Illness wellness scale: novel grading system for performance status of patients under surgical care.

BACKGROUND: Grading the illness using clinical parameters is essential for the daily progress of inpatients. Existing systems do not incorporate these parameters holistically. The study was designed to internally validate the illness wellness scale, based upon clinical assessment of the patients requiring surgical care, for their risk stratification and uniformity of communication between health care providers. METHODS: Prospective observational study conducted at a tertiary care hospital. An expert panel devised the scale, and it was modified after feedback from 100 health care providers. A total of 210 patients (150 for internal validation and 60 for inter-observer variability) who required care under the department of surgical disciplines were enrolled. This included patients presenting to surgery OPD, admitted to COVID/non-COVID surgical wards and ICUs, aged ≥16 years. RESULTS: The response rate of the final illness wellness scale was 95% with 86% positive feedback and a mean of 1.7 on the Likert scale for ease of use (one being very easy and five being difficult). It showed excellent consistency and minimal inter-observer variability with the intra-class correlation coefficient (ICC) above 0.9. In the internal validation cohort (n = 150), univariate and multivariable analysis of factors affecting mortality revealed that categorical risk stratification, age ≥ 60 years, presence or absence of co-morbidities especially hypertension and chronic kidney disease significantly affect mortality. CONCLUSIONS: The Illness wellness scale is an effective tool for uniformly communicating between health care professionals and is also a strong predictor of risk stratification and mortality in patients requiring surgical care.

How Did Reskilling During the COVID-19 Pandemic Relate to Entrepreneurship and Optimism? Barriers, Opportunities, and Implications for Equity.

With shorter durations and fewer barriers to entry, reskilling programs may serve as vehicles for social mobility and equity, as well as tools for creating a more adaptive workforce and inclusive economy. Nevertheless, much of the limited large-scale research on these types of programs was conducted prior to the COVID-19 pandemic. Thus, given the social and economic disruptions spurred by the pandemic, our ability to understand the impact of these types of programs in recent labor market conditions is limited. We fill this gap by leveraging three waves of a longitudinal household financial survey collected across all 50 US states during the pandemic. Through descriptive and inferential methods, we explore the sociodemographic characteristics related to reskilling and associated motivations, facilitators, and barriers, as well as the relationships between reskilling and measures of social mobility. We find that reskilling is positively related to entrepreneurship and, for Black respondents, to optimism. Moreover, we find that reskilling is not merely a tool for upward social mobility, but also economic stability. However, our results demonstrate that reskilling opportunities are stratified across race/ethnicity, gender, and socioeconomic status through both formal and informal mechanisms. We close with a discussion of implications for policy and practice.

The impact of COVID-19 on the interpretation of psycho-oncological support trial results: a quasi-experimental approach using the data from the new form of care "Integrated cross-sectoral psycho-oncology (nFC-isPO)".

OBJECTIVE: In addition to the common difficulties of ongoing trials, the COVID-19 pandemic posed several challenges to scientists worldwide and created an additional burden for vulnerable patient groups. In the nFC-isPO of individualised treatment for anxiety and depression in newly diagnosed patients with cancer caregivers (e.g. psycho-oncologists) reported elevated HADS scores in newly enrolled patients after the outbreak of the COVID-19 pandemic. Accordingly, the question arises whether the pandemic affected HADS scores. Therefore, stratified analyses by the time of enrolment (T1) were performed for patients with 12 months of care (T3). METHODS: Patients with 12 months of care (N = 1,140) were analysed. A comparison within the regression discontinuity design according to the time points at which patients completed the baseline (T1) HADS questionnaire was conducted to examine differences between patients recruited before Q2/2020 (pre-pandemic) and after the coronavirus outbreak. Furthermore, mean HADS scores at T1 and T3 for all quarters during the study were compared. RESULTS: Mean T1 and T3 HADS scores of patients with cancer during the pandemic are only slightly higher than those of the pre-pandemic group. No significant treatment effect was observed in either the pre-pandemic (p = 0.5495, Late = 1.7711) or the post-pandemic group (p = 0.9098, LATE=-0.2933). In contrast, the average local treatment effect in the post-pandemic group suggests a minimal decrease in HADS score in the predefined range and thus a positive treatment effect for isPO. Comparison of mean HADS scores at T1 and T3 did not show a large increase by pandemic-related timepoints, however, a decrease of approximately 2-3 points over each quarter at 12 months compared to baseline is observed. CONCLUSION: The existing nFC-isPO care is resilient to crisis and may counteract external influences such as the Corona pandemic. Accordingly, the pandemic had little influence on the fears of patients with cancer in the nFC-isPO. This emphasises that psycho-oncology is vital for the reduction of stress, anxiety and depression in patients with cancer. TRIAL REGISTRATION: The study was registered in the German Clinical Trials Registry on 30 October 2018 under the ID "DRKS00015326".

