Decrease in hemoglobin level predicts increased risk for severe respiratory failure in COVID-19 patients with pneumonia

Modulation in serum and hematological parameters as a prognostic indicator of COVID-19 infection in hypertension, diabetes mellitus, and different cardiovascular diseases

SARS-CoV-2 infection affects and modulates serum as well as hematological parameters. However, whether it modifies these parameters in the existing disease conditions, which help in the erection of specific treatments for the disease, is under investigation. Here, we aimed to determine whether serum and hematological parameters alteration in various diseases, diabetes mellitus (DM), hypertension (HTN), ischemic heart disease (IHD) and myocardial infarction (MI) conditions correlate and signal SARS-CoV-2 infection, which could be used as a rapid diagnosis tool for SARS-CoV-2 infection in disease conditions. To assess the projected goals, we collected blood samples of 1,113 male and female patients with solo and multiple disease conditions of DM/HTN/IHD/MI with severe COVID-19, followed by biochemical analysis, including COVID-19 virus detection by RT-qPCR. Furthermore, blood was collected from age-matched disease and healthy individuals 502 and 660 and considered as negative control. In our results, we examined higher levels of serum parameters, including D-dimer, ferritin, hs-CRP, and LDH, as well as hematological parameters, including TLC in sole and multiple diseases (DM/HTN/IHD/MI) conditions compared to the control subjects. Besides, the hematological parameters, including Hb, RBC, and platelet levels, decreased in the patients. In addition, we found declined levels of leukocyte count (%), lymphocyte (%), monocyte (%), and eosinophil (%), and elevated level of neutrophil levels (%) in all the disease patients infected with SARS-CoV-2. Besides, NLR and NMR ratios were also statistically significantly (p < 0.05) high in the patients with solo and multiple disease conditions of DM/HTN/IHD/MI infected with the SARS-CoV-2 virus. In conclusion, rapid alteration of sera and hematological parameters are associated with SARS-CoV-2 infections, which could help signal COVID-19 in respective disease patients. Moreover, our results may help to improve the clinical management for the rapid diagnosis of COVID-19 concurrent with respective diseases.

Assessing the interaction between hemoglobin and the receptor binding domain of SARS-CoV-2 spike protein through MARTINI coarse-grained molecular dynamics

The emergence of different coronavirus-related diseases in the 2000's (SARS, MERS, and Covid-19) warrants the need of a complete understanding of the pathological, biological, and biochemical behavior of this class of pathogens. Great attention has been paid to the SARS-CoV-2 Spike protein, and its interaction with the human ACE2 has been thoroughly investigated. Recent findings suggested that the SARS-CoV-2 components may interact with different human proteins, and hemoglobin has very recently been demonstrated as a potential target for the Spike protein. Here we have investigated the interaction between either adult or fetal hemoglobin and the receptor binding domain of the Spike protein at molecular level through advanced molecular dynamics techniques and proposed rational binding modes and energy estimations. Our results agree with biochemical data previously reported in literature. We also demonstrated that co-incubation of pulmonary epithelial cells with hemoglobin strongly reduces the pro-inflammatory effects exerted by the concomitant administration of Spike protein.

Evaluation of hematological parameters alterations in different waves of COVID-19 pandemic: A cross-sectional study

BACKGROUND

The occurrence of variations in routine hematological parameters is closely associated with disease progression, the development of severe illness, and the mortality rate among COVID-19 patients. This study aimed to investigate hematological parameters in COVID-19 hospitalized patients from the 1st to the 5th waves of the current pandemic.

METHODS

This cross-sectional study included a total of 1501 hospitalized patients with laboratory-confirmed COVID-19 based on WHO criteria, who were admitted to Shahid Sadoughi Hospital (SSH) in Yazd, Iran, from February 2020 to September 2021. Throughout, we encountered five COVID-19 surge waves. In each wave, we randomly selected approximately 300 patients and categorized them based on infection severity during their hospitalization, including partial recovery, full recovery, and death. Finally, hematological parameters were compared based on age, gender, pandemic waves, and outcomes using the Mann-Whitney U and Kruskal-Wallis tests.

RESULTS

The mean age of patients (n = 1501) was 61.1±21.88, with 816 (54.3%) of them being men. The highest mortality in this study was related to the third wave of COVID-19 with 21.3%. There was a significant difference in all of the hematological parameters, except PDW, PLT, and RDW-CV, among pandemic waves of COVID-19 in our population. The highest rise in the levels of MCV and RDW-CV occurred in the 1st wave, in the 2nd wave for lymphocyte count, MCHC, PLT count, and RDW-SD, in the 3rd wave for WBC, RBC, neutrophil count, MCH, and PDW, and in the 4th wave for Hb, Hct, and ESR (p < 0.01). The median level of Hct, Hb, RBC, and ESR parameters were significantly higher, while the mean level of lymphocyte and were lower in men than in women (p < 0.001). Also, the mean neutrophil in deceased patients significantly was higher than in those with full recovered or partial recovery (p < 0.001).

