PREDICTION OF MORTALITY USING CLUSTERS BASED ON CLINICAL AND LAB PARAMETERS: DATA FROM 2072 PATIENTS FROM INSPIRE COHORT

BackgroundLupus is a heterogenous diseases which results in significant premature mortality. Most studies have evaluated risk factors for lupus mortality using regression models which considers the phenotype in isolation. Identifying clusters of patients on the other hand may help overcome the limitations of such analyses.ObjectivesThe objectives of this study were to describe the causes of mortality and to analyze survival across clusters based on clinical phenotype and autoantibodies in patients of the Indian SLE Inception cohort for Research (INSPIRE)MethodsOut of all patients, enrolled in the INSPIRE database till March 3st 2022, those who had <10% missing variables in the clustering variables were included in the study. The cause of mortality and duration between the recruitment into the cohort and mortality was calculated. Agglomerative unsupervised hierarchical cluster analysis was performed using 25 variables that define SLE phenotype in clinical practice. The number of clusters were fixed using the elbow and silhouette methods. Survival rates were examined using Cox proportional hazards models: unadjusted, adjusted for age at disease onset, socio-economic status, steroid pulse, CYC, MMF usage and cluster of the patients.ResultsIndian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting.Out of 2211 patients in the cohort, 2072 were included into the analysis. The median (IQR) age of the patients was 26 (20-33) years and 91.7% were females. There were 288 (13.1%) patients with juvenile onset lupus. The median (range) duration of follow up of the patients was 37 (6-42) months. There were 170 deaths, with only 77 deaths occurring in a health care setting. Death within 6 months of enrollment occured in in 80 (47.1%) patients. Majority (n=87) succumbed to disease activity, 23 to infections, 24 to coexisting disease activity and infection and 21 to other causes. Pneumonia was the leading cause of death (n=24). Pneumococcal infection led to death in 11 patients and SARS-COV2 infection in 7 patients. The hierarchical clustering resulted in 4 clusters and the characteristics of these clusters are represented in a heatmap (Figure-1A,B). The mean (95% confidence interval [95% CI] survival was 39.17 (38.45-39.90), 39.52 (38.71-40.34), 37.73 (36.77-38.70) and 35.80 (34.10-37.49) months (p<0.001) in clusters 1, 2, 3 and 4, respectively with an HR (95% CI) of 2.34 (1.56, 3.49) for cluster 4 with cluster 1 as reference(Figure 1C). The adjusted model showed an HR (95%CI) for cluster 4 of 2.22 (1.48, 3.22) with an HR(95%CI) of 1.78 (1.29, 2.45) for low socioeconomic status as opposed to a high socioeconomic status (Table 1).ConclusionIndian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting. Disease activity as determined by the traditional activity measures may not be sufficient to understand the true magnitude of organ involvement resulting in mortality. Clinically relevant clusters can help clinicians identify those at high risk for mortality with greater accuracy.Table 1.Univariate and multivariate Cox regression models predicting mortalityUnivariateMultivariateVariablesHazard ratio (95% Confidence interval)P valueHazard ratio (95% Confidence interval)P valueCluster1Reference-Reference-20.87 (0.57, 1.34)0.5320.89 (0.57, 1.38)0.59831.22 (0.81, 1.84)0.3371.15 (0.76, 1.73)0.51342.34 (1.56, 3.49)<0.0012.22(1.48, 3.22)<0.001Socioeconomic statusLower1.78 (1.29, 2.45)<0.001Pulse steroidYes1.6 (0.99, 2.58)0.051MMFYes0.71 (0.48, 1.05)0.083CYCYes1.42 (0.99, 2.02)0.052Proliferative LNYes0.99 (0.62, 1.56)0.952Date of birth age0.99 (0.98, 1.01)0.657CYC- cyclophosphamide, MMF- Mycophenolate mofetilFigure 1.A. Agglomerative clustering dendrogram depicting the formation of four clusters. B.Heatmap depicting distribution of variables used in clustering C. Kaplan-Meier curve showing the survival function across the 4 clusters[Figure omitted. See PDF]REFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsNone eclared.