COVID-19: The efficacy and safety of anticoagulant, glucocorticosteroid therapy and metabolic

Objective: assessment of the efficacy and safety of the use of anticoagulant, glucocorticosteroid, metabolic therapy in patients with COVID-19 at the inpatient stage of treatment. Material and methods. In February 2021, a prospective, randomized, single-center, continuous comparative study was organized on the basis of the Gomel City Clinical Hospital No. 3, which included 827 patients with moderate and severe clinical course of COVID-19. Results. Stratification of the risks of an unfavorable outcome in patients with moderate and severe clinical course of COVID-19 made it possible to optimize treatment, with the selection of optimal doses of anticoagulant and glucocorticosteroid therapy, which led to an increase in patient survival. A high level of blood lactate reflects the degree of damage to the lung tissue, the severity of the course of the disease and requires an increase in the dose of anticoagulant therapy. The use of thiotriazoline effectively reduces the level of lactate, which makes it possible to restore the energy balance of the cell. Conclusion. The use of therapeutic (intermediate) doses of anticoagulant and optimal glucorticosteroid therapy in patients at high risk of poor outcomes with moderate and severe clinical course of COVID-19, can increase the survival rate from 82.1 to 96.8%, p<0.0001. The appointment of anticoagulant therapy was complicated by "minor" bleeding in 2.13% in the main group, in 2.11% in the control group, p>0.05, and the use of glucocorticosteroids was complicated by newly diagnosed diabetes mellitus (2.13% in the main group, 1.81% in the control group, p>0.05), which allows us to consider the therapy used is safe. The use of the metabolic, antioxidant agent thiotriazoline in patients with an LDH level of more than 800 U/L and with a high risk of an unfavorable outcome led to a decrease in LDH within five days of treatment by 447.9 U/L in the main group compared with the control group by 124.0 U/L (p=0.0001), which was accompanied by an improvement in the general condition, increased physical activity, and an earlier start of rehabilitation.Copyright © 2022 by the authors.

The Paths from Middle Class: Evaluation of the Poverty Risks for the Russian Middle Class

The middle class is usually perceived as a main supporter of innovations, source of political stability, and core consumer of goods and services. As a result, its members are traditionally supposed to have high human potential and make a significant contribution to economic growth both in certain country and all over the world, which permanently generates great interest in the issues concerning middle class. However, the main research questions have changed significantly over the last years. The experts both in Russia and abroad highlight the factors that negatively influence the position of the middle class. These are changes in labor market, price growth that outruns the growth of income, increase of tax burden and problems with access to public goods. During COVID-19 pandemic the income has fallen, the risks of unemployment have increased, and the costs of healthcare also have grown. The scholars in different countries underline similar tendencies: middle-class members, who already had to live in an ambiguous world, faced the risks of falling into poverty during the corona crisis. Using data from the Russian Longitudinal Monitor Survey, we evaluate the tracks of middle-class families during 2014-2020 and demonstrate that the problem of poverty affects a part of this social stratum every year. But the share of middle-class members with the income below the poverty line is relatively low and remains largely unaffected by the current corona crisis. © 2023 National Research University Higher School of Economics. All rights reserved.

Gut microbiota profile of COVID-19 patients: Prognosis and risk stratification (MicroCOVID-19 study).