CONCLUSION

The findings of our study unveiled notable variations in hematological parameters across different pandemic waves, gender, and clinical outcomes. These findings indicate that the behavior of different strains of the COVID-19 may differ across various stages of the pandemic.

Factors associated with adverse outcomes among patients hospitalized at a COVID-19 treatment center in Herat, Afghanistan

Though many studies on COVID have been published to date, data on COVID-19 epidemiology, symptoms, risk factors and severity in low- and middle-income countries (LMICS), such as Afghanistan are sparse. To describe clinical characteristics, severity, and outcomes of patients hospitalized in the MSF COVID-19 treatment center (CTC) in Herat, Afghanistan and to assess risk factors associated with severe outcomes. 1113 patients were included in this observational study between June 2020 and April 2022. Descriptive analysis was performed on clinical characteristics, complications, and outcomes of patients. Univariate description by Cox regression to identify risk factors for an adverse outcome was performed. Adverse outcome was defined as death or transfer to a level 3 intensive care located at another health facility. Finally, factors identified were included in a multivariate Cox survival analysis. A total of 165 patients (14.8%) suffered from a severe disease course, with a median time of 6 days (interquartile range: 2-11 days) from admission to adverse outcome. In our multivariate model, we identified male gender, age over 50, high O2 flow administered during admission, lymphopenia, anemia and O2 saturation < = 93% during the first three days of admission as predictors for a severe disease course (p<0.05). Our analysis concluded in a relatively low rate of adverse outcomes of 14.8%. This is possibly related to the fact that the resources at an MSF-led facility are higher, in terms of human resources as well as supply of drugs and biomedical equipment, including oxygen therapy devices, compared to local hospitals. Predictors for severe disease outcomes were found to be comparable to other settings.

Hematological alterations associated with long COVID-19

Long COVID-19 is a condition characterized by persistent symptoms lasting beyond the acute phase of COVID-19. Long COVID-19 produces diverse symptomatology and can impact organs and systems, including the hematological system. Several studies have reported, in COVID-19 patients, hematological abnormalities. Most of these alterations are associated with a higher risk of severe disease and poor outcomes. This literature review identified studies reporting hematological parameters in individuals with Long COVID-19. Findings suggest that Long COVID-19 is associated with a range of sustained hematological alterations, including alterations in red blood cells, anemia, lymphopenia, and elevated levels of inflammatory markers such as ferritin, D-dimer, and IL-6. These alterations may contribute to a better understanding of the pathophysiology of Long COVID-19 and its associated symptoms. However, further research is needed to elucidate the underlying mechanisms and potential treatments for these hematological changes in individuals with Long COVID-19.

Erythrocytes Functionality in SARS-CoV-2 Infection: Potential Link with Alzheimer's Disease

Coronavirus disease 2019 (COVID-19) is a rapidly spreading acute respiratory infection caused by SARS-CoV-2. The pathogenesis of the disease remains unclear. Recently, several hypotheses have emerged to explain the mechanism of interaction between SARS-CoV-2 and erythrocytes, and its negative effect on the oxygen-transport function that depends on erythrocyte metabolism, which is responsible for hemoglobin-oxygen affinity (Hb-O2 affinity). In clinical settings, the modulators of the Hb-O2 affinity are not currently measured to assess tissue oxygenation, thereby providing inadequate evaluation of erythrocyte dysfunction in the integrated oxygen-transport system. To discover more about hypoxemia/hypoxia in COVID-19 patients, this review highlights the need for further investigation of the relationship between biochemical aberrations in erythrocytes and oxygen-transport efficiency. Furthermore, patients with severe COVID-19 experience symptoms similar to Alzheimer's, suggesting that their brains have been altered in ways that increase the likelihood of Alzheimer's. Mindful of the partly assessed role of structural, metabolic abnormalities that underlie erythrocyte dysfunction in the pathophysiology of Alzheimer's disease (AD), we further summarize the available data showing that COVID-19 neurocognitive impairments most probably share similar patterns with known mechanisms of brain dysfunctions in AD. Identification of parameters responsible for erythrocyte function that vary under SARS-CoV-2 may contribute to the search for additional components of progressive and irreversible failure in the integrated oxygen-transport system leading to tissue hypoperfusion. This is particularly relevant for the older generation who experience age-related disorders of erythrocyte metabolism and are prone to AD, and provide an opportunity for new personalized therapies to control this deadly infection.

Disparities in COVID-19 incidence and fatality rates at high-altitude

Background

SARS-CoV-2 has affected every demography disproportionately, including even the native highland populations. Hypobaric-hypoxic settings at high-altitude (HA, >2,500 masl) present an extreme environment that impacts the survival of permanent residents, possibly including SARS-CoV-2. Conflicting hypotheses have been presented for COVID-19 incidence and fatality at HA.

