Coronavirus Disease 2019 Patients Research Articles

Retrospective analysis of risk factors associated with mortality in hospitalized COVID-19 patients.

Older age and comorbidities are associated with adverse outcomes in patients with coronavirus disease 2019 (COVID-19); however, comprehensive identification of mortality risk factors can further guide disease management. We aimed to analyze predictors of in-hospital mortality in hospitalized COVID-19 patients. This retrospective cohort study included 400 COVID-19 patients admitted between March and December 2020. Demographics, vital signs, medical history, presenting symptoms, laboratory findings, treatments, and outcomes were extracted from the patient's electronic medical records. Patients were stratified into survivor (n = 300) and nonsurvivor (n = 100) groups. Univariate and multivariate logistic regressions were used to analyze associations between variables and mortality. Nonsurvivors were older (mean age 65 vs 45 years) and had more hypertension (60% vs 33%), diabetes (40% vs 20%), chronic obstructive pulmonary disease (20% vs 5%), and chronic kidney disease (15% vs 3%). Shorter symptom onset to admission (7 vs 4 days), lower oxygen saturation (92% vs 96%), lymphopenia, and elevated inflammatory and coagulation markers were also associated with mortality (all P < 0.001). Mechanical ventilation (60% vs 3%) and therapeutic anticoagulation were more common in nonsurvivors (all P < 0.001). Age over 75 years (adjusted odds ratio 5.2), chronic medical conditions, elevated D-dimer, and mechanical ventilation had the strongest independent associations with mortality (P < 0.001). Older age, comorbidities such as chronic pulmonary and renal disease, disease severity parameters such as dysregulated inflammatory and coagulation markers, and the need for aggressive interventions predict increased mortality risk in hospitalized COVID-19 patients.

Cardiac Affection in COVID-19 Pediatrics and its Correlation with Inflammatory Markers

Abstract Background Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a pandemic of respiratory and cardiovascular diseases, known as coronavirus disease 2019 (COVID-19). However, the respiratory system is the primary target of SARS-CoV-2, it also causes a systemic illness with widespread inflammation and cytokine flood, resulting in acute respiratory distress syndrome (ARDS), severe cardiovascular injury, multiorgan failure (MOF), and death in its most severe form. COVID-19 progression severity can be detected by cardiac signs. Detection of subtle cardiac damage early allows for providing efficient treatment. Objective The current study aimed to detect cardiac involvement in COVID-19 and its correlation with other inflammatory markers elevated in COVID-19 patients. Methods This retrospective analytical observational study included a total of 72 patients diagnosed as positive for COVID-19, depending on PCR of nasopharyngeal swabs, at Children’s Hospital, Ain Shams University in the period between December 2021 to March 2022. Patients included were within the pediatrics age group, from 4 months to 16 years old. They underwent full clinical examination, laboratory investigations, chest radiological studies, and echocardiographic assessment after 48 hours of admission. These patients were admitted in the isolation unit and later 30 (41.6%) patients were admitted in PICU. Patients were further grouped into 2 groups: Group I without cardiac affection, and Group II with cardiac affection. Results Patients with cardiac affection (group II) had more thrombocytopenia (61.5%) (P-value = 0.037), higher ESR (Median (IQR) = 62.5 (33 – 90))(P-value = 0.000), higher D- dimer (Median (IQR) = 4.25 (2.33–7.37))(P-value = 0.001), higher serum ferritin (Median (IQR) = 1200 (1022–3421))(P-value = 0.281), higher CK-MB (Median (IQR) = 33.5 (28–46)) (P-value = 0.000) and as a consequence, higher troponin I (Median (IQR) = 0.24 (0.1–0.46))(P-value = 0.000). Regarding Echo findings, cardiac affection showed a lower ejection fraction in (88.5%) of group II patients with Mean±SD (50.23 ± 6.69) (P-value = 0.000). The most frequent Echo finding was carditis (46.2%), followed by valvular lesions (42.3%), especially Tricuspid regurge. All the non-survivor (dead) cases (only 8 patients) were with cardiac affection. Conclusions COVID-19 can cause cardiovascular complications in pediatrics and correlate with inflammatory markers of COVID-19, which also can predict severe prognosis.

Role of Biomarkers Diagnostic Tools in Patients with COVID-19: Stratification Made Easy.