Background: Gut microbiota is intrinsically associated with the immune system and can promote or suppress infectious diseases, especially viral infections. This study aims to characterize and compare the microbiota profile of infected patients with SARS-CoV-2 (milder or severe symptoms), non-infected people, and recovered patients. This is a national, transversal, observational, multicenter, and case-control study that analyzed the microbiota of COVID-19 patients with mild or severe symptoms at home, at the hospital, or in the intensive care unit, patients already recovered, and healthy volunteers cohabiting with COVID-19 patients. DNA was isolated from stool samples and sequenced in a NGS platform. A demographic questionnaire was also applied. Statistical analysis was performed in SPSS. Results: Firmicutes/Bacteroidetes ratios were found to be significantly lower in infected patients (1.61 and 2.57) compared to healthy volunteers (3.23) and recovered patients (3.89). Furthermore, the microbiota composition differed significantly between healthy volunteers, mild and severe COVID-19 patients, and recovered patients. Furthermore, Escherichia coli, Actinomyces naeslundii, and Dorea longicatena were shown to be more frequent in severe cases. The most common COVID-19 symptoms were linked to certain microbiome groups. Conclusion: We can conclude that microbiota composition is significantly affected by SARS-CoV-2 infection and may be used to predict COVID-19 clinical evolution. Therefore, it will be possible to better allocate healthcare resources and better tackle future pandemics.

Your Outpatient has Coronavirus Disease 2019: What Are the Treatment Options in the Current Severe Acute Respiratory Syndrome Coronavirus 2 Variant Climate?

Mutations accumulated by novel Severe Acute Respiratory Syndrome Coronavirus 2 Omicron sublineages contribute to evasion of previously effective monoclonal antibodies for treatment or prevention of Coronavirus Disease 2019 (COVID-19). Other authorized or approved antiviral drugs such as nirmatrelvir/ritonavir, remdesivir, and molnupiravir are, however, predicted to maintain activity against these sublineages and are key tools to reduce severe COVID-19 outcomes in vulnerable populations. A stepwise approach may be taken to target the appropriate antiviral drug to the appropriate patient, beginning with identifying whether a patient is at high risk for hospitalization or other complications of COVID-19. Among higher risk individuals, patient profile (including factors such as age, organ function, and comedications) and antiviral drug access inform suitable antiviral drug selection. When applied in targeted fashion, these therapies serve as a complement to vital ongoing nonpharmaceutical interventions and vaccination strategies that reduce morbidity and maximize protection against COVID-19.

Value of increased soluble suppressor tumorigenicity biomarker 2 (sST2) on admission as an indicator of severity in patients with COVID-19.

BACKGROUND: Soluble suppressor of tumorigenicity-2 (sST2) is a biomarker for heart failure and pulmonary injury. We hypothesize that sST2 could help predict severity of SARS-CoV-2 infections. METHODS: sST2 was analyzed in patients consecutively admitted for SARS-CoV-2 pneumonia. Other prognostic markers were also measured. In-hospital complications were registered, including death, ICU admission, and respiratory support requirements. RESULTS: 495 patients were studied (53% male, age: 57.6±17.6). At admission, median sST2 concentrations was 48.5ng/mL [IQR, 30.6-83.1ng/mL] and correlated with male gender, older age, comorbidities, other severity biomarkers, and respiratory support requirements. sST2 levels were higher in patients who died (n=45, 9.1%) (45.6 [28.0, 75.9]ng/mL vs. 144 [82.6, 319] ng/mL, p<0.001) and those admitted to ICU (n=46, 9.3%) (44.7 [27.5, 71.3] ng/mL vs. 125 [69.0, 262]ng/mL, p<0.001). sST2 levels>210ng/mL were a strong predictor of complicated in-hospital courses, with higher risk of death (OR, 39.3, CI95% 15.9, 103) and death/ICU (OR 38.3, CI95% 16.3-97.5) after adjusting for all other risk factors. The addition of sST2 enhanced the predictive capacity of mortality risk models. CONCLUSIONS: sST2 represents a robust severity predictor in COVID-19 and could be an important tool for identifying at-risk patients who may benefit from closer follow-up and specific therapies.

Postoperative surveillance in cranial and spinal tumor neurosurgery: when is this warranted?