Objectives

To evaluate protection or risk against COVID-19 incidence and fatality in humans under hypobaric-hypoxic environment of high-altitude (>2,501 masl).

Methods

Global COVID-19 data of March 2020-21, employed from official websites of the Indian Government, John Hopkins University, and Worldometer were clustered into 6 altitude categories. Clinical cofactors and comorbidities data were evaluated with COVID-19 incidence and fatality. Extensive comparisons and correlations using several statistical tools estimated the risk and protection.

Results

Of relevance, data analyses revealed four distinct responses, namely, partial risk, total risk, partial protection, and total protection from COVID-19 at high-altitude indicating a mixed baggage and complexity of the infection. Surprisingly, it included the countries within the same geographic region. Moreover, body mass index, hypertension, and diabetes correlated significantly with COVID-19 incidence and fatality rate (P ≤ 0.05).

Conclusions

Varied patterns of protection and risk against COVID-19 incidence and fatality were observed among the high-altitude populations. It is though premature to generalize COVID-19 effects on any particular demography without further extensive studies.

Pattern of antibiotic use and bacterial co-infection in hospitalized Covid-19 patients

Background

There is evidence that bacterial co-infection in respiratory viruses leads to morbidity and mortality. Patients with decreased immunity are prone to bacterial co-infection. A lack of judicious use of antibiotics leads to the spread of multi-drug resistant bacteria (MDR) that have a long-term negative impact. In this study, we attempted to observe the pattern of antibacterial use and its impact on secondary bacterial infection.

Methods

An observational study was conducted at Alexandria Main University Hospital (AMUH) (Alexandria University) from June 2021- February 2022. Study participants were admitted to the Intensive Care Unit (ICU) with confirmed Covid-19 (by Polymerase Chain Reaction (PCR) and Computed tomography (CT) scan). The following data was collected (Demographic, clinical, and laboratory data).In this study, the Pattern of antibiotic use as well as the occurrence of secondary bacterial infections were reported.

Results

Among 121 patients included in the present study, all received antibiotics empirically. Upon admission (19.8%) showed urinary tract infection, (11.5%) had bloodstream infection, and (57.7%) had respiratory tract infection. After 10 days secondary bacterial infection occurred in 38 patients (61.2%) with (24.1%) Urinary tract infection (UTI), (12.9%) Bloodstream infection (BSI), and (72.2%) respiratory tract infection. The respiratory sample size was (45) patients due to Infection Control (IC) restrictions on the aerosol-producing procedure.

Conclusion

Upon admission, all patients received broad-spectrum antibiotics while the incidence of bacterial co-infection was low.

mRNA COVID-19 Vaccines-Facts and Hypotheses on Fragmentation and Encapsulation

BACKGROUND

The adventure of the mRNA vaccine began thirty years ago in the context of influenza. This consisted in encapsulating the mRNA coding for a viral protein in a lipid particle. We show how the mRNA encoding S protein has been modified for that purpose in the context of the anti-SARS-CoV-2 vaccination.

RESULTS

by using data coming from genetic and epidemiologic databases, we show the theoretical possibility of fragmentation of this mRNA into small RNA sequences capable of inhibiting important bio-syntheses such as the production of beta-globin.

DISCUSSION

we discuss two aspects related to mRNA vaccine: (i) the plausibility of mRNA fragmentation, and (ii) the role of liposomal nanoparticles (LNPs) used in the vaccine and their impact on mRNA biodistribution.

CONCLUSION

we insist on the need to develop lipid nanoparticles allowing personalized administration of vaccines and avoiding adverse effects due to mRNA fragmentation and inefficient biodistribution. Hence, we recommend (i) adapting the mRNA of vaccines to the least mutated virus proteins and (ii) personalizing its administration to the categories of chronic patients at risk most likely to suffer from adverse effects.

Development and validation of a clinical predictive model for severe and critical pediatric COVID-19 infection

INTRODUCTION

Children infected with COVID-19 are susceptible to severe manifestations. We aimed to develop and validate a predictive model for severe/ critical pediatric COVID-19 infection utilizing routinely available hospital level data to ascertain the likelihood of developing severe manifestations.

METHODS

The predictive model was based on an analysis of registry data from COVID-19 positive patients admitted to five tertiary pediatric hospitals across Asia [Singapore, Malaysia, Indonesia (two centers) and Pakistan]. Independent predictors of severe/critical COVID-19 infection were determined using multivariable logistic regression. A training cohort (n = 802, 70%) was used to develop the prediction model which was then validated in a test cohort (n = 345, 30%). The discriminative ability and performance of this model was assessed by calculating the Area Under the Curve (AUC) and 95% confidence interval (CI) from final Receiver Operating Characteristics Curve (ROC).

