Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): a case-control study

Development and validation of a prediction model for mortality in critically ill COVID-19 patients

Background

Early prediction of prognosis may help early treatment measures to reduce mortality in critically ill coronavirus disease (COVID-19) patients. The study aimed to develop a mortality prediction model for critically ill COVID-19 patients.

Methods

This retrospective study analyzed the clinical data of critically ill COVID-19 patients in an intensive care unit between April and June 2022. Propensity matching scores were used to reduce the effect of confounding factors. A predictive model was built using logistic regression analysis and visualized using a nomogram. Calibration and receiver operating characteristic (ROC) curves were used to estimate the accuracy and predictive value of the model. Decision curve analysis (DCA) was used to examine the value of the model for clinical interventions.

Results

In total, 137 critically ill COVID-19 patients were enrolled; 84 survived, and 53 died. Univariate and multivariate logistic regression analyses revealed that aspartate aminotransferase (AST), creatinine, and myoglobin levels were independent prognostic factors. We constructed logistic regression prediction models using the seven least absolute shrinkage and selection operator regression-selected variables (hematocrit, red blood cell distribution width-standard deviation, procalcitonin, AST, creatinine, potassium, and myoglobin; Model 1) and three independent factor variables (Model 2). The calibration curves suggested that the actual predictions of the two models were similar to the ideal predictions. The ROC curve indicated that both models had good predictive power, and Model 1 had better predictive power than Model 2. The DCA results suggested that the model intervention was beneficial to patients and patients benefited more from Model 1 than from Model 2.

Conclusion

The predictive model constructed using characteristic variables screened using LASSO regression can accurately predict the prognosis of critically ill COVID-19 patients. This model can assist clinicians in implementing early interventions. External validation by prospective large-sample studies is required.

Prevalence of SARS-CoV-2 virus in saliva, stool, and urine samples of COVID-19 patients in Bihar, India

Introduction. The coronavirus illness caused by SARS-CoV-2 can cause multiple organ involvement, with varying degrees of severity. Besides inhalation as a route for transmission, feco-oral has also been proposed. Its transmission to sewage systems is a growing public health issue. Objective. To detect SARS-CoV-2 RNA in non-respiratory samples (saliva, urine, and stool) collected from COVID-19 cases, in Bihar. Methods. This cross-sectional observational study was conducted from January 2021 to March 2022 on human non-respiratory samples. A total of 345 samples including saliva (116), stool (97), and urine (132) were collected from 143 COVID-19 cases. Samples were analysed for SARS-CoV-2 by multiplex RT-PCR targeted against E, ORF 1ab, and RdRp genes. Results. In this study, out of 143 cases, a total of 107 (74.8 %) were positive for SARS-CoV-2 RNA in at least one of the non-respiratory samples. Conclusion. There is a high prevalence of SARS-CoV-2 virus in non-respiratory samples.

Exploring the impact of recent COVID-19 infection on perfusion and functional parameters derived from gated myocardial perfusion imaging in patients undergoing evaluation for coronary artery disease

OBJECTIVE

This study seeks to evaluate how recent COVID-19 infection affects myocardial perfusion and functional parameters derived from gated myocardial perfusion imaging in patients undergoing evaluation for coronary artery disease. The goal is to enhance our understanding of COVID-19's influence on the cardiovascular system.

METHOD

Conducted at Farshchian Heart Hospital from 2022 to 2023, this case-control study enrolled patients suspected of coronary artery disease, stratified into two groups: those with confirmed COVID-19 infection within the past 6 months (study group) and those without prior COVID-19 infection (control group). Employing a 2-day protocol, stress testing and gated SPECT MPI were performed. Statistical analysis included descriptive statistics, Chi-square test, Student's t test, and Mann-Whitney U test.

RESULT

Among the 86 patients included, 43 were in each group. Significantly higher summed stress core and summed difference score values were observed in the study group compared to the control group (p < 0.05). In addition, the study group exhibited significantly altered global left ventricular ejection fraction, end-diastolic volume, and end-systolic volume (p < 0.05). Non-perfusion findings, including transient ischemic dilation and transient right ventricular visualization, were more prevalent in the study group.

CONCLUSION

Recent COVID-19 infection is associated with impaired myocardial perfusion and altered functional parameters as detected by MPI. These findings underscore the intricate interplay between COVID-19 and cardiovascular health, emphasizing the importance of comprehensive evaluation and management strategies to address cardiac complications in affected individuals. Further research is warranted to elucidate the underlying mechanisms and optimize patient care in the context of COVID-19-associated cardiovascular manifestations.

Joint modeling of longitudinal and competing risks for assessing blood oxygen saturation and its association with survival outcomes in COVID-19 patients

BACKGROUND

The objective of the present study is to evaluate the association between longitudinal and survival outcomes in the presence of competing risk events. To illustrate the application of joint modeling in clinical research, we assessed the blood oxygen saturation (SPO2) and its association with survival outcomes in coronavirus disease (COVID-19).

MATERIALS AND METHODS

In this prospective cohort study, we followed 300 COVID-19 patients, who were diagnosed with severe COVID-19 in the Rohani Hospital in Babol, the north of Iran from October 22, 2020 to March 5, 2021, where death was the event of interest, surviving was the competing risk event and SPO2 was the longitudinal outcome. Joint modeling analyses were compared to separate analyses for these data.

RESULT

The estimation of the association parameter in the joint modeling verified the association between longitudinal outcome SPO2 with survival outcome of death (Hazard Ratio (HR) = 0.33, P = 0.001) and the competing risk outcome of surviving (HR = 4.18, P < 0.001). Based on the joint modeling, longitudinal outcome (SPO2) decreased in hypertension patients (β = -0.28, P = 0.581) and increased in those with a high level of SPO2 on admission (β = 0.75, P = 0.03). Also, in the survival submodel in the joint model, the risk of death survival outcome increased in patients with diabetes comorbidity (HR = 4.38, P = 0.026).

CONCLUSION

The association between longitudinal measurements of SPO2 and survival outcomes of COVID-19 confirms that SPO2 is an important indicator in this disease. Thus, the application of this joint model can provide useful clinical evidence in the different areas of medical sciences.

Predictive value of C-reactive protein for disease severity and survival in COVID-19 patients: a systematic review and meta-analysis

Coronavirus disease 2019 (COVID-19) is an infectious disease that can develop multiple complications and even be life-threatening. The aim of this study is to summarize current evidence of C-reactive protein's (CRP) predictive value for disease severity and survival of COVID-19 patients, focusing on curing patients and reducing the risk of death. We systematically searched related studies from four large databases: Web of Science, PubMed, China National Knowledge Infrastructure (CNKI), and Wanfang Database, all published between December 2019 and June 2021. Then, we implemented meta-analysis using random-effects models through STATA 15.1 and Review Manager 5.3. We also implemented sensitivity analysis and used funnel plots to check publication bias. From the systematic search of the four databases, we were able to identify 18 studies containing a total of 3052 patients. Meta-analysis results showed that 1) CRP levels were lower in non-severe patients than in severe patients (Standardized Mean Difference (SMD) =  - 0.87 mg/L, 95% Confidence Interval (CI) = [ - 1.27, - 0.47], p < 0.001); 2) CRP levels were lower in non-intensive care unit (ICU) patients than in ICU patients (SMD = - 1.39 mg/L, 95% CI = [- 1.68, - 1.11], p < 0.001), and 3) CRP levels were lower in survivors than in non-survivors (SMD =- 1.32 mg/L, 95% CI = [- 1.95, - 0.69], p < 0.001). Sensitivity analysis showed these results were stable. Funnel plots indicated no publication bias. The CRP level may timely reflect disease severity and predict survival of COVID-19 patients and may be worthy of further popularization and application in clinic practice.

Clinical characteristics and predictors for in-hospital mortality in adult COVID-19 patients: A retrospective single center cohort study in Vilnius, Lithuania

BACKGROUND

The COVID-19 infection had spread worldwide causing many deaths. Mortality rates and patients' characteristics varied within and between countries, making it important to understand the peculiarities of different populations. The aim of this study was to identify the main predictors associated with in-hospital mortality due to COVID-19 in Vilnius, Lithuania.

MATERIALS AND METHODS

This was a retrospective observational cohort study conducted at Vilnius University Hospital Santaros Clinics, Lithuania. The study included SARS-CoV-2 positive patients aged over 18 years and hospitalized between March 2020 and May 2021. Depersonalized data were retrieved from electronic medical records. The predictive values of laboratory parameters were evaluated using ROC analysis. Multivariable binary logistic regression was performed to reveal predictors of in-hospital mortality due to COVID-19.

RESULTS

Among 2794 patients, 54.4% were male, the age median was 59 years (IQR 48-70), 47.4% had at least one comorbidity. The most common comorbidities were arterial hypertension (36.9%) and diabetes mellitus (13.7%). Overall, 12.7% of patients died. Multivariable regression revealed that age (OR 1.04, 95%CI 1.02-1.06), congestive heart failure (OR 3.06, 95%CI 1.96-4.77), obesity (OR 3.90, 95%CI 2.12-7.16), COPD (OR 2.92, 95%CI 1.12-7.60), previous stroke (OR 5.80, 95%CI 2.07-16.21), urea >7.01 mmol/l (OR 2.32, 95%CI 1.47-3.67), AST/ALT >1.49 (OR 1.54, 95%CI 1.08-2.21), LDH >452.5 U/l (OR 2.60, 95%CI 1.74-3.88), CRP >92.68 mg/l (OR 1.58, 95%CI 1.06-2.35), IL-6 >69.55 ng/l (OR 1.62, 95%CI 1.10-2.40), and troponin I >18.95 ng/l (OR 2.04, 95%CI 1.38-3.02), were associated with increased risk for in-hospital mortality in COVID-19 patients.

CONCLUSIONS

Age, congestive heart failure, obesity, COPD, prior stroke, and increased concentration of urea, LDH, CRP, IL-6, troponin I, ALT to AST ratio were identified to be the predictors for in-hospital mortality of COVID-19 patients.

Factors Affecting Hospitalization Length and in-Hospital Death Due to COVID-19 Infection in Saudi Arabia: A Single-Center Retrospective Analysis

Background

The emerging COVID-19 coronavirus disease has widely spread, causing a serious worldwide pandemic. Disease severity and mortality risk can be predicted using an analysis of COVID-19 clinical characteristics. Finding out what influences patients' hospitalization length and in-hospital mortality is crucial for decision-making and planning for emergencies. The goal of this study is to identify the factors that influence hospital stay length and in-hospital death due to COVID-19 infection.