OBJECTIVE: The outbreak of COVID-19 and the sudden increase in the number of patients requiring mechanical ventilation significantly affected the management of neurooncological patients. Hospitals were forced to reallocate already scarce human resources to maximize intensive care unit (ICU) capacities, resulting in a significant postponement of elective procedures for patients with brain and spinal tumors, who traditionally require elective postoperative surveillance on ICU or intermediate care wards. This study aimed to characterize those patients in whom postoperative monitoring is required by analyzing early postoperative complications and associated risk factors. METHODS: All patients included in the analysis experienced benign or malignant cerebral or intradural tumors and underwent surgery between September 2017 and May 2019 at University Hospital Münster, Germany. Patient data were generated from a semiautomatic, prospectively designed database. The occurrence of adverse events within 24 hours and 30 days postoperatively-including unplanned reoperation, postoperative hemorrhage, CSF leakage, and pulmonary embolism-was chosen as the primary outcome measure. Furthermore, reasons and risk factors that led to a prolonged stay on the ICU were investigated. By performing multivariable logistic regression modeling, a risk score for early postoperative adverse events was calculated by assigning points based on beta coefficients. RESULTS: Eight hundred eleven patients were included in the study. Eleven patients (1.4%) had an early adverse event within 24 hours, which was either an unplanned reoperation (0.9%, n = 7) or a pulmonary embolism (0.5%, n = 4) within 24 hours. To predict the incidence of early postoperative complications, a score was developed including the number of secondary diagnoses, BMI, and incision closure time, termed the SOS score. According to this score, 0.3% of the patients were at low risk, 2.5% at intermediate risk, and 12% at high risk (p < 0.001). CONCLUSIONS: Postoperative surveillance in cranial and spinal tumor neurosurgery might only be required in a distinct patient collective. In this study, the authors present a new score allowing efficient prediction of the likelihood of early adverse events in patients undergoing neurooncological procedures, thus helping to stratify the necessity for ICU or intermediate care unit beds. Nevertheless, validation of the score in a multicenter prospective setting is needed.

Impact of the Coronacrisis on the Situation of Different Population Strata

The article analyzes coronacrisis impact on various segments of the population. The purpose is to identify universal and local consequences of the pandemic, as well as the sources to resist new challenges. For the analysis we use data from a FCTAS RAS study in the spring of 2021. The study showed that financial risks for representatives of all social groups are universal in Russian conditions. For disadvantaged segments of the population, for all analyzed reasons, the risks associated with obtaining stable incomes and employment grew. They are also less likely to contract the coronavirus and make significant lifestyle changes. For prosperous Russians, the risks associated with work are significantly lower. This allowed them to quickly adapt to epidemiological restrictions, learn new skills for their work. However, risks of contracting coronavirus and abandoning their usual lifestyle were higher for them. Thus, the ability to quickly adapt to new challenges in modern Russia is determined more by the quality of human potential and level of social protection in the workplace than by the income size. Along with this, potential weakening of positions under impact of the coronavirus and growing international tension for representatives of the upper and middle strata create significant risks of changes in the social structure, as well as transformation of channels and factors of social mobility.

Pandemics, Socioeconomic Gaps, and Macroeconomic Policy: The Ugly Truth Highlighted by COVID-19

Economic stratification lies at the heart of persistent inequities, which have been considerably amplified under COVID-19. To tackle these persistent inequities, a social economics approach and common goods focused policy for at-risk groups are required. Using this approach, this article highlights various past macroeconomic and health policy decisions that have created the conditions for the social and spatial distribution of COVID-19 infections, deaths, and other deleterious outcomes. Additionally, the linkages between health and socioeconomic status are explored, shedding light on the current and likely gaps present given the Covid19 global pandemic. One cannot look at the COVID-19 crisis in a vacuum, but rather how the crisis reflects deeply rooted institutional, structural, and systemic social stratification. This article contributes to the existing literature by analysing it through the lens of occupational prestige. The recognition of social economics and the growing stratification of Americans is necessary to enact healthier policies for all, but especially marginalized communities.

The stratified multi criteria decision making method: An extended version

It often occurs that after a multi-criteria decision is made, the decision maker becomes unsure as to whether they have made the best decision. This doubt arises because the criteria being considered do not carry the same weightings. This instability is relevant to the consideration of possible future events, such as a possible recession following the COVID-19 outbreak, which may affect the criteria weightings. The stratified multi-criteria decision-making method (SMCDM) has been proposed to address this issue. This method suggests the consideration of a number of states in the decision-making process. In each state, the weightings of the criteria are different depending on which event or which combination of events are being considered. The states are associated with transition probabilities that are used to compute the optimal weightings of the criteria. This paper suggests approaches to compute the transition probabilities. Moreover, the consideration of several events in SMCDM results in a great number of states and this would be a time consuming and error prone process. Hence, the incremental enlargement characteristic of the concept of stratification (CST) is added to SMCDM in order to reduce the large numbers of states to a manageable quantity. IEEE