In coronavirus disease 2019 (COVID-19) patients, several serum biomarkers have been identified. Upon intensive care unit (ICU) admission, these laboratory markers become more crucial to distinguish between patients with severe cases of COVID-19. It might assist doctors in predicting the course of illnesses and treating patients appropriately. This work was to investigate the role of biomarkers in patients with COVID-19 classification admitted to the hospital and identified by reverse transcription polymerase chain reaction (RT-PCR). Peripheral blood sample was taken from COVID-19 cases isolated on admission to determine C-reactive protein (CRP), D-dimer, Fibrinogen, neutrophil-lymphocyte ratio (NLR), leukocytes CRP ratio (LeCR), lymphocyte-CRP ratio (LCR), interleukin-6 (IL6), leukocytes interleukin 6 ratio (LeIL6), systemic inflammatory index (SII), platelet-to-lymphocyte ratio (PLR), and tissue plasminogen activator inhibitor one (tPAI-1). Follow-up for IL6, Ferritin, D-dimer, and tPAI-1 were determined on the 3rd and 7th days. Comparisons of severity revealed that hypertension, chronic obstructive pulmonary disease (COPD), and Ischemia were major risk factors in COVID-19 patients. There was a statistically significant difference between the test groups for fibrinogen (p < 0.000), IL6 (p < 0.009), LeCR (p < 0.006), and LCR (p < 0.011). Based on laboratory test findings at the time of ICU admission, we can distinguish severe cases of COVID-19.

Risks and outcomes among coronavirus disease 2019 patients admitted to Assiut University Hospital

Introduction The clinical characteristics present with coronavirus disease 2019 (COVID-19) encompasses asymptomatic to severe disease and mortality. Clinicians need to detect patients whose risk of illness progression and unfavorable outcomes is high. Aim To evaluate potential risk factors affecting the severity and outcome of coronavirus infection in patients admitted to Assiut University. Patients and methods From October 2021 to October 2022, Assiut University Hospital served as the site of this observational analytical cross-sectional single-centered study. A full medical history, examination, radiographic, and laboratory investigations were performed on patients. Results The primary risk variables for mortality of COVID-19 patients include a greater mean age (73.61 ± 10.51) (P value&lt;0.001). Individuals with chronic kidney disease (P value=0.005), and liver cirrhosis (P value&lt;0.001). Those unvaccinated against COVID-19 the (P value = 0.004). Laboratory findings can be used as a predictor of infection severity as higher median white blood cell count (P value=0.044), lower median lymphocytic count (P value=0.028), higher serum ferritin (P value=0.02). Radiologically, a significant higher mean computed tomography severity score percentage is noticed among died patients (16.61 ± 4.55%) (P value&lt;0.001). Conclusion Advanced age, patients with renal or hepatic impairment, patients with lower lymphocytic counts or with higher computed tomography severity score are linked to a worse clinical course and outcome among COVID-19 patients who were admitted to Assiut University Hospital. Trial registration ClinicalTrials.gov. NCT04860232.

Cytokine Profile in Children Following SARS-CoV-2 Infection: Preliminary Findings.

We provide preliminary evidence that, also in children, Long coronavirus disease (COVID) may be characterized by a proinflammatory signature. Ten Long COVID patients, 7 convalescent subjects after COVID infection and 4 healthy controls were enrolled. When adjusted for sex, children with long COVID had statistically significant differences in the levels of Flt3L, CD5, uPA, CCL23, CD40 and TGFα. When adjusted for age, CCL23 levels remained statistically significant.

Incidence of Long COVID-19 at 12-18 Months Following Delta Wave of Coronavirus Disease 2019: Hospital-based Prospective Registry.