Methods

This cross-sectional study was conducted from August to October 2020 and included 630 patients with a confirmed diagnosis of COVID-19 infection. Using odds ratios (OR) and 95% confidence intervals (CI), a multivariable logistic regression model was used to assess the variables that are linked to longer hospital stays and in-hospital deaths.

Results

Most patients were male (64.3%), and most were older than 40 years (81.4%). The mean length of hospital stay (LoHS) was 10.4±11.6 days. The overall death rate among these COVID-19 cases was 14.3%. Non-survivors were older, had more comorbidities, had prolonged LoHS with increased ICU admission rates and mechanical ventilation usage, and had a more severe condition than survivors. ICU admission, low serum albumin, and elevated LDH levels were associated with longer LoHS, while ICU admission, DM, and respiratory diseases as comorbidities, total leukocytic count, and serum albumin were predictors of mortality.

Conclusion

Longer LoHS due to COVID-19 infection was linked to ICU admission, low serum albumin, and elevated LDH levels, while the independent predictors of in-hospital death were ICU admission, DM, and respiratory diseases as comorbidities, total leukocytic count, and serum albumin.

Clinical Characteristics and Outcomes of Vaccinated VS Non-Vaccinated Critically Ill COVID-19 Patients: Retrospective Observation Study

Objective

We aim to identify the clinical characteristics and outcome of vaccine breakthrough infection in critically ill COVID-19 patients and to compare the clinical course of disease between vaccinated and non-vaccinated patients.

Methods

A retrospective review of all adult patients aged ≥18 years admitted to the ICU in King Fahd Hospital of the University in Saudi Arabia with positive COVID-19 RT-PCR test between the period of January 1st to August 31st, 2021, were included. The recruited patients were grouped in to "vaccinated and non-vaccinated group" based on their immunization status. The demographic data, co-morbidities, modality of oxygen support, ICU length of stay (ICU LOS) and mortality were collected and analyzed.

Results

A total of 167 patients were included. Seventy-two patients (43%) were vaccinated. Cardiovascular diseases were higher among the vaccinated group (33.3% vs 12.6%, p value <0.001). Requirements of Non-invasive ventilation was significantly lower in vaccinated group compared to non-vaccinated group (73.6% vs 91.6%, p value <0.011). The rates of intubation were similar between both groups. The total intubation days was longer in non-vaccinated patients compared to vaccinated patients and the median duration of intubation was 8 days vs 2 days, respectively (p value 0.027). In subgroup analysis, the P/F ratio was significantly higher in patients who received two doses of vaccine compared to single dose (p value <0.002).

Conclusion

In critically ill COVID-19 patients, the vaccinated group has significantly less need for Non-invasive ventilation, fewer intubation days and less hypoxia compared to non-vaccinated patients. We recommend more policies and public education nationwide and worldwide to encourage vaccination and raise awareness of the general population.

Impact of hyperchloremia on inflammatory markers, serum creatinine, hemoglobin, and outcome in critically ill patients with COVID-19 infection

Hyperchloremia has negative consequences, such as increased proinflammatory mediators, renal dysfunction, and mortality in patients with septic shock. However, data on the effects of hyperchloremia on COVID-19 infections are scarce. The study aimed to investigate the effects of hyperchloremia on inflammatory markers, serum creatinine, hemoglobin levels, and outcomes in critically ill COVID-19 patients. A retrospective review of all adult patients admitted to the ICU at King Fahd University Hospital with a moderate to severe COVID-19 infection from January 2020 to August 2021 was performed. Serum chloride levels, ferritin, lactate dehydrogenase (LDH), C-reactive protein (CRP), creatinine, and hemoglobin levels were collected on the first and third days of ICU admission. Demographic data, oxygen support modality, ICU length of stay (ICU LOS), renal replacement therapy (RRT), and deaths were collected. Of 420 patients, 255 were included; 97 (38%) had hyperchloremia, while 158 (62%) did not. Hyperchloremic patients had a higher percentage of increases in ferritin (54.6%), CRP (6.2%), and LDH (15.5%) between the first and third days of admission, compared to non-hyperchloremic patients (43.7%, 6.3%, and 5.7%, respectively). The decrease in hemoglobin levels was similar in both groups (p=0.103). There was a significant association between hyperchloremia and an increase in serum creatinine (p<0.0001). Sixty-six (68%) patients required endotracheal intubation in the hyperchloremic group (p=0.003). The mortality rate was significant in the hyperchloremic cohort (p=<0.0001). Hyperchloremia was significantly associated with increased risks of kidney injury, endotracheal intubation, and death. However, hyperchloremia was not associated with increased ferritin, CRP, or hemoglobin decreases in critically ill COVID-19 patients.

Exploration of Sex and Age-Based Associations in Clinical Characteristics, Predictors of Severity, and Duration of Stay among COVID-19 Patients at the University Hospital of Saudi Arabia

COVID-19 infection has a spectrum of variable clinical severity between populations because of their characteristic demographic features, co-morbidities, and immune system reactions. This pandemic tested the healthcare system's preparedness, which depends on predictors of severity and factors related to the duration of hospital stays. Therefore, we carried out a single-center, retrospective cohort study in a tertiary academic hospital to investigate these clinical features and predictors of severe disease and study the different factors that affect hospital stay. We utilized medical records from March 2020 to July 2021, which included 443 confirmed (positive RT-PCR) cases. The data were explained using descriptive statistics and analyzed via multivariate models. Among the patients, 65.4% were female and 34.5% were male, with a mean age of 45.7 years (SD ± 17.2). We presented seven age groups with ranges of 10 years and noticed that patients aged 30-39 years old comprised 23.02% of the records, while patients aged 70 and above comprised 10%. Nearly 47% were diagnosed as having mild, 25% as moderate, 18% as asymptomatic, and 11% as having a severe case of COVID-19 disease. Diabetes was the most common co-morbidity factor in 27.6% of patients, followed by hypertension (26.4%). Our population's predictors of severity included pneumonia, identified on a chest X-ray, and co-morbid conditions such as cardiovascular disease, stroke, ICU stay, and mechanical ventilation. The median length of hospital stay was six days. It was significantly longer in patients with a severe disease and who were administered systemic intravenous steroids. An empirical assessment of various clinical parameters could assist in effectively measuring the disease progression and follow-up with patients.

Inflammation as Prognostic Hallmark of Clinical Outcome in Patients with SARS-CoV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is often characterized by a life-threatening interstitial pneumonia requiring hospitalization. The aim of this retrospective cohort study is to identify hallmarks of in-hospital mortality in patients affected by Coronavirus Disease 19 (COVID-19). A total of 150 patients admitted for COVID-19 from March to June 2021 to "F. Perinei" Murgia Hospital in Altamura, Italy, were divided into survivors (n = 100) and non-survivors groups (n = 50). Blood counts, inflammation-related biomarkers and lymphocyte subsets were analyzed into two groups in the first 24 h after admission and compared by Student's t-test. A multivariable logistic analysis was performed to identify independent risk factors associated with in-hospital mortality. Total lymphocyte count and CD3⁺ and CD4⁺ CD8⁺ T lymphocyte subsets were significantly lower in non-survivors. Serum levels of interleukin-6 (IL-6), lactate dehydrogenase (LDH), C-reactive protein (CRP) and procalcitonin (PCT) were significantly higher in non-survivors. Age > 65 years and presence of comorbidities were identified as independent risk factors associated with in-hospital mortality, while IL-6 and LDH showed a borderline significance. According to our results, markers of inflammation and lymphocytopenia predict in-hospital mortality in COVID-19.

Effectiveness of mid-regional pro-adrenomedullin, compared to other biomarkers (including lymphocyte subpopulations and immunoglobulins), as a prognostic biomarker in COVID-19 critically ill patients: New evidence from a 15-month observational prospective study

Background

Mid-regional pro-adrenomedullin (MR-proADM), an endothelium-related peptide, is a predictor of death and multi-organ failure in respiratory infections and sepsis and seems to be effective in identifying COVID-19 severe forms. The study aims to evaluate the effectiveness of MR-proADM in comparison to routine inflammatory biomarkers, lymphocyte subpopulations, and immunoglobulin (Ig) at an intensive care unit (ICU) admission and over time in predicting mortality in patients with severe COVID-19.

Methods

All adult patients with COVID-19 pneumonia admitted between March 2020 and June 2021 in the ICUs of a university hospital in Italy were enrolled. MR-proADM, lymphocyte subpopulations, Ig, and routine laboratory tests were measured within 48 h and on days 3 and 7. The log-rank test was used to compare survival curves with MR-proADM cutoff value of >1.5 nmol/L. Predictive ability was compared using the area under the curve (AUC) and 95% confidence interval (CI) of different receiver-operating characteristic curves.

Results

A total of 209 patients, with high clinical severity [SOFA 7, IQR 4-9; SAPS II 52, IQR 41-59; median viral pneumonia mortality score (MuLBSTA)-11, IQR 9-13] were enrolled. ICU and overall mortality were 55.5 and 60.8%, respectively. Procalcitonin, lactate dehydrogenase, D-dimer, the N-terminal prohormone of brain natriuretic peptide, myoglobin, troponin, neutrophil count, lymphocyte count, and natural killer lymphocyte count were significantly different between survivors and non-survivors, while lymphocyte subpopulations and Ig were not different in the two groups. MR-proADM was significantly higher in non-survivors (1.17 ± 0.73 vs. 2.31 ± 2.63, p < 0.0001). A value of >1.5 nmol/L was an independent risk factor for mortality at day 28 [odds ratio of 1.9 (95% CI: 1.220-3.060)] after adjusting for age, lactate at admission, SOFA, MuLBSTA, superinfections, cardiovascular disease, and respiratory disease. On days 3 and 7 of the ICU stay, the MR-proADM trend evaluated within 48 h of admission maintained a correlation with mortality (p < 0.0001). Compared to all other biomarkers considered, the MR-proADM value within 48 h had the best accuracy in predicting mortality at day 28 [AUC = 0.695 (95% CI: 0.624-0.759)].

Conclusion

MR-proADM seems to be the best biomarker for the stratification of mortality risk in critically ill patients with COVID-19. The Ig levels and lymphocyte subpopulations (except for natural killers) seem not to be correlated with mortality. Larger, multicentric studies are needed to confirm these findings.