RESULTS

A total of 1147 patients were included in this analysis. In the multivariable model, infant age group, presence of comorbidities, fever, vomiting, seizures and higher absolute neutrophil count were associated with an increased risk of developing severe/critical COVID-19 infection. The presence of coryza at presentation, higher hemoglobin and platelet count were associated with a decreased risk of severe/critical COVID-19 infection. The AUC (95%CI) generated for this model from the training and validation cohort were 0.96 (0.94, 0.98) and 0.92 (0.86, 0.97), respectively.

CONCLUSION

This predictive model using clinical history and commonly used laboratory values was valuable in estimating the risk of developing a severe/critical COVID-19 infection in hospitalized children. Further validation is needed to provide more insights into its utility in clinical practice.

On-Admission Anemia and Survival Rate in COVID-19 Patients

Anemia often worsens the severity of respiratory illnesses, and few studies have so far elucidated the impact of anemia on COVID-19 infection. This study aimed to evaluate the effect of anemia at admission on the overall survival of COVID-19 patients using accelerated failure time (AFT) models.

This registry-based, single-center retrospective cohort study was conducted in a university hospital in Ilam, the southwest of Iran, between March 2020 and September 2021. AFT models were applied to set the data of 2,441 COVID-19 patients. Performance of AFT models was assessed using Akaike’s information criterion (AIC) and Cox-Snell residual. On-admission anemia was defined as hemoglobin (Hb) concentration <120 g/l in men, <110 g/l in women, and <100 g/l in pregnant women.

The median in-hospital survival times for anemic and non-anemic patients were 27 and 31 days, respectively. Based on the AIC and Cox-Snell residual graph, the Weibull model had the lowest AIC and it was the best fitted model to the data set among AFT models. In the adjusted model, the results of the Weibull model suggested that the anemia (adjusted time ratio: 1.04; 95% CI: 1.00-1.08; p = 0.03) was the accelerated factor for progression to death in COVID-19 patients. Each unit of increase in hemoglobin in COVID-19 patients enhanced the survival rate by 4%.

Anemia is an independent risk factor associated with the risk of mortality from COVID-19 infection. Therefore, healthcare professionals should be more sensitive to the Hb level of COVID-19 patients upon admission.

Clinical Features and Treatment Outcome of Coronavirus and Tuberculosis Co-Infected Patients: A Systematic Review of Case Reports

Background

Coronavirus disease 19 (COVID-19) and Mycobacterium tuberculosis (MTB) are among the top ongoing health crises globally. Both cause respiratory diseases, and the clinical presentations are similar. There is no summarized information about cases of COVID-19 patients with concomitant TB infection from different settings. Therefore this review aimed to summerize the clinical features and treatment outcomes of coronavirus and tuberculosis co-infected patients.

Methods

An electronic search of case reports published between 2020 and 2021 was conducted using Google Scholar, PubMed, Scopus, and ScienceDirect. From eligible reports, data were collected for the selected variables. We analyzed the collected information using SPSS version 27 software. Descriptive statistics were computed for the selected variables.

Results

A total of 83 patient histories were collected from 47 case reports. The majority (80%) of the cases were reported for male patients. The mean age was 42.6 years (3 months to 84 years, SD=17.3). Fever was reported in 80% of cases, followed by cough (73.3%) and hypotension (37.1%). Blood cell parameters revealed lymphopenia (52%), lower hemoglobin (30%), elevated CRP (70%), elevated ferritin (28%), and increased D-dimer (23.4%). Treatment outcome is significantly associated with blood cell count results (p-0.044) and a rise in blood inflammatory cytokines(p-0.041). The mean days for viral clearance or negative PCR was 23 days (Range 5-82 days) and the overall mean duration of hospitalization was 27 days. The total death rate was 22.4%. Recovery was reported for 76.6% of cases. Survival status (p-0.613) and disease severity (p-0.68) are not significantly associated with the gender of the participants.

Conclusion

An alteration in blood cell parameters is associated with an unfavorable treatment outcome. There is a higher death rate in COVID-19/TB co-infection. The death is associated with older age, smoking or smoking history, drug abuse, and co-morbidity of non-communicable diseases. Conversely, there is a lower death rate in HIV patients.

A novel reliability-based regression model to analyze and forecast the severity of COVID-19 patients

Background

Coronavirus outbreak (SARS-CoV-2) has become a serious threat to human society all around the world. Due to the rapid rate of disease outbreaks and the severe shortages of medical resources, predicting COVID-19 disease severity continues to be a challenge for healthcare systems. Accurate prediction of severe patients plays a vital role in determining treatment priorities, effective management of medical facilities, and reducing the number of deaths. Various methods have been used in the literature to predict the severity prognosis of COVID-19 patients. Despite the different appearance of the methods, they all aim to achieve generalizable results by increasing the accuracy and reducing the errors of predictions. In other words, accuracy is considered the only effective factor in the generalizability of models. In addition to accuracy, reliability and consistency of results are other critical factors that must be considered to yield generalizable medical predictions. Since the role of reliability in medical decisions is significant, upgrading reliable medical data-driven models requires more attention.