Long coronavirus disease 2019 (COVID-19) has emerged as an important consequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To identify its incidence 12-18 months following hospitalization in patients with COVID-19, we performed a prospective study. Virologically confirmed successive patients with moderate-to-severe COVID-19, hospitalized during the delta wave in India, were recruited. Data on clinical features, investigations, and outcomes were obtained. Long COVID-19 was diagnosed using the European quality of life questionnaire (EQ-5D) and Birmingham symptom burden questionnaire (SBQ) at 12-18-month follow-up. During the study period (January-July 2021), we evaluated 8,680 suspected COVID-19 patients, of whom 1,641 were confirmed virologically and 388 were hospitalized. Men accounted for 64.4%, individuals aged >60 years for 41.5%, hypertension for 42.8%, diabetes for 38.4%, and cardiovascular disease for 17.3%. At admission, there was a high prevalence of cough (71.1%), fever (86.6%), and oxygen requirement (38.6%). Proning was deployed in 89.2% of cases, nasal cannula in 36.3%, nonrebreather masks in 15.7%, noninvasive ventilation in 14.4%, and invasive ventilation in 16.2%. In-hospital deaths totaled 75 (19.3%), with 310 discharged for home care and eligible for follow-up. At a median follow-up of 15 months, 9 patients had died, 40 were lost to follow-up, and 264 were evaluated. The incidence of Long COVID-19 was 45 [17.0%, 95% confidence of interval (CI) 12.6-21.9%]. The median EQ-5D score was 5.0, with >5 observed in only 11 patients (0.6%). Using the SBQ, new-onset dyspnea on exertion was noted in 13 (4.9%), rest dyspnea in 7 (2.6%), fatigue in 31 (11.7%), feverishness in 18 (6.8%), and low energy in 16 (6.1%). Long COVID-19 was significantly more prevalent in women and older individuals. In Long COVID-19 compared to controls, the mean duration of oxygen requirement (5.46 ± 9.8 vs 2.46 ± 4.5 days, p = 0.002), use of nonrebreather masks (17.8 vs 7.3%, p = 0.026), noninvasive ventilation (11.1 vs 3.2%, p = 0.020), and duration of intensive care unit (ICU) stay (13.5, 8.7-17.3 vs 8.0, 5.0-11.0 days, p = 0.028) were significantly higher. The incidence of Long COVID-19 at 12-18 months follow-up is 17.0%. It is significantly higher in women, older age groups, and patients requiring longer oxygenation, nonrebreather oxygen masks, noninvasive respiratory support, and extended stays in the ICU.

Coronavirus Disease-19-associated Mucormycosis: A Single-center Observational Study of 69 Patients.

We studied the clinical presentation, risk factors, complications, and in-hospital outcomes of patients with coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM). A retrospective study was done on 69 COVID-19 patients with microbiologically proven mucormycosis admitted over a period of seven months from March 2021 to September 2021. All 69 mucormycosis patients (46 males, 23 females) had reverse transcriptase-polymerase chain reaction (RT-PCR)-confirmed COVID-19 infection. Their mean age was 52.8 years, with mucormycosis developing in 51 patients (73.9%) within 30 days of COVID-19 infection; 7 (10.1%) were positive on admission. Rhino-orbital-cerebral mucormycosis (ROCM) was the most common (40.3%), followed by rhino-orbital (37.3%) and sinonasal (22.4%). Diabetes mellitus was present in 98.6% of patients. Common symptoms of mucormycosis were facial pain, headache, facial swelling, and vision loss. During COVID-19, 88.4 and 52.5% received immunosuppressive treatment and zinc sulfate, respectively; 34.7% needed intensive care unit (ICU) admission. The mortality rate was 26.1%. On multivariate logistic regression analysis, the presence of chronic kidney disease, leukocytosis, ophthalmoplegia, oral/palate ulceration, current need for invasive ventilation, and past duration of oxygen therapy and zinc supplementation were significantly associated with mortality. Patients with current COVID-19 infection had severe disease with increased need for intensive care (57.1 vs 14.5%) and higher mortality (57.1 vs 22.6%) compared to mucormycosis patients with previous COVID-19 infection. Rhino-orbital-cerebral, rhino-orbital, and sinonasal were the most common presentations in cases of mucormycosis, with a mortality rate of 26.1%. COVID-19 coinfection predisposes patients with mucormycosis to severe disease with higher mortality.

Efficacy of Azvudine Therapy in Patients with Severe and Non-Severe COVID-19: A Propensity Score-Matched Analysis.