Hospitalised COVID-19 outcomes are predicted by hypoxaemia and pneumonia phenotype irrespective of the timing of their emergence

Despite the known clinical importance of hypoxemia and pneumonia, there is a paucity of evidence for these variables with respect to risk of mortality and short-term outcomes among those hospitalised with COVID-19.

OBJECTIVE

Describe the prevalence and clinical course of patients hospitalised with COVID-19 based on oxygenation and pneumonia status at presentation and determine the incidence of emergent hypoxaemia or radiographic pneumonia during admission.

METHODS

A retrospective study was conducted using a Canadian regional registry. Patients were stratified according to hypoxaemia/pneumonia phenotype and prevalence. Clinical parameters were compared between phenotypes using χ² and one-way Analysis of variance (ANOVA). Cox analysis estimated adjusted Hazard Ratios (HR) for associations between disease outcomes and phenotypes.

RESULTS

At emergency department (ED) admission, the prevalence of pneumonia and hypoxaemia was 43% and 50%, respectively, and when stratified to phenotypes: 28.2% hypoxaemia⁺/pneumonia⁺, 22.2% hypoxaemia⁺/pneumonia^-, 14.5% hypoxaemia^-/pneumonia⁺ and 35.1% hypoxaemia^-/pneumonia^-. Mortality was 31.1% in the hypoxaemia⁺/pneumonia^- group and 26.3% in the hypoxaemia⁺/pneumonia⁺ group. Hypoxaemia with pneumonia and without pneumonia predicted higher probability of death. Hypoxaemia either <24 hours or ≥24 hours after hospitalisation predicted higher mortality and need for home oxygen compared with those without hypoxaemia. Patients with early hypoxaemia had higher probability of Intensive care unit (ICU) admission compared with those with late hypoxaemia.

CONCLUSION

Mortality in COVID-19 infection is predicted by hypoxaemia with or without pneumonia and was greatest in patients who initially presented with hypoxaemia. The emergence of hypoxaemia was predicted by radiographic pneumonia. Patients with early and emergent hypoxaemia had similar mortality but were less likely to be admitted to ICU. There may be delayed identification of hypoxaemia, which prevents timely escalation of care.

Comparison Between Physiological Scores SIPF, CURB-65, and APACHE II as Predictors of Prognosis and Mortality in Hospitalized Patients with COVID-19 Pneumonia: A Multicenter Study, Saudi Arabia

Background

A coronavirus pandemic (COVID-19) is associated with catastrophic effects on the world with high morbidity and mortality. We aimed to evaluate the accuracy of physiological shock index (SIPF) (shock index and hypoxemia), CURB -65, acute physiology, and chronic health assessment II (APACHE II) as predictors of prognosis and in-hospital mortality in patients with COVID-19 pneumonia.

Methods

In Saudi Arabia, a multicenter retrospective study was conducted on hospitalized adult patients confirmed to have COVID-19 pneumonia. Information needed to calculate SIPF, CURB-65, and APACHE II scores were obtained from medical records within 24 hours of admission.

Results

The study included 1131 COVID-19 patients who met the inclusion criteria. They were divided into two groups: (A) the ICU group (n=340; 30.1%) and (B) the ward group (n=791; 69.9%). The most common concomitant diseases of patients at initial ICU admission were hypertension (71.5%) and diabetes (62.4%), and most of them were men (63.8%). The overall mortality was 18.7%, and the mortality rate was higher in the ICU group than in the ward group (39.4% vs 9.6%; p < 0.001). The SIPF score showed a significantly higher ability to predict both ICU admission and mortality in patients with COVID-19 pneumonia compared with APACHE II and CURB -65; (AUC 0.89 vs 0.87; p < 0.001) and (AUC 0.89 vs 0.84; p < 0.001) for ICU admission and (AUC 0.90 vs 0.65; p < 0.001) and (AUC 0.90 vs 0.80; p < 0.001) for mortality, respectively.

Conclusion

The ability of the SIPF score to predict ICU admission and mortality in COVID-19 pneumonia is higher than that of APACHE II and CURB-65. The overall mortality was 18.7%, and the mortality rate was higher in the ICU group than in the ward group (39.4% vs 9.6%; p < 0.001).

Association of Clinical and Laboratory Findings in COVID-19 Patients with Thromboembolic Complications

Background: COVID-19 is associated with dangerous thromboembolic complications, such as stroke, heart attack, pulmonary embolism, and arterial and venous thromboembolism (VTE). Early diagnosis and even prediction of thromboembolic complications using biomarkers could facilitate the treatment and decrease the mortality rate. Objectives: This study evaluated and compared the clinical and laboratory findings of COVID-19 patients with thrombotic events with other COVID-19 patients. Methods: A total of 114 confirmed COVID-19 patients referred to Taleghani Hospital, Tehran, Iran, between February and September 2020 were included in this cross-sectional study. Those with a history of thromboembolic disease were excluded. The laboratory data, including the levels of lactate dehydrogenase (LDH), D-dimer, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and counts of lymphocyte and neutrophil, along with clinical findings (such as oxygen saturation and lung involvement percentage), were retrospectively collected from the patients’ clinical files. The incidence of thrombotic events was evaluated in patients. Results: The prevalence of thrombosis in the right and left main pulmonary arteries, right and left sub-segmental pulmonary arteries, and right and left deep veins was 2.7%, 3.5%, 7%, 7.9%, 4.4%, and 1.8% of all patients, respectively. The results showed that thromboembolic complications were significantly associated with mortality (P < 0.001). Besides, it was found that LDH (P < 0.001) and neutrophil (P = 0.002) levels in thromboembolic COVID-19 patients were respectively higher and lower than those without thromboembolic manifestations. Conclusions: High LDH and neutropenia might serve as biomarkers for thromboembolism in COVID-19 patients.

CT-based Pathological Lung Opacities Volume as a Predictor of Critical Illness and Inflammatory Response Severity in Patients with COVID-19☆☆☆

Objective

The aim of the study was to assess the impact of CT-based lung pathological opacities volume on critical illness and inflammatory response severity of patients with COVID-19.

Methods

A retrospective, single center, single arm study was performed over a 30-day period. In total, 138 patients (85.2%) met inclusion criteria. All patients were evaluated with non-contrast enhanced chest CT scan at hospital admission. CT-based lung segmentation was performed to calculate pathological lung opacities volume (LOV). At baseline, complete blood count (CBC) and inflammation response biomarkers were obtained. The primary endpoint of the study was the occurrence of critical illness, as defined as, the need of mechanical ventilation and/or ICU admission. Mann-Whitney U test was performed for univariate analysis. Logistic regression analysis was performed to determine independent predictors of critical illness. Spearman analysis was performed to assess the correlation between inflammatory response biomarkers serum concentrations and LOV.

Results

Median LOV was 28.64% (interquartile range [IQR], 6.33-47.22%). Correlation analysis demonstrated that LOV was correlated with higher levels of D-dimer (r=0.51, p<0.01), procalcitonin (r=0.47, p<0.01) and IL6 (r=0.48, p<0.01). Critical illness occurred in 51 patients (37%). Univariate analysis demonstrated that inflammatory response biomarkers and LOV were associated with critical illness (p<0.05). However, multivariate analysis demonstrated that only D-dimer and LOV were independent predictors of critical illness. Furthermore, a ROC analysis demonstrated that a LOV equal or greater than 60% had a sensitivity of 82.1% and specificity of 70.2% to determine critical illness with an odds ratio of 19.4 (95% CI, 4.2-88.9).

Conclusion

Critical illness may occur in up to 37% of the patients with COVID-19. Among patients with critical illness, higher levels of inflammatory response biomarkers with larger LOVs were observed. Furthermore, multivariate analysis demonstrated that pathological lung opacities volume was an independent predictor of critical illness. In fact, patients with a pathological lung opacities volume equal or greater than 60% had 19.4-fold increased risk of critical illness.

Role of biological markers and CT severity score in predicting mortality in patients with COVID‑19: An observational retrospective study

COVID-19 pandemic is a continuing ongoing emergency of public concern. Early identification of markers associated with disease severity and mortality can lead to a prompter therapeutic approach. The present study conducted a multivariate analysis of different markers associated with mortality in order to establish their predictive role. Confirmed cases of 697 patients were examined. Demographic data, clinical symptoms and comorbidities were evaluated. Laboratory and imaging severity scores were reviewed. A total of 133 (19.1%) out of 697 patients succumbed during hospitalization. Obesity was the most common comorbidity, followed by hypertension, diabetes, coronary heart disease and chronic kidney disease. Compared with the survivor patients, non-survivors had a higher prevalence of diabetes, chronic kidney disease and coronary heart disease, as well as higher values of laboratory markers such as neutrophil-lymphocyte ratio (NLR), D-dimer, procalcitonin, IL-6 and C Reactive protein (CRP) and respectively high values of imaging severity scores. Multivariate regression analysis showed that high values of the proposed markers and chest computerized tomography (CT) severity imaging score were predictive for in hospital death: NLR [hazard ratio (HR): 3.127 confidence interval (CI) 95: 2.137-4.576]; D-dimer [HR: 6.223 (CI 95:3.809-10.167)]; procalcitonin [HR: 4.414 (CI 95:2.804-6.948)]; IL-6 [HR: 3.344 (CI 95:1.423-7.855)]; CRP [HR:2.997 (CI 95:1.940-4.630)]; and CT severity score [HR: 3.068 (CI 95:1.777-5.299)]. Laboratory markers and imaging severity scores could be used to stratify mortality risk in COVID-19 patients.

Admission Predictors of Mortality in Hospitalized COVID-19 Patients-A Serbian Cohort Study

Background: Early prediction of COVID-19 patients’ mortality risk may be beneficial in adequate triage and risk assessment. Therefore, we aimed to single out the independent morality predictors of hospitalized COVID-19 patients among parameters available on hospital admission. Methods: An observational, retrospective−prospective cohort study was conducted on 703 consecutive COVID-19 patients hospitalized in the University Clinical Center Kragujevac between September and December 2021. Patients were followed during the hospitalization, and in-hospital mortality was observed as a primary end-point. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis, including complete blood cell count, inflammation biomarkers and other biochemistry, coagulation parameters, and cardiac biomarkers. Socio-demographic and medical history data were obtained using patients’ medical records. Results: The overall prevalence of mortality was 28.4% (n = 199). After performing multiple regression analysis on 20 parameters, according to the initial univariate analysis, only four independent variables gave statistically significant contributions to the model: SaO2 < 88.5 % (aOR 3.075), IL-6 > 74.6 pg/mL (aOR 2.389), LDH > 804.5 U/L (aOR 2.069) and age > 69.5 years (aOR 1.786). The C-index of the predicted probability calculated using this multivariate logistic model was 0.740 (p < 0.001). Conclusions: Parameters available on hospital admission can be beneficial in predicting COVID-19 mortality.