Methods

This paper presents a new modeling technique to specify and maximize the reliability of results in predicting the severity prognosis of COVID-19 patients. We use the well-known classic regression as the basic model to implement our proposed procedure on it. To assess the performance of the proposed model, it has been applied to predict the severity prognosis of COVID-19 by using a dataset including clinical information of 46 COVID-19 patients. The dataset consists of two types of patients’ outcomes including mild (discharge) and severe (ICU or death). To measure the efficiency of the proposed model, we compare the accuracy of the proposed model to the classic regression model.

Results

The proposed reliability-based regression model, by achieving 98.6% sensitivity, 88.2% specificity, and 93.10% accuracy, has better performance than classic accuracy-based regression model with 95.7% sensitivity, 85.5% specificity, and 90.3% accuracy. Also, graphical analysis of ROC curve showed AUC 0.93 (95% CI 0.88–0.98) and AUC 0.90 (95% CI 0.85–0.96) for classic regression models, respectively.

Conclusions

Maximizing reliability in the medical forecasting models can lead to more generalizable and accurate results. The competitive results indicate that the proposed reliability-based regression model has higher performance in predicting the deterioration of COVID-19 patients compared to the classic accuracy-based regression model. The proposed framework can be used as a suitable alternative for the traditional regression method to improve the decision-making and triage processes of COVID-19 patients.

Bioinformatics analysis of potential therapeutic targets for COVID-19 infection in patients with carotid atherosclerosis

BACKGROUND

COVID-19 is a new coronavirus that constitutes a great challenge to human health. At this stage, there are still cases of COVID-19 infection in some countries and regions, in which ischemic stroke (IS) is a risk factor for new coronavirus pneumonia, and patients with COVID-19 infection have a dramatically elevated risk of stroke. At the same time, patients with long-term IS are vulnerable to COVID-19 infection and have more severe disease, and carotid atherosclerosis is an early lesion in IS.

METHODS

This study used human induced pluripotent stem cell (hiPSC)-derived monolayer brain cell dataset and human carotid atherosclerosis genome-wide dataset to analyze COVID-19 infection and carotid atherosclerosis patients to determine the synergistic effect of new coronavirus infection on carotid atherosclerosis patients, to clarify the common genes of both, and to identify common pathways and potential drugs for carotid atherosclerosis in patients with COVID-19 infection RESULTS: Using several advanced bioinformatics tools, we present the causes of COVID-19 infection leading to increased mortality in carotid atherosclerosis patients and the susceptibility of carotid atherosclerosis patients to COVID-19. Potential therapeutic agents for COVID-19 -infected patients with carotid atherosclerosis are also proposed.

CONCLUSIONS

With COVID-19 being a relatively new disease, associations have been proposed for its connections with several ailments and conditions, including IS and carotid atherosclerosis. More patient-based data-sets and studies are needed to fully explore and understand the relationship.

Implication of COVID-19 on Erythrocytes Functionality: Red Blood Cell Biochemical Implications and Morpho-Functional Aspects

Several diseases (such as diabetes, cancer, and neurodegenerative disorders) affect the morpho-functional aspects of red blood cells, sometimes altering their normal metabolism. In this review, the hematological changes are evaluated, with particular focus on the morphology and metabolic aspects of erythrocytes. Changes in the functionality of such cells may, in fact, help provide important information about disease severity and progression. The viral infection causes significant damage to the blood cells that are altered in size, rigidity, and distribution width. Lower levels of hemoglobin and anemia have been reported in several studies, and an alteration in the concentration of antioxidant enzymes has been shown to promote a dangerous state of oxidative stress in red blood cells. Patients with severe COVID-19 showed an increase in hematological changes, indicating a progressive worsening as COVID-19 severity progressed. Therefore, monitored hematological alterations in patients with COVID-19 may play an important role in the management of the disease and prevent the risk of a severe course of the disease. Finally, monitored changes in erythrocytes and blood, in general, may be one of the causes of the condition known as Long COVID.

Elements and COVID-19: A Comprehensive Overview of Studies on Their Blood/Urinary Levels and Supplementation with an Update on Clinical Trials

Simple Summary

COVID-19 is a disease caused by the SARS-CoV-2 coronavirus spreading mainly through person-to-person contact. It has caused millions of deaths around the world and lasting health problems in individuals who have survived the disease. This review concisely summarizes certain issues related to COVID-19 with a focus on elements and gives an update on clinical trials where some minerals will be tested/have been tested alone or in combination with drugs, vitamins, or plant extracts/herbal formulations in COVID-19 patients and in those at higher COVID-19 risk.