Respiratory virus coinfections with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) continue to be rare one year into the coronavirus disease 2019 (COVID-19) pandemic in Alberta, Canada (June 2020-May 2021).

To assess the burden of respiratory virus coinfections with severe acute respiratory coronavirus virus 2 (SARS-CoV-2), this study reviewed 4,818 specimens positive for SARS-CoV-2 and tested using respiratory virus multiplex testing. Coinfections with SARS-CoV-2 were uncommon (2.8%), with enterovirus or rhinovirus as the most prevalent target (88.1%). Respiratory virus coinfection with SARS-CoV-2 remains low 1 year into the coronavirus disease 2019 (COVID-19) pandemic.

New Onset Diabetes and Acute Pancreatitis- A Sequela of Long COVID?

Introduction: The association between worse COVID-19 outcomes and diabetes has been well-established in the literature. However, with more cases of new-onset diabetes and pancreatitis being reported with or after COVID-19 infection, it poses the question if there is a causal relationship between them. Case Description: 31 y/o female with COVID-19 infection 4-6 weeks ago with moderate symptoms (not requiring hospital admission or monoclonal ab), presented to ED with bandlike epigastric pain radiating to back, which is worsened with food, associated with nausea, vomiting, polyuria, and fatigue. Workup showed lipase 232, AST 180, ALT 256. Blood glucose was 281 and HbA1c was 12. CT A/P showed post cholecystectomy status, normal pancreas with mesenteric adenitis. MRCP showed hepatic steatosis with trace fluid around the pancreas s/o inflammation, and no evidence of choledocholithiasis or biliary dilatation. She denied alcohol use and autoimmune workup for pancreatitis was unremarkable. Islet cell antibodies were negative. The patient improved with fluid resuscitation and was discharged home on insulin with plans to transition to oral agents outpatient. Discussion(s): Long COVID is defined as a range of conditions or symptoms in patients recovering from COVID-19, lasting beyond 4 weeks after infection. A retrospective cohort study showed increased new-onset diabetes incidence in patients after COVID-19. This was redemonstrated in a systematic review and meta-analysis that showed a 14.4% increased proportion of new diagnoses of diabetes in patients hospitalized with COVID-19. Possible pathophysiology that have been attributed to this include undiagnosed pre-existing diabetes, hyperglycemia secondary to acute illness and stress from increased inflammatory markers during the cytokine storm, the effect of viral infections on the pancreas, and concurrent steroid use in patients with severe respiratory disease. The binding of SARS-CoV-2 to ACE2 receptors is thought to the other mechanism by which COVID can cause pancreatitis and hyperglycemia. Study showed increased lipase and amylase levels in patients with COVID and the increase in serum levels was proportional to the severity of the disease. Patients who died due to COVID-19 were also found to have degeneration of the islet cells. While, several studies have showed new onset diabetes and pancreatitis during an active COVID infections, we need larger cohort studies to comment on its true association or causation, especially in patients with long COVID symptoms. As more cases of new onset diabetes and pancreatitis with COVID-19 are being reported, there may be a need for more frequent blood sugar monitoring during the recovery phase of COVID-19.Copyright © 2023

Impact of COVID-19 Lockdown on Ambient Air Quality in the Southwest Coastal Urban Regions of India