Impact of Heat Inactivation of Blood Samples on Therapeutic Drug Monitoring of 5 Second-Generation Antipsychotics and Their Metabolites

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 outbreak has been classified as a pandemic. Because many coronaviruses are heat sensitive, heat inactivation of patient samples at 56°C before testing reduces the risk of transmission. The aim of this study is to assess the impact of heat inactivation of patient blood samples on plasma concentrations of 5 second-generation antipsychotics and their metabolites.

METHODS

Blood samples were collected during routine clinical therapeutic drug monitoring examination between April 3, 2021, and April 19, 2021. Samples were divided into 2 groups: group A, noninactivated raw sample, and group B, inactivated samples. Inactivation was performed by a 30-minute incubation at 56°C. The levels of the 5 drugs and their metabolites before and after sample heat inactivation were measured using liquid chromatography-tandem mass spectrometry and compared. Furthermore, correlation and Bland-Altman analyses were conducted.

RESULTS

No statistically significant difference was observed between the levels of the 5 drugs and their metabolites (ie, risperidone, 9-OH-risperidone, aripiprazole, dehydroaripiprazole, olanzapine, quetiapine, norquetiapine, clozapine, and norclozapine) in the noninactivated group A and the inactivated group B ( P > 0.05). Each drug's concentration values in inactivated and noninactivated treatments correlated (Spearman rs > 0.98; P < 0.001). The results of the noninactivated treatment methods and samples alone showed good consistency via Bland-Altman analysis.

CONCLUSIONS

Blood sample heat inactivation had no significant effect on the therapeutic drug monitoring of 5 second-generation antipsychotics and their metabolites. This inactivated treatment method should be recommended to effectively protect laboratory staff from virus contamination.

Correlates of In-Hospital COVID-19 Deaths: A Competing Risks Survival Time Analysis of Retrospective Mortality Data

INTRODUCTION

Several aspects of the coronavirus disease 2019 (COVID-19) pandemic remain ambiguous, including its transmission, severity, geographic, and racial differences in mortality. These variations merit elaboration of local patterns to inform wider national policies.

METHODS

In a retrospective analysis, data of patients treated at a dedicated COVID hospital with moderate and severe illness during 8 wk of the pandemic were reviewed with attention to mortality in a competing risks framework.

RESULTS

A total of 1147 patients were hospitalized, and 312 (27.2%) died in hospital. Those who died were older (56.5 vs 47.6 y; P < 0.0001). Of these, 885 (77.2%) had tested positive on reverse transcriptase polymerase chain reaction (RT-PCR), with 219 (24.2%) deaths (incidence rate, 1.9 per 100 person-days). Median time from onset of symptoms to death was 11 days. A competing risks analysis for in-hospital death revealed an adjusted cause-specific hazard ratio of 1.4 for each decade increase in age.

CONCLUSIONS

This retrospective analysis provides broad patterns of disease presentation and mortality. Even COVID test-negative patients will receive treatment at dedicated facilities, and 33% presenting cases may die within the first 72 h, most with comorbid illness. This should be considered while planning distribution of services for effective health-care delivery.

COVID-19 pnömonili hastalarda yaşa bağımlı bir prognostik faktör olarak CRP/albümin oranı

Amaç: Çalışmamızın amacı, Covid-19 pnömonisinde C-reaktif protein/albüminin yaşa bağlı bir belirteç olup olmadığını belirlemekti. Gereç ve Yöntem: Covid-19 pnömonisi olan 296 (166 erkek/ 130 kadın) hasta üzerinde retrospektif bir araştırma yaptık. Katılımcılar

Lymphocyte–C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission

In this study, we aimed to explore whether lymphocyte–C-reactive protein ratio (LCR) can differentiate disease severity of coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to hospital and intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all the above indicators were compared among the groups. Multiple clinical parameters, including LYMPH, CRP, and LCR, showed significant differences among the groups. The related factors to classify COVID-19 patients into moderate, severe, and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, the number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe, and critical groups was 0.176. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 1,780.7050 and 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included the number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under the ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 571.2200 and 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

Procalcitonin as a predictive marker in COVID-19: A systematic review and meta-analysis

Background

Coronavirus disease 2019 has emerged as a global pandemic causing millions of critical cases and deaths. Early identification of at-risk patients is crucial for planning triage and treatment strategies.

Methods and findings

We performed this systematic review and meta-analysis to determine the pooled prognostic significance of procalcitonin in predicting mortality and severity in patients with COVID-19 using a robust methodology and clear clinical implications.

Design

We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Cochrane Handbook for Systematic Reviews of Interventions guidelines. We included thirty-two prospective and retrospective cohort studies involving 13,154 patients.

Results

The diagnostic odds ratio of procalcitonin for predicting mortality were estimated to be 11 (95% CI: 7 to 17) with sensitivity, specificity, and summary area under the curveof 0.83 (95% CI: 0.70 to 0.91), 0.69 (95% CI: 0.58 to 0.79), and 0.83 (95% CI: 0.79 to 0.86) respectively. While for identifying severe cases of COVID-19, the odds ratio was 8.0 (95% CI 5.0 to 12.0) with sensitivity, specificity, and summary area under the curve of 0.73 (95% CI 0.67 to 0.78), 0.74 (0.66 to 0.81), and 0.78 (95% CI 0.74 to 0.82) respectively.

Conclusion

Procalcitonin has good discriminatory power for predicting mortality and disease severity in COVID-19 patients. Therefore, procalcitonin measurement may help identify potentially severe cases and thus decrease mortality by offering early aggressive treatment.

Assessment of hypertension and other factors associated with the severity of disease in COVID-19 pneumonia, Addis Ababa, Ethiopia: A case-control study

BACKGROUND

Various reports suggested that pre-existing medical illnesses, including hypertension and other demographic, clinical, and laboratory factors, could pose an increased risk of disease severity and mortality among COVID-19 patients. This study aimed to assess the relation of hypertension and other factors to the severity of COVID-19 pneumonia in patients discharged from Eka Kotebe Hospital in June-September, 2020.

METHODS

This is a single-center case-control study of 265 adult patients discharged alive or dead, 75 with a course of severe COVID-19 for the cases arm and 190 with the non-severe disease for the control arm. Three age and sex-matched controls were selected randomly for each patient on the case arm. Chi-square, multivariable binary logistic regression, and odds ratio (OR) with a 95% confidence interval was used to assess the association between the various factors and the severity of the disease. A p-value of <0.05 is considered statistically significant.

RESULTS

Of the 265 study participants, 80% were male. The median age was 43 IQR(36-60) years. Both arms had similar demographic characteristics. Hypertension was strongly associated with the severity of COVID-19 pneumonia based on effect outcome adjustment (AOR = 2.93, 95% CI 1.489, 5.783, p-value = 0.002), similarly, having diabetes mellitus (AOR = 3.17, 95% CI 1.374, 7.313, p-value<0.007), chronic cardiac disease (AOR = 4.803, 95% CI 1.238-18.636, p<0.023), and an increase in a pulse rate (AOR = 1.041, 95% CI 1.017, 1.066, p-value = 0.001) were found to have a significant association with the severity of COVID-19 pneumonia.

CONCLUSIONS

Hypertension was associated with the severity of COVID-19 pneumonia, and so were diabetes mellitus, chronic cardiac disease, and an increase in pulse rate.

Comparison of clinical outcomes and risk factors for COVID-19 infection in cancer patients without anticancer treatment and noncancer patients

Background

Previous studies have shown that cancer patients have higher rates of coronavirus disease 2019 (COVID-19) infection and mortality than noncancer patients. However, the differences between cancer patients undergoing regular follow-up without anticancer treatment and noncancer patients with COVID-19 have remained insufficiently investigated.

Methods

A retrospective case-control study of 52 patients with COVID-19 infection was performed with a 1:3 matched proportion of cancer patients undergoing regular follow-up without anticancer treatment and noncancer patients. The demographic characteristics, clinical data, laboratory tests, treatment, and complications of patients were collected from medical records. Chi-square tests and univariate and multivariate regressions were performed to assess the differences between these two cohorts of COVID-19 patients with and without cancer and risk factors for severe events in COVID-19 patients.

Results

Increased C-reactive protein (CRP) (>4 mg/L) (p = 0.015) and lactate dehydrogenase (LDH) (>243 IU/L) (p = 0.038) were identified as risk factors for severe events in all enrolled COVID-19 patients based on multivariate analysis, but cancer as a chronic disease (p = 1.000) was not identified as an independent risk factor for severe events in COVID-19 patients. Compared with noncancer patients, cancer patients had a significantly longer median hospitalization time (29 days vs. 19 days, p = 0.048) and a higher incidence of hypoalbuminemia complications (84.6 vs. 46.2%, p = 0.016).

Conclusions

Increased CRP and LDH were risk factors for severe events in all enrolled COVID-19 patients, and an increased incidence of hypoalbuminemia complications and longer hospitalization were noted in COVID-19 cancer patients undergoing regular follow-up without anticancer treatment compared with noncancer patients.

Goulart A, Desuó IC, Gomes G. Application of thermography to estimate respiratory rate in the emergency room: The journal Temperature toolbox

Among the vital signs collected during hospital triage, respiratory rate is an important parameter associated with physiological, pathophysiological, and emotional changes. In recent years, the importance of its verification in emergency centers due to the severe acute respiratory syndrome 2 (SARS2) pandemic has become very clear, although it is still one of the least evaluated and collected vital signs. In this context, infrared imaging has been shown to be a reliable estimator of respiratory rate, with the advantage of not requiring physical contact with patients. The objective of this study was to evaluate the potential of analyzing a sequence of thermal images as an estimator of respiratory rate in the clinical routine of an emergency room. We used an infrared thermal camera (T540, Flir Systems) to obtain the respiratory rate data of 136 patients, based on nostrils' temperature fluctuation, during the peak of the COVID-19 pandemic in Brazil and compared it with the chest incursion count method, commonly employed in the emergency screening procedures. We found a good agreement between both methods, with Bland-Altman limits of agreement ranging from -4 to 4 min-1, no proportional bias (R2 = 0.021, p = 0.095), and a strong correlation between them (r = 0.95, p < 0.001). Our results suggest that infrared thermography has potential to be a good estimator of respiratory rate in the routine of an emergency room.