Azvudine is used to treat patients with the coronavirus disease 2019 (COVID-19). This study evaluated the clinical efficacy of azvudine in hospitalized patients with different severities of COVID-19 because few studies have described this in patients with severe and non-severe COVID-19. This retrospective study included hospitalized patients with COVID-19 in Guizhou Provincial People's Hospital between December 2022 and January 2023. Azvudine-treated patients and controls were matched for sex, age, and disease severity at admission. Laboratory results and outcomes, including all-cause mortality, invasive mechanical ventilation, intensive care unit admission, and hospital stay length, were evaluated. Stratified analysis was used to explore the difference in the efficacy of azvudine in severe and non-severe COVID-19 patients. No significant differences in all-cause mortality were observed between the 303 azvudine recipients and 303 matched controls. However, azvudine-treated patients had shorter hospital stays (8.34±4.79 vs 9.17±6.25 days, P=0.046) and higher lymphocyte improvement rates (21.5% vs 13.9%, P=0.019), with a more pronounced effect in patients with non-severe COVID-19 (length of hospital stay, 8.07±4.35 vs 10.00±6.29 days, P=0.001; lymphocyte improvement rate, 23.8% vs 12.8%, P=0.015). Azvudine treatment shortens hospital stay length and increases the rate of lymphocyte count improvement in patients with non-severe COVID-19, suggesting that azvudine may be a treatment option for these patients.

Impact of serum IL-10 level on the clinical outcome of COVID-19 patients and the development of post-COVID pulmonary fibrosis

A characteristic feature of the cytokine storm in coronavirus disease 2019 (COVID-19) is the dramatic elevation of serum interleukin 10 (IL-10). This may be a negative feedback mechanism to suppress inflammation. However, this IL-10 elevation may contribute to COVID-19 severity. In our study, we aimed to evaluate the effect of serum IL-10 level on patients' clinical outcome and the incidence of post-COVID19 pulmonary fibrosis. This was a prospective observational study, included 100 patients, confirmed to have COVID-19, Of these, 50 patients had COVID-19 without evidence of pneumonia in computed tomography (CT) scans (group I) and the other 50 patients had COVID-19 pneumonia (group II). Our results showed a significant increase in serum ferritin level in patients with COVID pneumonia. However, no difference was found in serum C-reactive protein (CRP) nor D-Dimer between both groups. There was a statistically significant increase in serum IL-10 in patients with COVID pneumonia compared with COVID patients without pneumonia (p&lt;0.001). Fibrosis was developed in 35 patients (70%) with COVID pneumonia after 3 months and 4 of them died, however, all patients without pneumonia survived. Among age, serum IL-10, aspartate aminotransferase (AST), alanine transaminase (ALT), elevated serum IL-10 was found to be an independent predictor of pneumonia (p=0.32). However, there was no significant effect for IL-10 on patients’ clinical outcome. There was a statistically significant correlation between serum IL-10 levels and oxygen (O2) demand, CRP and D-Dimer (p= 0.015, p=0.034 and p=0.042, respectively). The higher the level of IL-10 the less fibrosis detected in follow up CT scans (p=0.038). In conclusion, even though IL-10 was significantly associated with disease severity (higher in pneumonia), elevated serum Il-10 has an independent role in decreasing the incidence of post-COVID-19 pulmonary fibrosis.

Clinical characteristics and outcomes of critically ill COVID-19 patients with CAUTI: a study in Vietnam.

Urethral catheterization is commonly required in coronavirus disease 2019 (COVID-19) patients hospitalized in intensive care units (ICUs). However, this increases their vulnerability to nosocomial infections such as catheter-associated urinary tract infections (CAUTIs). Existing studies on nosocomial infections in COVID-19 patients usually report CAUTI prevalence but neglect the clinical differences between CAUTI and non-CAUTI patients. This study aimed to assess clinical features, microbiological characteristics, and outcomes of COVID-19 patients with CAUTI vs non-CAUTI patients in an ICU. We analyzed the clinical data from a retrospective cohort study of 527 critically ill COVID-19 patients who required urethral catheterization at the ICU of Bach Mai hospital in Ho Chi Minh City, Vietnam, from August to October 2021. A total of 69 patients (n = 37 CAUTI vs n = 32 non-CAUTI) were selected for urine culture, and their clinical features, microbiological characteristics, and outcomes were recorded for analysis. COVID-19 patients with CAUTI had a higher mortality rate compared to those without CAUTI (p = 0.02). The length of stay in the ICU was 1.4 times longer for CAUTI patients compared to the non-CAUTI group (p = 0.03). Fungi was the most common microbiological cause of UTI in COVID-19 ICU (91.4%), and Pseudomonas aeruginosa was a significant risk factor of CAUTI. P. aeruginosa, number of antibiotics used, and duration of catheterization had a strong association with the patients' survival time in ICU. This study provides a better understanding of CAUTI in COVID-19 patients, thus facilitating their future treatment.

IFN Lambda Deficiency Contributes to Severe COVID-19 Outcomes.