Abstract

The current report provides a brief overview of the clinical features, hematological/biochemical abnormalities, biomarkers, and AI-related strategies in COVID-19; presents in a nutshell the pharmacological and non-pharmacological therapeutic options; and concisely summarizes the most important aspects related to sociodemographic and behavioral factors as well as comorbidities having an impact on this disease. It also gives a brief outline of the effect of selected elements on immune response and collects data on the levels of micro-/macro-elements and toxic metals in the blood/urine of SARS-CoV-2 infected patients and on supplementation with minerals in COVID-19 subjects. Moreover, this review provides an overview of clinical trials based on the use of minerals alone or in combination with other agents that can provide effective responses toward SARS-CoV-2 infection. The knowledge compiled in this report lays the groundwork for new therapeutic treatments and further research on biomarkers that should be as informative as possible about the patient’s condition and can provide more reliable information on COVID-19 course and prognosis. The collected results point to the need for clarification of the importance of mineral supplementation in COVID-19 and the relationships of the levels of some minerals with clinical improvement.

Effect of PDCA circulation nursing intervention on prognosis of patients with severe pneumonia

OBJECTIVES

To investigate the effect of a new nursing method combining Plan-Do-Check-Act (PDCA) circulation management and nursing on the prognosis of patients with severe pneumonia.

METHODS

The clinical records of 98 patients treated in the Second Affiliated Hospital of Xi'an Jiaotong University from January 2019 to January 2021 were retrospectively analyzed. Patients were divided into the control group (n=49) and the PDCA group (n=49), which were intervened by routine nursing and PDCA nursing based on routine nursing, respectively, by the same group of nursing staff.

RESULTS

After PDCA care, the nutritional status (body weight; total protein, TP; albumin, ALB) and immune function (immunoglobulin A, IgA; immunoglobulin G, IgG) in the PDCA group were significantly higher than those in the control group. Compared with routine nursing, PDCA care significantly increased the levels of PaO₂ and oxygenation index, and reduced PaCO₂, thus improving patients' ventilation function. The levels of interleukin-6 (IL-6), C-reactive protein (CRP) and procalcitonin (PCT) decreased more significantly in the PDCA group, thus better inhibiting the inflammatory response. The PDCA group also had fewer cases of invasive mechanical ventilation, shorter time of invasive ventilation, noninvasive ventilation, total oxygen therapy, and hospitalization, and better prognosis.

CONCLUSIONS

PDCA care can effectively improve the nursing quality and patients' satisfaction, and better alleviate patients' poor psychological emotions, which is conducive to building a harmonious doctor-patient relationship.

Krebs von den Lungen-6 (KL-6) as a clinical marker for severe COVID-19: A systematic review and meta-analyses

BACKGROUND

Krebs von den Lungen-6 (KL-6) is a molecule that is predominantly expressed by damaged alveolar type II cells, and has been proposed as a marker of COVID-19 and the severity of the disease. Here, we performed a meta-analysis to determine whether KL-6 could be used as a prognostic factor for severe COVID-19.

METHODS

PubMed, Cochrane and Google Scholar were searched until April 20, 2021, and 7 studies were included. KL-6 was considered as the outcome and pooled in meta-analyses.

RESULTS

All included studies compared KL-6 in severe and non-severe patients. Serum KL-6 was higher in severe COVID-19 patients compared to non-severe (n = 6; SMD = 1.25; 95% CI: 0.99-1.5; P < 0.001) and healthy controls (n = 4; SMD = 3.07; 95% CI: 1.36-4.8; P < 0.001).

CONCLUSION

This data collection revealed the potential clinical significance of KL-6 as a non-expensive predictive biomarker in severe COVID-19 and for the categorization of COVID-19 clinical severity.

The outcome of COVID-19 in patients with hematological malignancy

OBJECTIVE

The aim of this study was to examine the effect of coronavirus disease 2019 (COVID-19) on the malignancy-related clinical course and overall survival, and to determine the factors affecting mortality.

METHODS

This retrospective study included 77 patients with hematological cancer and COVID-19. Patients were sub-grouped for analysis as survivors and non-survivors.

RESULTS

COVID-19 was seen more frequently in myeloproliferative neoplasms (MPN), non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) patients. Mortality rate due to COVID-19 was 20.8%. No statistically significant difference was determined between the survivor and non-survivor groups with respect to age and gender, presence of any comorbidity, leukocyte, neutrophil, lymphocyte, and monocyte values. Platelet count and hemoglobin count were significantly lower in the group with mortality than in the group with recovery.

CONCLUSION

It should be kept in mind that low hemoglobin and platelet levels contribute to mortality. In addition, it is important to protect patients with hematological cancer from COVID-19 and undertake effective vaccination due to its mortal course.