Does serum butyrylcholinesterase level determine the severity and mortality of COVID-19 pneumonia?: Prospective study

Background

The WHO emphasized the importance of knowing the risk factors for the severity of the disease in the COVID-19 pandemic. Our aim in this study was to determine the relationship between serum Butyrylcholinesterase (BChE) level, which is rapidly affected by inflammation, and the severity of COVID-19 pneumonia and mortality.

Methods

Patients diagnosed with COVID-19 pneumonia between March and May 2021 were included in the study. The patients were divided into two groups as severe and mild to moderate pneumonia according to the WHO's guidelines. Serum BChE levels were studied by ELISA method from the blood samples taken from the patients on the day of hospitalization. The severity of the disease and other factors affecting hospital mortality were also evaluated.

Results

147 patients with COVID-19 pneumonia were included in this study. Of these patients, 58% had severe pneumonia and 42% had mild to moderate pneumonia. The BChE level was median 13 (IQR: 11.2–21.5)ng/ml in patients with severe COVID-19 pneumonia and median 20 (IQR: 10–35.7)ng/ml in patients with mild to moderate pneumonia (p: 0.001). Hospital with mortality rate was higher in patients with low BChE levels. However, statistically, BChE hasn't associated mortality in COVID-19 pneumonia [OR 1.002 (0.957–1.049) p: 0.490]. CRP, procalcitonin, lactate, and D-dimer levels were associated mortality in COVID-19 pneumonia.

Conclusion

Being not statistically significant, the mortality rate was higher in patients with low BChE levels. BChE level is an important marker in determining the severity of COVID-19 pneumonia. Early prediction of the severity of COVID-19 pneumonia will enable early planning of the treatment process.

Multifunctional Role of S100 Protein Family in the Immune System: An Update

S100 is a broad subfamily of low-molecular weight calcium-binding proteins (9–14 kDa) with structural similarity and functional discrepancy. It is required for inflammation and cellular homeostasis, and can work extracellularly, intracellularly, or both. S100 members participate in a variety of activities in a healthy cell, including calcium storage and transport (calcium homeostasis). S100 isoforms that have previously been shown to play important roles in the immune system as alarmins (DAMPs), antimicrobial peptides, pro-inflammation stimulators, chemo-attractants, and metal scavengers during an innate immune response. Currently, during the pandemic, it was found that several members of the S100 family are implicated in the pathophysiology of COVID-19. Further, S100 family protein members were proposed to be used as a prognostic marker for COVID-19 infection identification using a nasal swab. In the present review, we compiled the vast majority of recent studies that focused on the multifunctionality of S100 proteins in the complex immune system and its associated activities. Furthermore, we shed light on the numerous molecular approaches and signaling cascades regulated by S100 proteins during immune response. In addition, we discussed the involvement of S100 protein members in abnormal defense systems during the pathogenesis of COVID-19.

COVID-19'da hastane içi mortaliteyi tahmin etmede enflamatuvar temelli parametrelerin ve MELD-XI skorunun 4C mortalite skoru ile karşılaştırılması

Purpose: In this study, we compared the roles of inflammatory parameters such as neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), C-reactive protein/lymphocyte ratio (CLR), monocyte/lymphocyte ratio (MLR), neutrophil/platelet ratio (NPR), neutrophil/monocyte ratio (NMR), CRP/albumin ratio (CAR), BUN/albumin ratio (BAR), MELD-XI score and 4C mortality score in predicting in-hospital mortality risk in COVID-19. Materials and Methods: A total of 117 patients over 18 years old with a PCR-confirmed diagnosis of COVID-19 between June 2020 and February 2021 were retrospectively included. The roles of parameters for independently predicting in-hospital mortality were determined and compared with each other using appropriate statistical methods. Results: Age, chronic kidney disease, diabetes mellitus, acute kidney injury, and length of hospital stay, urea, creatinine, LDH, AST, ferritin, D-dimer, CRP, albumin, Hb, CLR, BAR, CAR, MELD-XI score, and 4C mortality score were significantly correlated to in-hospital mortality. However, only the 4C mortality score and AST independently predicted in-hospital mortality in COVID-19 [OR 2.08 (%95 CI 1.06-2.36), for 4C mortality score, and OR 1.05 (%95 CI 1.00-1.10), for AST]. Conclusion: Unlike other mortality-related inflammatory parameters, the 4C mortality score and AST were independent and strong predictors of mortality in hospitalized COVID-19 patients.

Admission Levels of Serum P-Selectin and IL-6 Can Predict Development of Deep Venous Thrombosis in Hospitalized Covid-19 Patients

Background and Aim

Deep venous thrombosis (DVT) of the lower extremities is common in Covid-19 patients. Interleukin (IL)-6 and P-selectin were found to be elevated in Covid-19 patients. The current study aimed to evaluate P-selectin and IL6 in Covid-19 patients with DVT and to explore its relation to clinical and laboratory parameters in those patients.

Patients and methods

The present retrospective study included 150 hospitalized COVID-19 patients diagnosed on the basis of a positive result of reverse-transcriptase polymerase chain reaction (RT-PCR) test. Laboratory assessments were included for IL-6 and P selectin assessments via enzyme-linked immunosorbent assay. The primary outcome of the present study was the development of DVT detected by Doppler ultrasound (DU) evaluation of the lower extremities during the admission.

Results

The present study included 150 hospitalized Covid-19 patients. DVT was developed in 59 patients (39.3%). DVP patients had significantly higher levels of P selectin [76.0 (63.0-87.0) versus 63.0 (54.3-75.0), p < 0.001] and IL-6 [37.0 (27.0-49.0) versus 18.5 (13.5-31.5), p < 0.001]. ROC curve analysis revealed good performance of P selectin [AUC (95% CI): 0.72 (0.64-0.81)] and IL-6 [AUC (95% CI): 0.79 (0.71-0.86)] in identification of DVT. Logistic regression analysis identified the presence of severe disease [OR (95% CI): 9.016 (3.61-22.49), p < 0.001], elevated P selectin [OR (95% CI): 1.032 (1.005-1.059), p = 0.018] and elevated IL-6 [OR (95% CI): 1.062 (1.033-1.091), p < 0.001] as significant predictors of DVT development in multivariate analysis.

Conclusion

The present study identified a probable role of elevated P-selectin and IL-6 levels in the DVT development in hospitalized Covid-19 patients.

Evaluation of Serum Ferritin, Procalcitonin, and C-Reactive Protein for the Prediction of Severity and Mortality in Hemorrhagic Fever With Renal Syndrome

This study aimed to analyze the clinical significance of serum ferritin, procalcitonin (PCT), and C-reactive protein (CRP) in patients with hemorrhagic fever with renal syndrome (HFRS). The demographical, clinical, and laboratory data of 373 patients with HFRS in northeastern China were retrospectively analyzed. The levels of serum ferritin and PCT in severe patients (n = 108) were significantly higher than those in mild patients (n = 265, p < 0.001) and associated with HFRS severity. The area under the receiver operating characteristic curve (AUC) values of serum ferritin and PCT for predicting the severity of HFRS were 0.732 (95% CI 0.678-0.786, p < 0.001) and 0.824 (95% CI 0.773-0.875, p < 0.001), respectively, showing sensitivity and specificity of 0.75 and 0.88 for serum ferritin, and 0.76 and 0.60 for PCT. The CRP level in HFRS with bacterial co-infection (n = 115) was higher than that without bacterial co-infection (n = 258, p < 0.001). The AUC value of CRP for predicting bacterial co-infection was 0.588 (95% CI 0.525-0.652, p < 0.001), showing sensitivity and specificity of 0.43 and 0.76, respectively. The serum ferritin level in non-survivors (n = 14) was significantly higher than in survivors (n = 359, p < 0.001). The AUC value of serum ferritin for predicting mortality was 0.853 (95% CI 0.774-0.933, p < 0.001), showing sensitivity and specificity of 0.933 and 0.739. Serum ferritin and PCT have a robust association with HFRS severity and mortality, which may be promising predictors, and CRP is an effective biomarker to assess bacterial co-infection in HFRS.

Post-COVID-19 fetal cardiac evaluation in moderate infection group of pregnant women

PURPOSE

To determine the long-term fetal cardiac effects of the SARS-CoV-2 infection in pregnant women recovered from moderate COVID-19 with fetal echocardiography (ECHO).

METHODS

Forty-five pregnant women that recovered from moderate COVID-19 (CRG) 4 weeks after the infection confirmation, were compared with 45 gestational and maternal age-matched control groups (CG) in terms of demographic features fetal cardiac morphological (sphericity index, cardiothoracic ratio), and functional (myocardial performance index, mitral E/A, tricuspid E/A, mitral and tricuspid annular plane systolic excursion) parameters.

RESULTS

There was no difference in demographic features between the groups. Fetal cardiac morphologic parameters were found to be similar between the two groups. When the fetal cardiac functional assessment of the two groups was compared, only mitral E/A ratio results were found to be statistically significantly lower in the CRG than in the control group (p = 0.030).

CONCLUSION

The fetal heart does not seem to be negatively affected by COVID-19 after recovery from moderate infection. These results about the fetal effect of SARS-CoV-2 may improve our limited knowledge of the utility of fetal ECHO in pregnant women who recovered from COVID-19.