Online Survey Data on Economic Effects of Lockdowns and Post-Stratification Data Adjustment: Evidence from Bulgaria

This contribution aims to discuss an original survey methodology, conceived in lockdown conditions, when face to face interviewing was prohibited and economic and sociological research faced obstacles in obtaining empirical data. An original pseudo-longitudinal Covid-CAWI is conducted in two fully harmonized waves. The basic methodological principles are elucidated along with limitations and advantages within the context of anti-epidemic measures and lockdowns in Bulgaria. The article elaborates the steps of data cleaning, conducted as an essential pre-processing step to high level of data quality. Special focus is devoted to posterior data optimization, using post-stratification adjustments. A comparison between weighted and unweighted data on economic effects is analysed. The paper contributes to the scientific debate on methodology insofar as online surveys become the one and only research opportunity for quantitative research in a crisis situation. The presented analysis of subsequent optimization procedures in Internet studies aims to open a discussion, especially in the context of socioeconomic research in a crisis situation where there are physical distance constraints. The data from the Covid-CAWI survey will be available for open access, so all interested in research may analyse the effects of the pandemic on social and economic life and debate on survey methodology. © 2023, University of National and World Economy. All rights reserved.

Editorial: Consequences of the Corona crisis for social inequalities in Germany

The possible consequences of the Corona crisis for social inequalities have received a lot of attention in public as well as scientific debates. On the one hand, concerns have been raised that the pandemic intensified pre-existing patterns of social inequality. On the other hand, the crisis has also been seen as an opportunity for social change and a renegotiation of social relationships. Complementing previous research that focused on the immediate consequences of the pandemic, this Special Issue is devoted to its longer-term effects. It unites six theory-guided empirical studies that use qualitative and quantitative longitudinal data to study changes in social inequality in the course of the pandemic in different life domains. Overall, the results do not show a universal trend of increased inequalities. While changes in different life domains occurred, such as better grading for students, intensified strong ties in families or increased social trust, there is only limited evidence of changes in social inequalities. In general, a complex picture of effects, consequences and concomitants of the pandemic appears. © 2023 Nomos Verlagsgesellschaft mbH und Co. All rights reserved.

Using NEWS2 to triage newly admitted patients with COVID-19.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has spread globally and caused a major worldwide health crisis. Patients who are affected more seriously by COVID-19 usually deteriorate rapidly and need further intensive care. AIMS AND OBJECTIVES: We aimed to assess the performance of the National Early Warning Score 2 (NEWS2) as a risk stratification tool to discriminate newly admitted patients with COVID-19 at risk of serious events. DESIGN: We conducted a retrospective single-centre case-control study on 200 unselected patients consecutively admitted in March 2020 in a public general hospital in Wuhan, China. METHODS: The following serious events were considered: mortality, unplanned intensive care unit (ICU) admission, and non-invasive ventilation treatment. Receiver operating characteristic (ROC) analysis and logistic regression analysis were used to quantify the association between outcomes and NEWS2. RESULTS: There were 12 patients (6.0%) who had serious events, where 7 patients (3.5%) experienced unplanned ICU admissions. The area under the ROC curve (AUROC) and cut-off of NEWS2 for the composite outcome were 0.83 and 3, respectively. For patients with NEWS2 ≥ 4, the odds of being at risk for serious events was 16.4 (AUROC = 0.74), while for patients with NEWS2 ≥ 7, the odds of being at risk for serious events was 18.2 (AUROC = 0.71). CONCLUSIONS: NEWS2 has an appropriate ability to triage newly admitted patients with COVID-19 into three levels of risk: low risk (NEWS2 = 0-3), medium risk (NEWS2 = 4-6), and high risk (NEWS2 ≥ 7). RELEVANCE TO CLINICAL PRACTICE: Using NEWS2 may help nurses in early identification of at-risk COVID-19 patients and clinical nursing decision-making. Using NEWS2 to triage new patients with COVID-19 may help nurses provide more appropriate level of care and medical resources allocation for patients safety.