The rapid growth of urban areas and population as well as associated development over recent decades have been a major factor controlling ambient air quality of the urban environment in Kerala (India). Being located at the southwestern fringe of the Indian peninsula, Kerala is one of the regions that has been significantly influenced by the activities in the Indian Ocean. The present study focuses on the effect of the COVID-19 lockdown (in 2021) on ambient air quality in the selected coastal metropolitan areas of Kerala. Although previous research studies reported improvement in ambient air quality in Kerala during the lockdown period, this study demonstrates the potential of onshore transport of air pollutants in controlling the air quality of coastal urban regions during the lockdown period. Data from the ambient air quality monitoring stations of the Kerala State Pollution Control Board in the urban areas of Thiruvananthapuram (TM), Kollam (KL), Kozhikode (KZ), and Kannur (KN) are used for the analysis. Temporal variation in the concentration of air pollutants during the pre-lockdown (PRLD), lockdown (LD), and post-lockdown (PTLD) periods (i.e., 1 March to 31 July) of 2021 is examined to assess the effect of lockdown measures on the National Air Quality Index (AQI). Results indicate a significant decline in the levels of air pollutants and subsequent improvement in air quality in the coastal urban areas. All the effect of lockdown measures has been evident in the AQI, an increase in the concentration of different pollutants including CO, SO2, and NH3 during the LD period suggests contributions from multiple sources including onshore transport due to marine traffic and transboundary transport. © 2023, The Author(s) under exclusive licence to Institute of Earth Environment, Chinese Academy Sciences.

Targeting viral ORF3a protein: A new approach to mitigate COVID- 19 induced Immune cell apoptosis and associated respiratory complications

Infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a growing concern to the global well-being of the public at present. Different amino acid mutations alter the biological and epidemiological characteristics, as well as immune resistance of SARS-CoV-2. The virus-induced pulmonary impairment and inflammatory cytokine storm are directly related to its clinical manifestations. But, the fundamental mechanisms of inflammatory responses are found to be the reason for the death of immune cells which render the host immune system failure. Apoptosis of immune cells is one of the most common forms of programmed cell death induced by the virus for its survival and virulence property. ORF3a, a SARS-CoV-2 accessory viral protein, induces apoptosis in host cells and suppress the defense mechanism. This suggests, inhibiting SARS-CoV-2 ORF3a protein is a good therapeutic strategy for the treatment in COVID-19 infection by promoting the host immune defense mechanism.Copyright © 2023 Tabriz University of Medical Sciences. All rights reserved.

THE ROLE OF VACCINES IN PUBLIC HEALTH

The development and usage of vaccines depend on the assessment of their benefits and risks, primarily by regulatory bodies as well as by physicians and patients. The immunization programs have helped to increase life expectancy, reduce parental fears of life-threatening childhood diseases, eradication of certain destructive epidemics from the community, and pecuniary savings by prevention of disabilities and diseases. Different types of vaccines are currently in use against various life-threatening diseases and those which have the potential of emerging in previously unaffected regions of the world. For certain globally infectious diseases like Yellow Fever, Japanese Encephalitis, Dengue, Influenza, Pneumonia, Rotaviral Gastroenteritis and Hepatitis B, effective human vaccines have already been developed, while for Gonorrhoea, Melioidosis and Tuberculosis (apart from the BCG vaccine) several effective vaccines are in development. Research advancements and most modern technologies are being applied in the development of several modern vaccines through the support of proteomics, genomics, comparative genomics, structural vaccinology, transcriptomics, mRNA based technologies and most recently vaccinomics. The rate of vaccine refusal or delay has been reported to increase in developed countries due to several reasons, leading to variation in vaccine coverage rates and reemergence of vaccinepreventable diseases. Use of combination vaccines increases vaccination rates, provide better coverage and timeliness of vaccination, improve the efficiency of healthcare practice, and reduce costs for the healthcare system. Veterinary vaccines are important for animal health and welfare, food production and public health by preventing animal diseases, reducing transmission of zoonotic and food borne infections to people and finally by enhancing the efficiency of food production. According to WHO, the pandemic COVID-19 is a serious threat to our health and well-being. Recently different countries have developed and are still developing several vaccines in order to combat this lifethreatening disease. Currently, while widespread vaccination is the only strategy that is effective in preventing the transmission of COVID-19, questions remain about the degree and duration of protection that will be offered from the COVID-19 vaccines. Recent studies report the emergence of an anti-vaccination culture among public and its spread through social media, which consequently may result in reduction of herd immunity and the spread of infectious diseases. © 2022 by Nova Science Publishers, Inc.