Comprehensive Review of Cardiovascular Complications of Coronavirus Disease 2019 and Beneficial Treatments

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 and was first reported in December 2019 in Wuhan, China. Since then, it caused a global pandemic with 212,324,054 confirmed cases and 4,440,840 deaths worldwide as of August 22, 2021. The disease spectrum of COVID-19 ranges from asymptomatic subclinical infection to clinical manifestations predominantly affecting the respiratory system. However, it is now evident that COVID-19 is a multiorgan disease with a broad spectrum of manifestations leading to multiple organ injuries including the cardiovascular system. We review studies that have shown that the relationship between cardiovascular diseases and COVID-19 is indeed bidirectional, implicating that preexisting cardiovascular comorbidities increase the morbidity and mortality of COVID-19, and newly emerging cardiac injuries occur in the settings of acute COVID-19 in patients with no preexisting cardiovascular disease. We present the most up-to-date literature summary to explore the incidence of new-onset cardiac complications of coronavirus and their role in predicting the severity of COVID-19. We review the association of elevated troponin with the severity of COVID-19 disease, which includes mild compared to severe disease, in nonintensive care unit compared to intensive care unit patients and in those discharged from the hospital compared to those who die. The role of serum troponin levels in predicting prognosis are compared in survivors and non-survivors. The association between COVID-19 disease and myocarditis, heart failure and coagulopathy are reviewed. Finally, an update on beneficial treatments is discussed.

A conceptual IoT-based early-warning architecture for remote monitoring of COVID-19 patients in wards and at home

Due to the COVID-19 pandemic, health services around the globe are struggling. An effective system for monitoring patients can improve healthcare delivery by avoiding in-person contacts, enabling early-detection of severe cases, and remotely assessing patients' status. Internet of Things (IoT) technologies have been used for monitoring patients' health with wireless wearable sensors in different scenarios and medical conditions, such as noncommunicable and infectious diseases. Combining IoT-related technologies with early-warning scores (EWS) commonly utilized in infirmaries has the potential to enhance health services delivery significantly. Specifically, the NEWS-2 has been showing remarkable results in detecting the health deterioration of COVID-19 patients. Although the literature presents several approaches for remote monitoring, none of these studies proposes a customized, complete, and integrated architecture that uses an effective early-detection mechanism for COVID-19 and that is flexible enough to be used in hospital wards and at home. Therefore, this article's objective is to present a comprehensive IoT-based conceptual architecture that addresses the key requirements of scalability, interoperability, network dynamics, context discovery, reliability, and privacy in the context of remote health monitoring of COVID-19 patients in hospitals and at home. Since remote monitoring of patients at home (essential during a pandemic) can engender trust issues regarding secure and ethical data collection, a consent management module was incorporated into our architecture to provide transparency and ensure data privacy. Further, the article details mechanisms for supporting a configurable and adaptable scoring system embedded in wearable devices to increase usefulness and flexibility for health care professions working with EWS.

Surviving the Storm: Cytokine Biosignature in SARS-CoV-2 Severity Prediction

Simple Summary

The world has been stricken mentally, physically, and economically by the COVID-19 virus. However, while SARS-CoV-2 viral infection results in mild flu-like symptoms in most patients, a number of those infected develop severe illness. These patients require hospitalization and intensive care. The severe disease can spiral downwards with eventual severe damage to the lungs and failure of multiple organs, leading to the individual’s demise. It is necessary to identify those who are developing a severe form of illness to provide early management. Therefore, it is crucial to learn about the mechanisms and chemical mediators that lead to critical conditions in SARS-CoV-2 infection. This paper reviews studies regarding the individual chemical mediators, pathways, and means that contribute to worsening health conditions in SARS-CoV-2 infection.

Abstract

A significant part of the world population has been affected by the devastating SARS-CoV-2 infection. It has deleterious effects on mental and physical health and global economic conditions. Evidence suggests that the pathogenesis of SARS-CoV-2 infection may result in immunopathology such as neutrophilia, lymphopenia, decreased response of type I interferon, monocyte, and macrophage dysregulation. Even though most individuals infected with the SARS-CoV-2 virus suffer mild symptoms similar to flu, severe illness develops in some cases, including dysfunction of multiple organs. Excessive production of different inflammatory cytokines leads to a cytokine storm in COVID-19 infection. The large quantities of inflammatory cytokines trigger several inflammation pathways through tissue cell and immune cell receptors. Such mechanisms eventually lead to complications such as acute respiratory distress syndrome, intravascular coagulation, capillary leak syndrome, failure of multiple organs, and, in severe cases, death. Thus, to devise an effective management plan for SARS-CoV-2 infection, it is necessary to comprehend the start and pathways of signaling for the SARS-CoV-2 infection-induced cytokine storm. This article discusses the current findings of SARS-CoV-2 related to immunopathology, the different paths of signaling and other cytokines that result in a cytokine storm, and biomarkers that can act as early signs of warning for severe illness. A detailed understanding of the cytokine storm may aid in the development of effective means for controlling the disease’s immunopathology. In addition, noting the biomarkers and pathophysiology of severe SARS-CoV-2 infection as early warning signs can help prevent severe complications.

A look back at the first wave of COVID-19 in China: A systematic review and meta-analysis of mortality and health care resource use among severe or critical patients

Background

To investigate the mortality and health care resource use among patients with severe or critical coronavirus disease of 2019 (COVID-19) in the first wave of pandemic in China.

Methods

We performed a systematic review and meta-analysis to investigate the mortality, discharge rate, length of hospital stay, and use of invasive ventilation in severe or critical COVID-19 cases in China. We searched electronic databases for studies from China with no restrictions on language or interventions patients received. We screened records, extracted data and assessed the quality of included studies in duplicate. We performed the meta-analysis using random-effect models through a Bayesian framework. Subgroup analyses were conducted to examine studies by disease severity, study location and patient enrolment start date. We also performed sensitivity analysis using various priors, and assessed between-study heterogeneity and publication bias for the primary outcomes.

Results

Out of 6,205 titles and abstracts screened, 500 were reviewed in full text. A total of 42 studies were included in the review, of which 95% were observational studies (n = 40). The pooled 28-day and 14-day mortalities among severe or critical patients were 20.48% (7,136 patients, 95% credible interval (CrI), 13.11 to 30.70) and 10.83% (95% CrI, 6.78 to 16.75), respectively. The mortality declined over time and was higher in patients with critical disease than severe cases (1,235 patients, 45.73%, 95% CrI, 22.79 to 73.52 vs. 3,969 patients, 14.90%, 95% CrI, 4.70 to 39.57) and patients in Hubei compared to those outside Hubei (6,719 patients, 26.62%, 95% CrI, 13.11 to 30.70 vs. 244 patients, 5.88%, 95% CrI 2.03 to 14.11). The length of hospital stay was estimated at 18.48 days (6,847 patients, 95% CrI, 17.59 to 21.21), the 28-day discharge rate was 50.48% (3,645 patients, 95% CrI, 26.47 to 79.53), and the use of invasive ventilation rate was 13.46% (4,108 patients, 95% CrI, 7.61 to 22.31).

Conclusions

Our systematic review and meta-analysis found high mortality among severe and critical COVID-19 cases. Severe or critical COVID-19 cases consumed a large amount of hospital resources during the outbreak.

D-dimer, CRP, PCT, and IL-6 Levels at Admission to ICU Can Predict In-Hospital Mortality in Patients with COVID-19 Pneumonia

Introduction

Health care workers have had a challenging task since the COVID-19 outbreak. Prompt and effective predictors of clinical outcomes are crucial to recognize potentially critically ill patients and improve the management of COVID-19 patients. The aim of this study was to identify potential predictors of clinical outcomes in critically ill COVID-19 patients.

Methods

The study was designed as a retrospective cohort study, which included 318 patients treated from June 2020 to January 2021 in the Intensive Care Unit (ICU) of the Clinical Hospital Center “Bezanijska Kosa” in Belgrade, Serbia. The verified diagnosis of COVID-19 disease, patients over 18 years of age, and the hospitalization in ICU were the criteria for inclusion in the study. The optimal cutoff value of D-dimer, CRP, IL-6, and PCT for predicting hospital mortality was determined using the ROC curve, while the Kaplan-Meier method and log-rank test were used to assess survival.

Results

The study included 318 patients: 219 (68.9%) were male and 99 (31.1%) female. The median age of patients was 69 (60-77) years. During the treatment, 195 (61.3%) patients died, thereof 130 male (66.7%) and 65 female (33.3%). 123 (38.7%) patients were discharged from hospital treatment. The cutoff value of IL-6 for in-hospital death prediction was 74.98 pg/mL (Sn 69.7%, Sp 62.7%); cutoff value of CRP was 81 mg/L (Sn 60.7%, Sp 60%); cutoff value of procalcitonin was 0.56 ng/mL (Sn 81.1%, Sp 76%); and cutoff value of D-dimer was 760 ng/mL FEU (Sn 63.4%, Sp 57.1%). IL-6 ≥ 74.98 pg/mL, CRP ≥ 81 mg/L, PCT ≥ 0.56 ng/mL, and D-dimer ≥ 760 ng/mL were statistically significant predictors of in-hospital mortality.

Conclusion

IL-6 ≥ 74.98 pg/mL, CRP values ≥ 81 mg/L, procalcitonin ≥ 0.56 ng/mL, and D-dimer ≥ 760 ng/mL could effectively predict in-hospital mortality in COVID-19 patients.

The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients

Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has caused a global burden for health care systems due to high morbidity and mortality rates, leading to caseloads that episodically surpass hospital resources. Due to different disease manifestations, the triage of patients at high risk for a poor outcome continues to be a major challenge for clinicians. The AIFELL score was developed as a simple decision instrument for emergency rooms to distinguish COVID-19 patients in severe disease stages from less severe COVID-19 and non-COVID-19 cases. In the present study, we aimed to evaluate the AIFELL score as a prediction tool for clinical deterioration and disease severity in hospitalized COVID-19 patients. During the second wave of the COVID-19 pandemic in Switzerland, we analyzed consecutively hospitalized patients at the Triemli Hospital Zurich from the end of November 2020 until mid-February 2021. Statistical analyses were performed for group comparisons and to evaluate significance. AIFELL scores of patients developing severe COVID-19 stages IIb and III during hospitalization were significantly higher upon admission compared to those patients not surpassing stages I and IIa. Group comparisons indicated significantly different AIFELL scores between each stage. In conclusion, the AIFELL score at admission was useful to predict the disease severity and progression in hospitalized COVID-19 patients.

