparable characteristics at baseline in terms of age, gender, and comorbidities. Before ECMO or conventional therapy, patients in the two groups had sever acute respiratory distress syndrome with a mean partial pressure of arterial oxygen to the fraction of inspired oxygen (PaO2 /FiO2 ) ratio of 69.6 and 75.4, respectively. At the time of reporting, patients in the ECMO had significantly lower in-hospital mortality compared with the control group (58.8 vs. 93.5%, p = .001). CONCLUSION: ECMO is shown to decrease the mortality of extremely critical ill COVID-19 patients compared with the conventional treatment. Although complications occurred frequently, ECMO could still be a rescue therapy for the treatment of COVID-19 during the pandemic.

Depressive and Anxiety Symptoms of Healthcare Workers in Intensive Care Unit Under the COVID-19 Epidemic: An Online Cross-Sectional Study in China.

Background: Since the coronavirus disease-2019 (COVID-19) outbreak, intensive care unit (ICU) healthcare workers were responsible for the critical infected patients. However, few studies focused on the mental health of ICU healthcare workers. This study aimed to investigate the psychological impact of COVID-19 on ICU healthcare workers in China. Methods: We distributed the nine-item Patient Health Questionnaire (PHQ-9) and seven-item General Anxiety Disorder questionnaire (GAD-7) online to ICU healthcare workers in China. Respondents were divided into frontline and second-line according to whether they have contact with COVID-19 patients. Depressive and anxiety symptoms of all respondents were evaluated based on their questionnaire scores. Results: There were 731 ICU healthcare workers finally enrolled in our study, including 303 (41.5%) male, 383 (52.4%) doctors, and 617 (84.4%) aged 26-45 years. All in all, 482 (65.9%) ICU healthcare workers reported symptoms of depression, while 429 (58.7%) reported anxiety. There was no significant difference between frontline (n = 325) and second-line (n = 406) respondents in depression (P = 0.15) and anxiety severity (P = 0.56). Logistic regression analysis showed that being female, ICU work time >5 years, and night duty number ≥10 were risk factors of developing depressive and anxiety symptoms. Income reduction was separately identified as risk of anxiety. Additionally, ICU work time >5 years was also identified as risk of developing moderate-severe depressive and anxiety symptoms. Conclusions: Frontline ICU work was not associated with higher risk of depressive and anxiety symptoms during COVID-19 pandemic remission period in China. Actions like controlling night duty number, ensuring vacation, and increasing income should be taken to relieve mental health problem. Furthermore, we should pay close attention to those who had worked long years in ICU.