Lung Ultrasound Findings Associated With COVID-19 ARDS, ICU Admission, and All-Cause Mortality.

BACKGROUND: As lung ultrasound (LUS) has emerged as a diagnostic tool in patients with COVID-19, we sought to investigate the association between LUS findings and the composite in-hospital outcome of ARDS incidence, ICU admission, and all-cause mortality. METHODS: In this prospective, multi-center, observational study, adults with laboratory-confirmed SARS-CoV-2 infection were enrolled from non-ICU in-patient units. Subjects underwent an LUS evaluating a total of 8 zones. Images were analyzed off-line, blinded to clinical variables and outcomes. A LUS score was developed to integrate LUS findings: ≥ 3 B-lines corresponded to a score of 1, confluent B-lines to a score of 2, and subpleural or lobar consolidation to a score of 3. The total LUS score ranged from 0-24 per subject. RESULTS: Among 215 enrolled subjects, 168 with LUS data and no current signs of ARDS or ICU admission (mean age 59 y, 56% male) were included. One hundred thirty-six (81%) subjects had pathologic LUS findings in ≥ 1 zone (≥ 3 B-lines, confluent B-lines, or consolidations). Markers of disease severity at baseline were higher in subjects with the composite outcome (n = 31, 18%), including higher median C-reactive protein (90 mg/L vs 55, P < .001) and procalcitonin levels (0.35 µg/L vs 0.13, P = .033) and higher supplemental oxygen requirements (median 4 L/min vs 2, P = .001). However, LUS findings and score did not differ significantly between subjects with the composite outcome and those without, and were not associated with outcomes in unadjusted and adjusted logistic regression analyses. CONCLUSIONS: Pathologic findings on LUS were common a median of 3 d after admission in this cohort of non-ICU hospitalized subjects with COVID-19 and did not differ among subjects who experienced the composite outcome of incident ARDS, ICU admission, and all-cause mortality compared to subjects who did not. These findings should be confirmed in future investigations. The study is registered at Clinicaltrials.gov (NCT04377035).

Effective prognostic and clinical risk stratification in COVID-19 using multimodality biomarkers.

In acute coronavirus disease 19 (COVID-19) patients, effective clinical risk stratification has important implications on treatment and therapeutic resource distribution. This article reviews the evidence behind a wide range of biomarkers with prognostic value in COVID-19. Patient characteristics and co-morbidities, such as cardiovascular and respiratory diseases, are associated with increased mortality risk. Peripheral oxygen saturation and arterial oxygenation are predictive of severe respiratory compromise, whereas risk scores such as the 4C-score enable multi-factorial prognostic risk estimation. Blood tests such as markers of inflammation, cardiac injury and d-dimer and abnormalities on electrocardiogram are linked to inpatient prognosis. Of the imaging modalities, lung ultrasound and echocardiography enable the bedside assessment of prognostic abnormalities in COVID-19. Chest radiograph (CXR) and computed tomography (CT) can inform about prognostic pulmonary pathologies, whereas cardiovascular CT detects high-risk features such as coronary artery and aortic calcification. Dynamic changes in biomarkers, such as blood tests, CXR, CT and electrocardiogram findings, can further inform about disease severity and prognosis. Despite the vast volumes of existing evidence, several gaps exist in our understanding of COVID-19 biomarkers. First, the pathophysiological basis on which these markers can foretell prognosis in COVID-19 remains poorly understood. Second, certain under-explored tests such as thoracic impedance assessment and cardiovascular magnetic resonance imaging deserve further investigation. Lastly, the prognostic values of most biomarkers in COVID-19 are derived from retrospective analyses. Prospective studies are required to validate these markers for guiding clinical decision-making and to facilitate their translation into clinical management pathways.

Integrating AI/ML Models for Patient Stratification Leveraging Omics Dataset and Clinical Biomarkers from COVID-19 Patients: A Promising Approach to Personalized Medicine.