Why do men have worse COVID-19-related outcomes? A systematic review and meta-analysis with sex adjusted for age

We aimed to study the mechanism behind worse coronavirus disease-19 (COVID-19) outcomes in men and whether the differences between sexes regarding mortality as well as disease severity are influenced by sex hormones. To do so, we used age as a covariate in the meta-regression and subgroup analyses. This was a systematic search and meta-analysis of observational cohorts reporting COVID-19 outcomes. The PubMed (Medline) and Cochrane Library databases were searched. The primary outcome was COVID-19-associated mortality and the secondary outcome was COVID-19 severity. The study was registered at PROSPERO: 42020182924. For mortality, men had a relative risk of 1.36 (95%CI: 1.17 to 1.59; I2 63%, P for heterogeneity <0.01) compared to women. Age was not a significant covariate in meta-analysis heterogeneity (P=0.393) or subgroup analysis. For disease severity, being male was associated with a relative risk of 1.29 (95%CI: 1.19 to 1.40; I2 48%, P for heterogeneity <0.01) compared to the relative risk of women. Again, age did not influence the outcomes of the meta-regression (P=0.914) or subgroup analysis. Men had a higher risk of COVID-19 mortality and severity regardless of age, decreasing the odds of hormonal influences in the described outcomes.

Risk factors of mortality in hospitalized patients with COVID-19 applying a Machine Learning algorithm

Introduction

Risk stratification of patients with COVID-19 can be fundamental to support clinical decision-making and optimize resources. The objective of our study is to identify among the routinely tested clinical and analytical parameters those that would allow us to determine patients with the highest risk of dying from COVID-19.

Material and methods

We carried out a retrospective cohort multicentric study by consecutively, including hospitalized patients with COVID-19 admitted in any of the 11 hospitals in the healthcare network of HM Hospitals-Spain. We collected the clinical, demographic, analytical, and radiological data from the patient's medical records.

To assess each of the biomarkers’ predictive impact and measure the statistical significance of the variables involved in the analysis, we applied a random forest with a permutation method. We used the similarity measure induced by a previously classification model and adjusted the k-groups clustering algorithm based on the energy distance to stratify patients into a high and low-risk group. Finally, we adjusted two optimal classification trees to have a schematic representation of the cut-off points.

Results

We included 1246 patients (average age of 65.36 years, 62% males). During the study one hundred sixty-eight patients (13%) died. High values of age, D-Dimer, White Blood Cell, Na, CRP, and creatinine represent the factors that identify high-risk patients who would die.

Conclusions

Age seems to be the primary predictor of mortality in patients with SARS-CoV-2 infection, while the impact of acute phase reactants and blood cellularity is also highly relevant.

A Peek into Pandora’s Box: COVID-19 and Neurodegeneration

Ever since it was first reported in Wuhan, China, the coronavirus-induced disease of 2019 (COVID-19) has become an enigma of sorts with ever expanding reports of direct and indirect effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on almost all the vital organ systems. Along with inciting acute pulmonary complications, the virus attacks the cardiac, renal, hepatic, and gastrointestinal systems as well as the central nervous system (CNS). The person-to-person variability in susceptibility of individuals to disease severity still remains a puzzle, although the comorbidities and the age/gender of a person are believed to play a key role. SARS-CoV-2 needs angiotensin-converting enzyme 2 (ACE2) receptor for its infectivity, and the association between SARS-CoV-2 and ACE2 leads to a decline in ACE2 activity and its neuroprotective effects. Acute respiratory distress may also induce hypoxia, leading to increased oxidative stress and neurodegeneration. Infection of the neurons along with peripheral leukocytes’ activation results in proinflammatory cytokine release, rendering the brain more susceptible to neurodegenerative changes. Due to the advancement in molecular biology techniques and vaccine development programs, the world now has hope to relatively quickly study and combat the deadly virus. On the other side, however, the virus seems to be still evolving with new variants being discovered periodically. In keeping up with the pace of this virus, there has been an avalanche of studies. This review provides an update on the recent progress in adjudicating the CNS-related mechanisms of SARS-CoV-2 infection and its potential to incite or accelerate neurodegeneration in surviving patients. Current as well as emerging therapeutic opportunities and biomarker development are highlighted.

Prognostic Accuracy of Cardiovascular Disease Biomarkers in Patients with COVID-19: A Diagnostic Test Accuracy Meta-Analysis

Background: Several reports have determined that cardiovascular diseases (CVDs) are common complications in patients with coronavirus disease 2019 (COVID-19) and lead them to poor outcomes. CVD biomarkers have, thus, great potential to be used as prognostic biomarkers. We aimed to determine the accuracy of CVD biomarkers for the prognosis of the COVID-19 patient’s outcome via a diagnostic test accuracy (DTA) meta-analysis.

Methods: Until September 30, 2020, we searched Web of Sciences, Scopus, and MEDLINE/PubMed databases to obtain related papers. The summary points and lines were calculated using bivariate/HSROC model. As outcomes, we considered critical conditions and mortality.

Results: A total of 17 659 patients from 33 studies were included. Five biomarkers, namely increased levels of lactate dehydrogenase (LDH), cardiac troponin I (cTnI), creatine kinase (CK), D-dimer, and thrombocytopenia, met the inclusion criteria. Our results indicated that LDH and cTnI had good accuracy for the prognosis of critical condition (AUC_HSROC=0.83 and 0.80, respectively), while LDH, cTnI, and D-dimer had acceptable accuracy (AUC_HSROC=0.74, 0.71, and 0.72, respectively) for the prognosis of mortality. LDH and D-dimer had high sensitivity, whereas cTnI had high specificity. The other biomarkers did not have acceptable accuracy. Significant publication bias was found for D-dimer (P=0.053).

Conclusion: Among CVD biomarkers, LDH and cTnI had good accuracy for the prognosis of critical outcomes and acceptable accuracy for the prognosis of mortality, without publication bias. Given their different sensitivities and specificities, we recommend the use of these 2 biomarkers concomitantly.

COVID-19 disease severity and associated factors among Ethiopian patients: A study of the millennium COVID-19 care center

Background

The COVID-19 pandemic started a little later in Ethiopia than the rest of the world and most of the initial cases were reported to have a milder disease course and a favorable outcome. This changed as the disease spread into the population and the more vulnerable began to develop severe disease. Understanding the risk factors for severe disease in Ethiopia was needed to provide optimal health care services in a resource limited setting.

Objective

The study assessed COVID-19 patients admitted to Millennium COVID-19 Care Center in Ethiopia for characteristics associated with COVID-19 disease severity.

Methods

A cross-sectional study was conducted from June to August 2020 among 686 randomly selected patients. Chi-square test was used to detect the presence of a statistically significant difference in the characteristics of the patients based on disease severity (Mild vs Moderate vs Severe). A multinomial logistic regression model was used to identify factors associated with COVID-19 disease severity where Adjusted Odds ratio (AOR), 95% CIs for AOR and P-values were used for significance testing.

Results

Having moderate as compared with mild disease was significantly associated with having hypertension (AOR = 2.30, 95%CI = 1.27,4.18), diabetes mellitus (AOR = 2.61, 95%CI = 1.31,5.19for diabetes mellitus), fever (AOR = 6.12, 95%CI = 2.94,12.72) and headache (AOR = 2.69, 95%CI = 1.39,5.22). Similarly, having severe disease as compared with mild disease was associated with age group (AOR = 4.43, 95%CI = 2.49,7.85 for 40–59 years and AOR = 18.07, 95%CI = 9.29,35.14for ≥ 60 years), sex (AOR = 1.84, 95%CI = 1.12,3.03), hypertension (AOR = 1.97, 95%CI = 1.08,3.59), diabetes mellitus (AOR = 3.93, 95%CI = 1.96,7.85), fever (AOR = 13.22, 95%CI = 6.11, 28.60) and headache (AOR = 4.82, 95%CI = 2.32, 9.98). In addition, risk factors of severe disease as compared with moderate disease were found to be significantly associated with age group (AOR = 4.87, 95%CI = 2.85, 8.32 for 40–59 years and AOR = 18.91, 95%CI = 9.84,36.331 for ≥ 60 years), fever (AOR = 2.16, 95%CI = 1.29,3.63) and headache (AOR = 1.79, 95%CI = 1.03, 3.11).

Conclusions

Significant factors associated with severe COVID-19 in Ethiopia are being older than 60 years old, male, a diagnosis of hypertension, diabetes mellitus, and the presence of fever and headache. This is consistent with severity indicators identified by WHO and suggests the initial finding of milder disease in Ethiopia may have been because the first people to get COVID-19 in the country were the relatively younger with fewer health problems.

Methylprednisolone accelerate chest computed tomography absorption in COVID-19: A three-centered retrospective case control study from China

BACKGROUND

Based on the results of some large randomized controlled trials (RCTs) confirmed the efficacy of corticosteroids in coronavirus disease 2019 (COVID-19), corticosteroids have been included in World Health Organization guidelines, but remain controversial.

AIM

To investigate the efficacy and safety of low-to-moderate dose (30 to 40 mg/d) short-term methylprednisolone for COVID-19 patients.

METHODS

The clinical data of 70 patients diagnosed with COVID-19 who received antiviral therapy with Arbidol for 7-10 d before admission but had no obvious absorption on chest computed tomography (CT) imaging were retrospectively analyzed. Arbidol (as the control group) and methylprednisolone (as the corticosteroid group) were given respectively after admission. After treatment, chest CT was reexamined to evaluate the absorption of pulmonary lesions. Additionally, we evaluated and compared the lymphocyte count, erythrocyte sedimentation rate (ESR), interleukin-6(IL-6), serum ferritin, lactate dehydrogenase (LDH), creatine kinase-MB (CK-MB), hypersensitive C-reactive protein (hs-CRP) and D-dimer levels, and also analyzed the incidence of toxic and side effects.

RESULTS

All patients in the corticosteroid group had varying degrees of CT absorption, which was significantly better than that in the control group (CT obvious absorption rate: 89.47% vs 12.5%, P < 0.05). The average daily dose and course of methylprednisolone in the patients with significant improvement on chest CT was (38.55 ± 13.17) mg and (6.44 ± 1.86) d respectively. During the treatment, the lymphocyte count, ESR, IL-6, serum ferritin, LDH, CK-MB, hs-CRP and D-dimer levels all improved gradually, indicating that both Arbidol and methylprednisolone therapy were contributed to improving the condition of COVID-19 patients. The corticosteroid regimen did not prolong the clearance time of severe acute respiratory syndrome coronavirus 2. There were no severe adverse reactions such as gastrointestinal bleeding, secondary severe infection, hypertension, diabetic ketoacidosis, mental disorders or electrolyte disorders during the whole corticosteroid treatment process.