Not just a complication, can be an initial presentation in COVID 19 A case report

Background: The coronavirus disease 2019 (COVID-19) infection caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is sweeping across the Globe and may be complicated with a wide range of secondary bacterial and fungal co-infections during the course of illness. Here we report a case of severe COVID 19 patient co-infected with pulmonary aspergillosis. Case Study: A 56 year old male patient presented with cough, dyspnea and generalized weakness since 3 days, streaky hemoptysis since a day, with uncontrolled diabetes mellitus of HBA1c8.2% and RAT positive covid-19 illness. HRCT thorax was done which showed diffuse, dense illdefined ground glass oapacities with air bronchograms involving all the segments of bilateral lower lobes and periphery of upper lobes with CORADS 5 Category and CT severity score - 16/25. Also noted reversed halo sign in right upper lobe, hence possibility of angioinvasive fungal infections (Mucormycosis/ aspergillosis) was considered.Patient was treated with Covid-19 guidelines as per Government of Karnataka. Also started with oral Posaconazole in view of CT findings. His general condition continued to deteriorate and despite all the efforts he succumbed to the illness within 28hours after admission. After taking written informed consent from the patient's attenders, we went ahead doing transthoracic biopsy from right upper lobe after his death which showed pulmonary aspergillosis. Discussion: Covid 19 associated pulmonary aspergillosis is commonly seen in immunocompromised individuals including uncontrolled diabetes mellitus, chemotherapy, hematological and other malignancies, organ transplantation, and corticosteroid therapy. Conclusion: Our case report highlights the fact that COVID 19 infection may expose the patients to a greater risk of developing opportunistic co-infections even at presentation which may lead to worse outcomes.

The Significance of Coordinated Research Against SARS-CoV-2

With many unanswered questions about SARS-CoV-2, the research community needs to immediately prioritize research areas in the fight against the current COVID-19 pandemic. An accelerated and coordinated multidisciplinary research effort is needed from the wider scientific community in many sectors from vaccine and antiviral development to digital technology. This mini-review highlights key research opportunities such as vaccine development, diagnostics, antiviral masks, environmental transmission and antiviral treatments, and outlines how systematic efforts can be focused in these key areas. Some alternate strategies such as the use of novel nanostructured surfaces to slow and prevent the spread of COVID-19 are presented. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Trends in Outpatient Hematology Clinic Visits Duringthe First Wave of the COVID-19 Pandemic: Datafrom an Academic Hospital in South India

Introduction: The challenges to the care of hematological disordersin India is considerable;compounded by the huge population andinadequate resources for patient management. The coronavirus disease 2019 (COVID-19) pandemic has further affected healthcaredelivery in India. With the number of cases on the rise and with themajority of health care focused on fighting COVID-19;there is aconcern that care of non-COVID diseases could be affected. Thisimpact is likely more profound in patients with hematological diseases (both benign and malignant) given the immunosuppression dueto the disease and its treatment.Aims &Objectives: The objective of this study was to identify thetrend and challenges to non-COVID care in patients with hematological diseases at our academic setup.Materials &Methods: We conducted a cross-sectional, prospective,descriptive study of hematology outpatient visits from October 1stthrough December 31, 2020. Patients visiting the service wereinterviewed face to face or contacted telephonically through a questionnaire with their responses recorded into a computer-based form. Atelephonic survey was done from March 1st to March 31, 2021 torecord status and vaccination. Institutional Ethics Committeeapproval was taken. Descriptive statistics were used for analysis.Result: A total of 505 patients were interviewed in this period. 15(2.9%) patients opted for teleconsultation. Baseline characteristic ofpatients attending our hematology service (Benign &MalignantHematology) are detailed in Table 1a. Patients consulted a median of2 centers before committing to their hematology care. Many [482(95.4%)] developed unrelated complaints for which the patients didnot opt for a consultation. There were 8 patients who tested positivefor COVID in this period. Three (37.5%) continued COVID care atour center and 5 in the government center. 158(31.3%) patientstransferred their hematology non-covid care from other centers to oursetup. The changes to clinical care are tabulated in Table 1b. Therewere 20 deaths in this period.Conclusions: In our analysis, transfer from the primary care providerwas the most common change in outpatient hematology practice.Despite a perception of compromise in care and vaccine hesitancy,most patients received the planned care and 25% received theirvaccination despite the data collected in the first months of vaccination. Deferral or discontinuation of treatment, investigations andtransfusions were very few.