Interferons (IFNs) produced by airway epithelial cells are crucial in defending against pathogens. Fluctuations in IFN-λ levels may influence coronavirus disease 19 (COVID-19) severity. However, conflicting data have been reported regarding serum IFN-λ concentrations in COVID-19 patients. To address this, we evaluated serum IFN-λ levels over time in moderate and severe COVID-19 patients and their association with cytokine production and clinical parameters using the enzyme-linked immunosorbent assay (ELISA) and the Bio-Plex Pro Human Cytokine 17-plex Assay. Results from testing 51 COVID-19 patients showed that 68% lacked detectable serum IFN-λ. Among non-IFN-λ secretors, severe COVID-19 predominated. In contrast, IFN-λ secretors displayed stable IFN-λ levels in moderate cases, while severe cases showed a decline over time, which persisted even after recovery. A negative correlation was observed between IFN-λ levels and inflammatory markers. This, combined with an increase in tumor necrosis factor alpha (TNF-α) and clinical improvement, suggests a regulatory role for IFN-λ in promoting faster recovery. Despite this, survival rates were similar between the groups, indicating that while IFN-λ influences the course of the disease, it does not directly affect overall survival. In conclusion, IFN-λ is vital, but not unique, for the antiviral response and COVID-19 recovery. Simultaneously, serum IFN-λ deficiency signifies severe COVID-19.

Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.

During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the disease has placed an enormous burden on the world's healthcare and economy. The early risk assessment system based on a variety of machine learning (ML) algorithms may be able to provide more accurate advice on the classification of COVID-19 patients, offering predictive, preventive, and personalized medicine (PPPM) solutions in the future. In this retrospective study, we divided a portion of the data into training and validation cohorts in a 7:3 ratio and established a model based on a combination of two ML algorithms first. Then, we used another portion of the data as an independent testing cohort to determine the most accurate and stable model and compared it with other scoring systems. Finally, patients were categorized according to risk scores and then the correlation between their clinical data and risk scores was studied. The elderly accounted for the majority of hospitalized patients with COVID-19. The C-index of the model constructed by combining the stepcox[both] and survivalSVM algorithms was 0.840 in the training cohort and 0.815 in the validation cohort, which was calculated to have the highest C-index in the testing cohort compared to the other 119 ML model combinations. Compared with current scoring systems, including the CURB-65 and several reported prognosis models previously, our model had the highest AUC value of 0.778, representing an even higher predictive performance. In addition, the model's AUC values for specific time intervals, including days 7,14 and 28, demonstrate excellent predictive performance. Most importantly, we stratified patients according to the model's risk score and demonstrated a difference in survival status between the high-risk, median-risk, and low-risk groups, which means a new and stable risk assessment system was built. Finally, we found that COVID-19 patients with a history of cerebral infarction had a significantly higher risk of death. This novel risk assessment system is highly accurate in predicting the prognosis of patients with COVID-19, especially elderly patients with COVID-19, and can be well applied within the PPPM framework. Our ML model facilitates stratified patient management, meanwhile promoting the optimal use of healthcare resources.

Lung field-based severity score (LFSS): a feasible tool to identify COVID-19 patients at high risk of progressing to critical disease.

Coronavirus disease 2019 (COVID-19) still poses a threat to people's physical and mental health. We proposed a new semi-quantitative visual classification method for COVID-19, and this study aimed to evaluate the clinical usefulness and feasibility of lung field-based severity score (LFSS). This retrospective study included 794 COVID-19 patients from two hospitals in China between December 2022 and January 2023. Six lung fields on the axial computed tomography (CT) were defined. LFSS and eighteen clinical characteristics were evaluated. LFSS was based on summing up the parenchymal opacification involving each lung field, which was scored as 0 (0%), 1 (1-24%), 2 (25-49%), 3 (50-74%), or 4 (75-100%), respectively (range of LFSS from 0 to 24). Total pneumonia burden (TPB) was calculated using the U-net model. The correlation between LFSS and TPB was analyzed. After performing logistic regression analysis, an LFSS-based model, clinical-based model and combined model were developed. Receiver operating characteristic curves were used to evaluate and compare the performance of three models. LFSS, age, chronic liver disease, chronic kidney disease, white blood cell, neutrophils, lymphocytes and C-reactive protein differed significantly between the non-critical and critical group (all P<0.05). There was a strong positive correlation of LFSS and TPB (Pearson correlation coefficient =0.767, P<0.001). The area under curves of LFSS-based model, clinical-based model and combined model were 0.799 [95% confidence interval (CI): 0.770-0.827], 0.758 (95% CI: 0.727-0.788), and 0.848 (95% CI: 0.821-0.872), respectively. The LFSS derived from chest CT may be a potential new tool to help identify COVID-19 patients at high risk of progressing to critical disease.