CONCLUSION

Low-to-moderate dose short-term methylprednisolone can accelerate the chest CT imaging absorption of COVID-19 so as to improve symptoms and alleviate the condition in a short term, reduce the hospital stay, meanwhile avoid severe COVID-19 phases. The protocol has been proven to be effective and safe in clinical use.

Accumulation of Cytochrome b558 at the Plasma Membrane: Hallmark of Oxidative Stress in Phagocytic Cells

Neutrophils play a very key role in the human immune defense against pathogenic infections. The predominant players in this role during the activation of neutrophils are the release of cytotoxic agents stored in the granules and secretory vesicles and the massive production of reactive oxygen species (ROS) initiated by the enzyme NADPH oxidase. In addition, in living organisms, cells are continuously exposed to endogenous (inflammations, elevated neutrophil presence in the vicinity) and exogenous ROS at low and moderate levels (travels by plane, radiotherapy, space irradiation, blood banking, etc.). To study these effects, we used ROS induced by gamma radiation from low (0.2 Gy) to high (25 Gy) dose levels on PLB-985 cells from a myeloid cell line differentiated to neutrophil-like cells that are considered a good alternative to neutrophils. We determined a much longer lifetime of PLB-985 cells than that of neutrophils, which, as expected, decreased by increasing the irradiation dose. In the absence of any secondary stimulus, a very low production of ROS is detected with no significant difference between irradiated and non-irradiated cells. However, in phagocytosing cells, irradiation doses above 2 Gy enhanced oxidative burst in PLB-985 cells. Whatever the irradiation dose, NADPH oxidase devoid of its cytosolic regulatory units is observed at the plasma membrane in irradiated PLB-985 cells. This result is different from that observed for irradiated neutrophils in which irradiation also induced a translocation of regulatory subunits suggesting that the signal transduction mechanism or pathway operate differently in both cells.

Factor Related the Use of Respiratory Supports among COVID-19 Patients in Sardjito Hospital Yogyakarta: A Cross-sectional Study

BACKGROUND: In patients with coronavirus disease-19 (COVID-19), respiratory failure is a serious condition that requires immediate respiratory supports. Various clinical conditions can be determinant factors to the need for used of ventilators. AIM: The aim of the study was to determine factor related to the used of ventilators among COVID-19 patients transferred to intensive care unit Sardjito Hospital. METHODS: Using a cross-sectional design, a total of 171 of 300 medical records selected in accordance to the inclusion criteria. Association of each clinical characteristics and outcome variable used contingency coefficient and Spearman rank tests, while multivariate logistic regression model was performed for hypothesis testing. The area under curve (AUC) was test to determine model fit of the logistic approach. RESULTS: There was a significant correlation between age (p = 0.004), blood sugar levels (p < 0.001), and oxygen saturation (p < 0.001), and the used of ventilator. Patients with hypoxia and severe hypoxia had odds of using ventilation supports 5 times and 114 times (OR = 5.623) and (OR = 114.3). The AUC test indicated that null hypothesis was rejected. CONCLUSION: The clinical characteristics were associated with age, blood sugar levels, and oxygen saturation. Patients with COVID-19 who admitted to hospital with hypoxia and severe hypoxia increased the odds of the use ventilators.

Risk factors for oxygen requirement in hospitalized pregnant and postpartum women with COVID-19

OBJECTIVE

To identify risk factors for Oxygen (O₂) needs in pregnant and postpartum women with COVID-19.

METHODS

Prospective cohort involving pregnant women hospitalized with COVID-19 from April to October 2020. The oxygen need was analyzed regarding risk factors: demographic characteristics, clinical and laboratory parameters at hospital admission, and chest Computer Tomography (CT) findings. Poisson univariate analysis was used to estimate the Relative Risk (RR) and 95% Confidence Intervals.

RESULTS

145 patients, 80 who used and 65 who did not use O₂, were included. Body mass index ≥ 30, smoking, and chronic hypertension increased the risk of O₂ need by 1.86 (95% CI 1.10-3.21), 1.57 (95% CI 1.16‒2.12), and 1.46 (95% CI 1.09‒1.95), respectively. Patients who were hospitalized for COVID-19 and for obstetric reasons had 8.24 (95% CI 2.8‒24.29) and 3.44 (95% CI 1.05‒11.31) times more use of O₂ than those admitted for childbirth and abortion. Respiratory rate ≥ 24 breaths/min and O₂ saturation < 95% presented RR for O₂ requirements of 2.55 (1.82‒3.56) and 1.68 (95% CI 1.27-2.20), respectively. Ground Glass (GG) < 50% and with GG ≥ 50%, the risk of O₂ use were respectively 3.41-fold and 5.33-fold higher than in patients who haven't viral pneumonia on CT. The combination of C-reactive protein ≥ 21 mg/L, hemoglobin < 11.0 g/dL, and lymphopenia < 1500 mm³ on hospital admission increased the risk of O₂ use by 4.97-times.

CONCLUSIONS

In obstetric patients, clinical history, laboratory, clinical and radiological parameters at admission were identified as a risk for O₂ need, selecting the population with the greatest chance of worsening.

Predictors of mortality in COVID-19 patients at Kinshasa Medical Center and a survival analysis: a retrospective cohort study

Background

Despite it being a global pandemic, there is little research examining the clinical features of severe COVID-19 in sub-Saharan Africa. This study aims to identify predictors of mortality in COVID-19 patients at Kinshasa Medical Center (KMC).

Methods

In this retrospective, observational, cohort study carried out at the Kinshasa Medical Center (KMC) between March 10, 2020 and July 10, 2020, we included all adult inpatients (≥ 18 years old) with a positive COVID-19 PCR result. The end point of the study was survival. The study population was dichotomized into survivors and non-survivors group. Kaplan–Meier plot was used for survival analyses. The Log-Rank test was employed to compare the survival curves. Predictors of mortality were identified by Cox regression models. The significance level of p value was set at 0.05.

Results

432 patients with confirmed COVID-19 were identified and only 106 (24.5%) patients with moderate, severe or critical illness (mean age 55.6 ± 13.2 years old, 80.2% were male) were included in this study, of whom 34 (32%) died during their hospitalisation. The main complications of the patients included ARDS in 59/66 (89.4%) patients, coagulopathy in 35/93 (37.6%) patients, acute cardiac injury in 24/98 (24.5%) patients, AKI in 15/74 (20.3%) patients and secondary infection in 12/81 (14.8%) patients. The independent predictors of mortality were found to be age [aHR 1.38; 95% CI 1.10–1.82], AKI stage 3 [aHR 2.51; 95% CI 1.33–6.80], proteinuria [aHR 2.60; 95% CI 1.40–6.42], respiratory rate [aHR 1.42; 95% CI 1.09–1.92] and procalcitonin [aHR 1.08; 95% CI 1.03–1.14]. The median survival time of the entire group was 12 days. The cumulative survival rate of COVID-19 patients was 86.9%, 65.0% and 19.9% respectively at 5, 10 and 20 days. Levels of creatinine (p = 0.012), were clearly elevated in non-survivors compared with survivors throughout the clinical course and increased deterioration.

Conclusion

Mortality rate of COVID-19 patients is high, particularly in intubated patients and is associated with age, respiratory rate, proteinuria, procalcitonin and acute kidney injury.

Simple Coagulation Profile as Predictor of Mortality in Adults Admitted with COVID-19: A Meta-Analysis

Context: COVID-19 severe manifestations must be detected as soon as possible. One of the essential poor characteristics is the involvement of coagulopathy. Simple coagulation parameters, including prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (aPTT), and platelet, are widely accessible in many health centers. Objectives: This meta-analysis aimed to determine the association between simple coagulation profiles and COVID-19 in-hospital mortality. Method: We systematically searched five databases for studies measuring simple coagulation parameters in COVID-19 on admission. The random-effects and inverse-variance weighting were used in the study, which used a standardized-mean difference of coagulation profile values. The odds ratios were computed using the Mantel-Haenszel formula for dichotomous variables. Results: This meta-analysis comprised a total of 30 studies (9,175 patients). In our meta-analysis, we found that non-survivors had a lower platelet count [SMD = -0.56 (95% CI: -0.79 to -0.33), P < 0.01; OR = 3.00 (95% CI: 1.66 to 5.41), P < 0.01], prolonged PT [SMD = 1.22 (95%CI: 0.71 to 1.72), P < 0.01; OR = 1.86 (95%CI: 1.43 to 2.43), P < 0.01], prolonged aPTT [SMD = 0.24 (95%CI: -0.04 to 0.52), P = 0.99], and increased INR [SMD = 2.21 (95%CI: 0.10 to 4.31), P = 0.04] than survivors. Conclusions: In COVID-19 patients, abnormal simple coagulation parameters on admission, such as platelet, PT, and INR, were associated with mortality outcomes.

Lactate dehydrogenase to albumin ratio as a prognostic factor in lower respiratory tract infection patients

PURPOSE

To verify the role of lactate dehydrogenase to albumin (LDH/ALB) ratio as an independent prognostic factor for mortality due to the lower respiratory tract infection (LRTI) in the emergency department (ED).

METHODS

We reviewed the electronic medical records of patients who were admitted to the ED for the management of LRTI between January 2018 and December 2020. Initial vital signs, laboratory data, and patient severity scores in the ED were collected. The LDH/ALB ratio was compared to other albumin-based ratios (blood urea nitrogen to albumin ratio, C-reactive protein to albumin ratio, and lactate to albumin ratio) and severity scales (pneumonia severity index, modified early warning score, CURB-65 scores), which are being used as prognostic factors for in-hospital mortality. Multivariable logistic regression was performed to identify independent risk factors.

RESULTS

The LDH/ALB ratio was higher in the non-survivor group than in the survivor group (median [interquartile range]: 217.6 [160.3;312.0] vs. 126.4 [100.3;165.1], p < 0.001). In the comparison of the area under the receiver operating characteristic curve (AUC) for predicting in-hospital mortality, the AUC of the LDH/ALB ratio (0.808, 95% confidence interval: 0.757-0.842, p < 0.001) was wider than other albumin-based ratios and severity scales, except the blood urea nitrogen to albumin ratio. In the multivariable logistic regression analysis, the LDH/ALB ratio independently affected in-hospital mortality.

CONCLUSION

The LDH/ALB ratio may serve as an independent prognostic factor for in-hospital mortality in patients with LRTI.