State-of-the-Art Review of The Application and Development of Various Methods of Aerosol Therapy

Aerosol therapy is a rapidly developing field of science. Due to a number of advantages, the administration of drugs to the body with the use of aerosol therapy is becoming more and more popular. Spraying drugs into the patient's lungs has a significant advantage over other methods of administering drugs to the body, including injection and oral methods. In order to conduct proper and effective aerosol therapy, it is necessary to become familiar with the basic principles and applications of aerosol therapy under various conditions. The effectiveness of inhalation depends on many factors, but most of all on: the physicochemical properties of the sprayed system, the design of the medical inhaler and its correct application, the dynamics of inhalation (i.e. the frequency of breathing and the volume of inhaled air). It is worth emphasizing that respiratory system diseases are one of the most frequently occurring and fastest growing diseases in the world. Accordingly, in recent years, a significant increase in the number of new spraying devices and pharmaceutical drugs for spraying has appeared on the market. It should also be remembered that the process of spraying a liquid is a complicated and complex process, and its efficiency is very often characterized by the use of micro- and macro parameters (including average droplet diameters or the spectrum of droplet diameter distribution). In order to determine the effectiveness of the atomization process and in the delivery of drugs to the patient's respiratory tract, the analysis of the size of the generated aerosol droplets is most often performed. Based on the proposed literature review, it has been shown that many papers dealt with the issues related to aerosol therapy, the selection of an appropriate spraying device, the possibility of modifying the spraying devices in order to increase the effectiveness of inhalation, and the possibility of occurrence of certain discrepancies resulting from the use of various measurement methods to determine the characteristics of the generated aerosol. The literature review presented in the paper was prepared in order to better understand the spraying process. Moreover, it can be helpful in choosing the right medical inhaler for a given liquid with specific rheological properties. The experimental data contained in this study are of great cognitive importance and may be of interest to entities involved in pharmaceutical product engineering (in particular in the case of the production of drugs containing liquids with complex rheological properties).

A Novel Approach for COVID-19 Patient Condition Tracking: From Instant Prediction to Regular Monitoring

Purpose: The aim of this research is to develop an accurate and interpretable aggregated score not only for hospitalization outcome prediction (death/discharge) but also for the daily assessment of the COVID-19 patient's condition. Patients and Methods: In this single-center cohort study, real-world data collected within the first two waves of the COVID-19 pandemic was used (27.04.2020-03.08.2020 and 01.11.2020-19.01.2021, respectively). The first wave data (1,349 cases) was used as a training set for the score development, while the second wave data (1,453 cases) was used as a validation set. No overlapping cases were presented in the study. For all the available patients' features, we tested their association with an outcome. Significant features were taken for further analysis, and their partial sensitivity, specificity, and promptness were estimated. Sensitivity and specificity were further combined into a feature informativeness index. The developed score was derived as a weighted sum of nine features that showed the best trade-off between informativeness and promptness. Results: Based on the training cohort (median age ± median absolute deviation 58 ± 13.3, females 55.7%), the following resulting score was derived: APTT (4 points), CRP (3 points), D-dimer (4 points), glucose (4 points), hemoglobin (3 points), lymphocytes (3 points), total protein (6 points), urea (5 points), and WBC (4 points). Internal and temporal validation based on the second wave cohort (age 60 ± 14.8, females 51.8%) showed that a sensitivity and a specificity over 90% may be achieved with an expected prediction range of more than 7 days. Moreover, we demonstrated high robustness of the score to the varying peculiarities of the pandemic. Conclusions: An extensive application of the score during the pandemic showed its potential for optimization of patient management as well as improvement of medical staff attentiveness in a high workload stress. The transparent structure of the score, as well as tractable cutoff bounds, simplified its implementation into clinical practice. High cumulative informativeness of the nine score components suggests that these are the indicators that need to be monitored regularly during the follow-up of a patient with COVID-19.

Kynurenine and Hemoglobin as Sex-Specific Variables in COVID-19 Patients: A Machine Learning and Genetic Algorithms Approach

Differences in clinical manifestations, immune response, metabolic alterations, and outcomes (including disease severity and mortality) between men and women with COVID-19 have been reported since the pandemic outbreak, making it necessary to implement sex-specific biomarkers for disease diagnosis and treatment. This study aimed to identify sex-associated differences in COVID-19 patients by means of a genetic algorithm (GALGO) and machine learning, employing support vector machine (SVM) and logistic regression (LR) for the data analysis. Both algorithms identified kynurenine and hemoglobin as the most important variables to distinguish between men and women with COVID-19. LR and SVM identified C10:1, cough, and lysoPC a 14:0 to discriminate between men with COVID-19 from men without, with LR being the best model. In the case of women with COVID-19 vs. women without, SVM had a higher performance, and both models identified a higher number of variables, including 10:2, lysoPC a C26:0, lysoPC a C28:0, alpha-ketoglutaric acid, lactic acid, cough, fever, anosmia, and dysgeusia. Our results demonstrate that differences in sexes have implications in the diagnosis and outcome of the disease. Further, genetic and machine learning algorithms are useful tools to predict sex-associated differences in COVID-19.