SARS-CoV-2 infection is associated with intestinal permeability, systemic inflammation, and microbial dysbiosis in hospitalized patients.

Coronavirus disease 2019 (COVID-19) and its associated severity have been linked to uncontrolled inflammation and may be associated with changes in the microbiome of mucosal sites including the gastrointestinal tract and oral cavity. These sites play an important role in host-microbe homeostasis, and disruption of epithelial barrier integrity during COVID-19 may potentially lead to exacerbated inflammation and immune dysfunction. Outcomes in COVID-19 are highly disparate, ranging from asymptomatic to fatal, and the impact of microbial dysbiosis on disease severity is unclear. Here, we obtained plasma, rectal swabs, oropharyngeal swabs, and nasal swabs from 86 patients hospitalized with COVID-19 and 12 healthy volunteers. We performed 16S rRNA sequencing to characterize the microbial communities in the mucosal swabs and measured concentrations of circulating cytokines, markers of gut barrier integrity, and fatty acids in the plasma samples. We compared these plasma concentrations and microbiomes between healthy volunteers and COVID-19 patients, some of whom had unfortunately died by the end of the study enrollment, and performed a correlation analysis between plasma variables and bacterial abundances. Rectal swabs of COVID-19 patients had reduced abundances of several commensal bacteria including Faecalibacterium prausnitzii and an increased abundance of the opportunistic pathogens Eggerthella lenta and Hungatella hathewayi. Furthermore, the oral pathogen Scardovia wiggsiae was more abundant in the oropharyngeal swabs of COVID-19 patients who died. The abundance of both H. hathewayi and S. wiggsiae correlated with circulating inflammatory markers including IL-6, highlighting the possible role of the microbiome in COVID-19 severity and providing potential therapeutic targets for managing COVID-19.IMPORTANCEOutcomes in coronavirus disease 2019 (COVID-19) are highly disparate and are associated with uncontrolled inflammation; however, the individual factors that lead to this uncontrolled inflammation are not fully understood. Here, we report that severe COVID-19 is associated with systemic inflammation, microbial translocation, and microbial dysbiosis. The rectal and oropharyngeal microbiomes of COVID-19 patients were characterized by a decreased abundance of commensal bacteria and an increased abundance of opportunistic pathogens, which positively correlated with markers of inflammation and microbial translocation. These microbial perturbations may, therefore, contribute to disease severity in COVID-19 and highlight the potential for microbiome-based interventions in improving COVID-19 outcomes.

Assessing COVID-19 outcomes among healthcare workers: a retrospective study.

The purpose of this research was to investigate the outcomes of coronavirus disease 2019 (COVID-19) infection in healthcare workers, assess the incidence of infection among them, and identify factors linked to the severity of the disease. This cross-sectional study was conducted retrospectively in Duhok city, Kurdistan Region of Iraq, from September 2021 to January 2023. The study included 1,958 participants, of whom 1,338 (68.33%) contracted the infection. Among them, 830 (62.03%) and 372 (27.81%) patients experienced mild and moderate infections, respectively, while 136 (10.1%) had severe infections. The results indicated that several factors, including maintaining a healthy lifestyle, avoiding obesity, having a chronic condition, working consecutive hours, and being in an overwhelmed work environment were significantly associated with a higher severity of infection (p < 0.05). However, factors such as smoking habits, adherence to preventive health guidelines, direct exposure to COVID-19 patients, work days and patterns, family members with COVID-19, and hand/glove sterilization did not appear to have a significant effect on the severity of infection (p > 0.05). These findings may offer valuable insights for clinicians and public health officials, and aid in the development of effective strategies to manage COVID-19 patients based on their risk factors for infection severity.

Investigation of ADAMTS-13 levels in patients with COVID-19 infection.