The COVID-19 pandemic has presented an unprecedented challenge to the healthcare system. Identifying the genomics and clinical biomarkers for effective patient stratification and management is critical to controlling the spread of the disease. Omics datasets provide a wealth of information that can aid in understanding the underlying molecular mechanisms of COVID-19 and identifying potential biomarkers for patient stratification. Artificial intelligence (AI) and machine learning (ML) algorithms have been increasingly used to analyze large-scale omics and clinical datasets for patient stratification. In this manuscript, we demonstrate the recent advances and predictive accuracies in AI- and ML-based patient stratification modeling linking omics and clinical biomarker datasets, focusing on COVID-19 patients. Our ML model not only demonstrates that clinical features are enough of an indicator of COVID-19 severity and survival, but also infers what clinical features are more impactful, which makes our approach a useful guide for clinicians for prioritization best-fit therapeutics for a given cohort of patients. Moreover, with weighted gene network analysis, we are able to provide insights into gene networks that have a significant association with COVID-19 severity and clinical features. Finally, we have demonstrated the importance of clinical biomarkers in identifying high-risk patients and predicting disease progression.

Systematic lung ultrasound in Omicron-type vs. wild-type COVID-19.

AIMS: Preliminary data suggested that patients with Omicron-type-Coronavirus-disease-2019 (COVID-19) have less severe lung disease compared with the wild-type-variant. We aimed to compare lung ultrasound (LUS) parameters in Omicron vs. wild-type COVID-19 and evaluate their prognostic implications. METHODS AND RESULTS: One hundred and sixty-two consecutive patients with Omicron-type-COVID-19 underwent LUS within 48 h of admission and were compared with propensity-matched wild-type patients (148 pairs). In the Omicron patients median, first and third quartiles of the LUS-score was 5 [2-12], and only 9% had normal LUS. The majority had either mild (≤5; 37%) or moderate (6-15; 39%), and 15% (≥15) had severe LUS-score. Thirty-six percent of patients had patchy pleural thickening (PPT). Factors associated with LUS-score in the Omicron patients included ischaemic-heart-disease, heart failure, renal-dysfunction, and C-reactive protein. Elevated left-filling pressure or right-sided pressures were associated with the LUS-score. Lung ultrasound-score was associated with mortality [odds ratio (OR): 1.09, 95% confidence interval (CI): 1.01-1.18; P = 0.03] and with the combined endpoint of mortality and respiratory failure (OR: 1.14, 95% CI: 1.07-1.22; P < 0.0001). Patients with the wild-type variant had worse LUS characteristics than the matched Omicron-type patients (PPT: 90 vs. 34%; P < 0.0001 and LUS-score: 8 [5, 12] vs. 5 [2, 10], P = 0.004), irrespective of disease severity. When matched only to the 31 non-vaccinated Omicron patients, these differences were attenuated. CONCLUSION: Lung ultrasound-score is abnormal in the majority of hospitalized Omicron-type patients. Patchy pleural thickening is less common than in matched wild-type patients, but the difference is diminished in the non-vaccinated Omicron patients. Nevertheless, even in this milder form of the disease, the LUS-score is associated with poor in-hospital outcomes.

CHINA'S SOCIAL CREDIT SYSTEM: DYSTOPIA OR PUBLIC WELFARE FACTOR

This article analyses China's social credit system, a digital sociotechnical phenomenon that assesses the reliability of people, companies, public organizations, and government institutions through reward-punishment mechanisms. It is aimed to encourage more honest and law-abiding behaviour to improve trust and quality of life in Chinese society. The article examines the evolution of social scoring systems in China in historical retrospect, beginning with the archival systems of the Han Dynasty and ending with the immediate predecessor of social credit, the so-called 'morality files.' The article describes the draft of the social credit system adopted in 2014 and its goals. It is shown that the Chinese government views the system as one of the main solutions to society's social problems. It is proved that the social credit system is also an effective regulatory measure, especially in emergency situations such as the COVID-19 pandemic. The analysis considers the system as a category of social stratification and as a factor in exacerbating inequality, since people with higher levels of education and higher status tend to change their behaviour significantly in response to initiatives of the social credit system. It is concluded that this mechanism allows the state, through positive reinforcement based on indirect incentives, to manipulate citizens to act unconsciously in favour of an established social ideal. It is shown that despite the negative assessment of the Chinese social credit system by researchers as violating the democratic principles and rights of citizens, the system is supported by a large part of the PRC population, which has abandoned privacy in favour of public safety. However, the reasons for the popularity of social credit systems in China, along with cultural and historical preconditions, are censorship and state propaganda. © 2022 National Research University Higher School of Economics. All rights reserved.