COVID-19 induces proatherogenic alterations in moderate to severe non-comorbid patients: A single-center observational study

Patients with COVID-19 can be asymptomatic or present mild to severe symptoms, leading to respiratory and cardiovascular complications and death. Type 2 diabetes mellitus (T2DM) and obesity are considered risk factors for COVID-19 poor prognosis. In parallel, COVID-19 severe patients exhibit dyslipidemia and alterations in neutrophil to lymphocyte ratio (NLR) associated with disease severity and mortality. To investigate whether such alterations are caused by the infection or results from preexisting comorbidities, this work analyzed dyslipidemia and the hemogram profile of COVID-19 patients according to the severity and compared with patients without T2DM or obesity comorbidities. Dyslipidemia, with a marked decrease in HDL levels, and increased NLR accompanied the disease severity, even in non-T2DM and non-obese patients, indicating that COVID-19 causes the observed alterations. Because decreased hemoglobin is involved in COVID-19 severity, and hemoglobin concentration is associated with metabolic diseases, the erythrogram of patients was also evaluated. We verified a drop in hemoglobin and erythrocyte number in severe patients, independently of T2DM and obesity, which may explain in part the need for artificial ventilation in severe cases. Thus, the control of such parameters (especially HDL levels, NLR, and hemoglobin concentration) could be a good strategy to prevent COVID-19 complications and death.

Severe COVID-19 is associated with endothelial activation and abnormal glycosylation of von Willebrand factor in patients undergoing hemodialysis

BACKGROUND

A major clinical feature of severe coronavirus diease 2019 (COVID-19) is microvascular thrombosis linked to endothelial cell activation. Consistent with this, a number of studies have shown that patients with severe COVID-19 have highly elevated plasma levels of von Willebrand Factor (VWF) that may contribute to the prothrombotic phenotype. In the current study, we investigated the extent of endothelial activation in patients receiving hemodialysis who had either mild or severe COVID-19.

METHODS

Plasma VWF, ADAMTS-13, angiopoietin-2 (Ang2), and syndecan-1 levels were determined by ELISA. The sialic acid content of VWF was investigated using a modified ELISA to measure elderberry bark lectin, specific for sialic acid residues, binding to VWF.

RESULTS

Patients receiving hemodialysis with severe COVID-19 had significantly higher plasma levels of VWF and lower ADAMTS-13. VWF levels peaked and were sustained during the first 10 days after positive confirmation of infection. While Ang2 trended toward being higher in severely ill patients, this did not reach significance; however, severely ill patients had significantly higher soluble syndecan-1 levels, with high levels related to risk of death. Finally, higher VWF levels in severely ill patients were correlated with lower VWF sialic acid content.

CONCLUSIONS

Severe COVID-19 in patients undergoing hemodialysis is associated with both acute and sustained activation of the endothelium, leading to alteration of the VWF/ADAMTS-13 axis. Lower VWF sialic acid content represents altered VWF processing and further confirms the disturbance caused to the endothelium in COVID-19.

In-hospital mortality in SARS-CoV-2 stratified by hemoglobin levels: A retrospective study

This study is to estimate in-hospital mortality in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients stratified by hemoglobin (Hb) level. Patients were stratified according to hemoglobin level into two groups, that is, Hb <100 g/L and Hb >100 g/L. A total of 6931 patients were included. Of these, 6377 (92%) patients had hemoglobin levels >100 g/L. The mean age was 44 ± 17 years, and 66% of the patients were males. The median length of overall hospital stay was 13 days [2; 31]. The remaining 554 (8%) patients had a hemoglobin level <100 g/L. Overall mortality was 176 patients (2.54%) but was significantly higher in the group with hemoglobin levels <100 g/L (124, 22.4%) than in the group with hemoglobin levels >100 g/L (52, 0.82%). Risk factors associated with increased mortality were determined by multivariate analysis. The Kaplan-Meier survival analysis showed hemoglobin as a predictor of mortality. Cox proportional hazards regression coefficients for hemoglobin for the HB ≤ 100 category of hemoglobin were significant, B = 2.79, SE = 0.17, and HR = 16.34, p < 0.001. Multivariate logistic regression showed Hb < 100 g/L had a higher cumulative all-cause in-hospital mortality (22.4% vs. 0.8%; adjusted odds ratio [aOR], 0.33; 95% [CI]: [0.20-0.55]; p < 0.001). In this study, hemoglobin levels <100 g/L were found to be an independent predictor of in-hospital mortality.