Coronavirus disease 2019 (COVID-19) patients are predisposed to thrombotic events. COVID-19 coagulopathy can be associated with ADAMTS-13 (a disintegrin-like and metalloprotease with thrombospondin type I repeats 13) levels. ADAMTS-13, the cleaving protease of highly thrombogenic ultra-large von Willebrand Factor (vWF) multimers, was rarely investigated in COVID-19 patients and inconsistent results were obtained. We measured ADAMTS-13 levels of patients admitted to emergency department. A prospective study was carried out with 180 individuals at the Emergency Department of Uşak Training and Research Hospital. The patients were divided into three groups: mild COVID-19 (group 2), severe COVID-19 with oxygen saturation below 94% (group 3), and control group (group 1). ADAMTS-13 levels were analyzed with an enzyme linked immunosorbent assay (ELISA) kit (SunRed, Shanghai, China). Demographic data, clinical findings, and routine laboratory test results (alanine aminotransferase (ALT), aspartate aminotransferase (AST), white blood cell, lymphocyte, platelet, C-reactive protein (CRP), lactate dehydrogenase (LDH), prothrombin time, international normalized ratio (INR), partial thromboplastin time, D-dimer, creatinine, urea) were evaluated. ADAMTS-13 serum levels were slightly lower in groups 2 and 3 compared to the control group, with no significant difference between the ADAMTS-13 median values (p > 0.05). Groups 1 and 2 exhibited comparable outcomes. Group 3 demonstrated notably elevated levels of CRP, LDH, D-dimer, AST, ALT, creatinine; and decreased platelet counts and INR levels (p < 0.05). COVID-19-associated coagulopathy is still unclear. Based on our data, ADAMTS-13 levels cannot be used as a biomarker to help stratify patients' risks at the time of admission.

D-Dimer, ferritin, and lactate dehydrogenase (LDH) as predictors of mortality in hospitalized COVID-19 patients.

Several laboratory parameters may be predictors of coronavirus disease 2019 (COVID-19) mortality. This study aimed to analyze the potential of D-dimer, ferritin, and lactate dehydrogenase (LDH) to predict mortality in severe COVID-19 patients. A retrospective cohort study, including 147 patients, was examined using secondary data from medical records of hospitalized COVID-19 patients. D-dimer, ferritin, and LDH levels were obtained from the patients' blood analysis on first hospitalization. Patients were then categorized into a survival group (97 patients) and a non-survival group (50 patients) based on final outcome. Proportions and means were analyzed using Chi square and Mann-Whitney tests. Further, the correlation and accuracy were analyzed using partial correlations test and receiver operating characteristic curve analysis. The combination of multiple predictors was also analyzed. The non-survival group had significantly higher levels of D-dimer (32.11 ± 13.05 vs. 9.57 ± 16.65; p < 0.001), ferritin (1719.84 ± 539.52 vs. 808.83 ± 664.81; p < 0.001), and LDH (1782.92 ± 1537.92 vs. 622.848 ± 274.79; p < 0.001) than the survival group. These parameters also had a moderate correlation with mortality (r > 0.500) and robust sensitivity and specificity for predicting mortality, especially ferritin (AUC = 0.906; sensitivity = 92.3%; specificity = 87.5%; p < 0.001), and the combination of ferritin and LDH with or without D-dimer (AUC = 0.959; sensitivity = 100%; specificity = 87.5%; p < 0.001). The levels of these parameters are significantly higher, have robust sensitivity and specificity, and can be used as predictors of mortality.

A Fatal Co-infections of Aspergillus latus and Pneumocystis jirovecii in COVID-19 Pneumonia Patient: Case Report

Introduction: For coronavirus disease 2019 (COVID-19) positive patients, co-infection with fungi has previously been reported. Owing to non-specific clinical manifestations and radiographic evidence, it is difficult to distinguish fungal infection from COVID-19 alone, resulting in delayed diagnosis and lack of appropriate treatment. Aspergillus latus infection, a newly rare species with life-threatening characteristics, requires rapid detection with accurate diagnosis to reduce mortality. However, there is little literature that provides a reference for a better understanding of this rare pathogen and guides medical practitioners in choosing the right diagnostics and therapies. Case Presentation: We reported a 67-year-old female complaining of fever, cough, and chest tightness, who had previously been hospitalized for a week due to initial COVID-19 pneumonia. On admission, clinical manifestations and radiological evidence were consistent with COVID-19 pneumonia, and there was no obvious improvement after anti-infective therapy. In terms of etiology for the patient, Galactomannan test was positive for Aspergillus genus, and Metagenomic next-generation sequencing further determined co-infections of A. latus and Pneumocystis jirovecii. Subsequently, isolation of A. latus was obtained through microbial culture. Despite targeted antifungal therapy, no clinical improvement was observed, possibly due to delayed diagnosis and treatment. Finally, the patient died of respiratory failure. Conclusions: This case report demonstrated that metagenomic next-generation sequencing is a fast, unbiased, culture-free approach that can increase the detection of rare pathogens, helping clinicians improve the accuracy of clinical diagnosis and take therapeutic action as quickly as possible. Clinicians should be aware of the risk of COVID-19-associated pulmonary Aspergillosis in COVID-19 patients, and we hope to optimize diagnosis and improve outcomes of COVID-19-associated pulmonary Aspergillosis.