Paediatric multisystem inflammatory syndrome associated with COVID-19 infection: A case series

Multisystem Inflammatory Syndrome (MIS) is a newer, rarer and dangerous childhood disease that require early attention and is associated with Coronavirus Disease-2019 (COVID-19) infection. This article reports four clinically ill children of age 6-15 years admitted to Aster CMI hospital, Bengaluru, Karnataka, India, during October and November 2020. The diagnosis was based on elevated laboratory values (D-Dimer, C-reactive Protein (CRP), and Ferritin) and positive COVID-19 antibody test. No infectious aetiologies were identified. All patients presented at Emergency Room (ER) with hypotensive shock and were treated with inotropic support, Intravenous Immunoglobulin (IV-Ig), and steroids. Children responded well to treatment and were discharged within a period of 8-11 days. Clinical characteristics are necessary for understanding more about newly identified paediatric illness.

Machine Learning Approaches to Identify Patient Comorbidities and Symptoms That Increased Risk of Mortality in COVID-19.

Providing appropriate care for people suffering from COVID-19, the disease caused by the pandemic SARS-CoV-2 virus, is a significant global challenge. Many individuals who become infected may have pre-existing conditions that may interact with COVID-19 to increase symptom severity and mortality risk. COVID-19 patient comorbidities are likely to be informative regarding the individual risk of severe illness and mortality. Determining the degree to which comorbidities are associated with severe symptoms and mortality would thus greatly assist in COVID-19 care planning and provision. To assess this we performed a meta-analysis of published global literature, and machine learning predictive analysis using an aggregated COVID-19 global dataset. Our meta-analysis suggested that chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CEVD), cardiovascular disease (CVD), type 2 diabetes, malignancy, and hypertension as most significantly associated with COVID-19 severity in the current published literature. Machine learning classification using novel aggregated cohort data similarly found COPD, CVD, CKD, type 2 diabetes, malignancy, and hypertension, as well as asthma, as the most significant features for classifying those deceased versus those who survived COVID-19. While age and gender were the most significant predictors of mortality, in terms of symptom-comorbidity combinations, it was observed that Pneumonia-Hypertension, Pneumonia-Diabetes, and Acute Respiratory Distress Syndrome (ARDS)-Hypertension showed the most significant associations with COVID-19 mortality. These results highlight the patient cohorts most likely to be at risk of COVID-19-related severe morbidity and mortality, which have implications for prioritization of hospital resources.

Current update on COVID-19 vaccines

Novel Coronavirus, also known as SARS-CoV-2, is an infectious disease that primarily affects the respiratory tract and gastrointestinal tract. The viral spread occurs through respiratory droplets produced while coughing and sneezing. Major vaccine targets for COVID-19 are spike protein, M protein, envelope protein, receptor binding domain, nucleic acids etc. Different mechanisms through which a vaccine can be developed to evoke an immune response include virus inactivated vaccine, live attenuated vaccine, subunit vaccines, virus-like particles, replicating and non-replicating viral vectors and nucleic acid-based vaccines. The mainstay of COVID-19 treatment is supportive and symptomatic therapy with dexamethasone, hydroxychlorquine and anti-viral agents like Darunavir, Ribavirin, Remdesivir, Interferons. Maintaining social distance, personal hygiene, use of N-95 masks aids in limiting the spread of the infection. There is a vital requirement for an ideal and potent vaccine with a favorable beneFit-risk proFile to evoke an immune response against SARS-CoV-2 infection. There are currently 11 approved vaccines in the market of which the PFizer/ BioNTech vaccine have produced the most efFicacy (95%), followed by Moderna (94%), Sputnik (91.6%), Covaxin (90%), Janssen (90%) and Astra Zeneca (70%). Vaccine hesitancy, vaccine-related adverse reactions and the high cost of the vaccine can be a major barrier to public acceptance and global access to the vaccine.