Study of biomarkers to determine severity and lung damages in COVID-19 patients.

Identifying inflammation and lung damage markers is crucial in reducing morbidity and mortality of coronavirus disease 2019 (COVID-19). This study aimed to examine the validity and reliability of severity and post-infection lung damage and analyse their relationship. This was a prospective analysis study at the Airlangga University Hospital, Surabaya, Indonesia, from March to August 2021. The infection`s severity was measured by examining angiotensin-converting enzyme 2 (ACE2) levels and complete blood count. Lung damage was estimated by reviewing Krebs von de Lungen (KL)-6, matrix metalloproteinase (MMP)-9, tissue inhibitor metalloproteinase (TIMP)-1, and MMP-9/TIMP-1. Two-factor confirmatory factor analysis (CFA) and canonical correlation were calculated using Lisrel and SPSS (version 25). The research sample included 76 patients. The t count loading factor values were calculated: ACE2 (6.00), neutrophils (-0.80), lymphocytes (-0.63), neutrophil-lymphocyte ratio (NLR, 1.27), eosinophils (-1.52), basophils (1.72), monocytes (0.05), platelets (0.53), leukocytes (-0.51), platelet-lymphocyte ratio (PLR, -1.15), KL-6 (10.47), MMP-9 (11.91), TIMP-1 (11.79), and MMP-9/TIMP-1 (-0.24). The t values were: neutrophil covariance error (6.11), lymphocytes (6.12), NLR (6.10), eosinophils (6.08), basophils (6.07), monocytes (6.12), platelets (6.12), leukocytes (6.12), PLR (6.10), ACE2 (0.97), KL-6 (5.63), MMP-9 (2.08), TIMP-1 (2.77), and MMP-9/TIMP-1 (6.12). t value canonical correlation of 7.04 (t count > 1.96) indicated a correlation between the severity of the patient and post-infection lung damage. The severity was adequately measured through ACE2, IL-6, IL-10, neutrophils, lymphocytes, leukocytes, and NLR. Lung damage was measured with KL-6, MMP-9, and TIMP-1. There was a correlation between disease severity and lung damage.

A single-center experience in home management of mild and moderate COVID-19 cases.

The use of telemedicine for treatment of coronavirus disease 2019 (COVID-19) infection has been effective in lowering the risk of infection and relieving strain on the healthcare system. This study aimed to describe the clinical characteristics of COVID-19 cases, their follow-up, risk factors of disease severity, and predictors of hospital admission while using telemedicine. The study included 611 Egyptian patients with mild and moderate COVID-19 disease. The patients were isolated at home and monitored daily. Based on the World Health Organization classification, 79% of studied patients had mild illness while 20.5% had moderate illness. The initial symptoms included cough (51.7%), fever (50.8%), fatigue (45.9%), sore throat (41.1%), dyspnea (35.2%), and headache (34%); 25.2% patients had prolonged symptoms (≥ 21 days). Dyspnea was the most frequent (15.5%) long-term symptom. Age, co-existing diabetes, and COVID-19 infection with moderate severity, were associated with the need for hospitalization. We compared patients with COVID-19 infection who required hospital admission (n = 37) versus patients who continued in home isolation (n = 574). High neutrophil/lymphocyte ratio, transaminases, and ferritin significantly correlated with the need for hospitalization. 18.9% of the patients who required hospital admission had diabetes. Multivariate analysis described age and diabetes as independent predictors of disease severity. Age and high neutrophil/lymphocyte ratio were independent predictors of hospital admission. Telemedicine is effective in-home management of mild/moderate COVID-19 patients, which may ease the pressure on the healthcare system, even beyond the pandemic.