Attacking COVID-19 Progression Using Multi-Drug Therapy for Synergetic Target Engagement.

COVID-19 is a devastating respiratory and inflammatory illness caused by a new coronavirus that is rapidly spreading throughout the human population. Over the past 12 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, has already infected over 160 million (>20% located in United States) and killed more than 3.3 million people around the world (>20% deaths in USA). As we face one of the most challenging times in our recent history, there is an urgent need to identify drug candidates that can attack SARS-CoV-2 on multiple fronts. We have therefore initiated a computational dynamics drug pipeline using molecular modeling, structure simulation, docking and machine learning models to predict the inhibitory activity of several million compounds against two essential SARS-CoV-2 viral proteins and their host protein interactors-S/Ace2, Tmprss2, Cathepsins L and K, and Mpro-to prevent binding, membrane fusion and replication of the virus, respectively. All together, we generated an ensemble of structural conformations that increase high-quality docking outcomes to screen over >6 million compounds including all FDA-approved drugs, drugs under clinical trial (>3000) and an additional >30 million selected chemotypes from fragment libraries. Our results yielded an initial set of 350 high-value compounds from both new and FDA-approved compounds that can now be tested experimentally in appropriate biological model systems. We anticipate that our results will initiate screening campaigns and accelerate the discovery of COVID-19 treatments.

Broad respiratory testing to identify SARS-CoV-2 viral co-circulation and inform diagnostic stewardship in the COVID-19 pandemic.

BACKGROUND: SARS-CoV-2 infection can present with a broad clinical differential that includes many other respiratory viruses; therefore, accurate tests are crucial to distinguish true COVID-19 cases from pathogens that do not require urgent public health interventions. Co-circulation of other respiratory viruses is largely unknown during the COVID-19 pandemic but would inform strategies to rapidly and accurately test patients with respiratory symptoms. METHODS: This study retrospectively examined 298,415 respiratory specimens collected from symptomatic patients for SARS-CoV-2 testing in the three months since COVID-19 was initially documented in the province of Alberta, Canada (March-May, 2020). By focusing on 52,285 specimens that were also tested with the Luminex Respiratory Pathogen Panel for 17 other pathogens, this study examines the prevalence of 18 potentially co-circulating pathogens and their relative rates in prior years versus since COVID-19 emerged, including four endemic coronaviruses. RESULTS: SARS-CoV-2 was identified in 2.2% of all specimens. Parallel broad multiplex testing detected additional pathogens in only 3.4% of these SARS-CoV-2-positive specimens: significantly less than in SARS-CoV-2-negative specimens (p < 0.0001), suggesting very low rates of SARS-CoV-2 co-infection. Furthermore, the overall co-infection rate was significantly lower among specimens with SARS-CoV-2 detected (p < 0.0001). Finally, less than 0.005% of all specimens tested positive for both SARS-CoV-2 and any of the four endemic coronaviruses tested, strongly suggesting neither co-infection nor cross-reactivity between these coronaviruses. CONCLUSIONS: Broad respiratory pathogen testing rarely detected additional pathogens in SARS-CoV-2-positive specimens. While helpful to understand co-circulation of respiratory viruses causing similar symptoms as COVID-19, ultimately these broad tests were resource-intensive and inflexible in a time when clinical laboratories face unprecedented demand for respiratory virus testing, with further increases expected during influenza season. A transition from broad, multiplex tests toward streamlined diagnostic algorithms targeting respiratory pathogens of public health concern could simultaneously reduce the overall burden on clinical laboratories while prioritizing testing of pathogens of public health importance. This is particularly valuable with ongoing strains on testing resources, exacerbated during influenza seasons.