ASSOCIATION OF URIC ACID LEVELS WITH COVID-19 SEVERITY DURING 2020 AND 2021 YEARS

BackgroundThe decrease in uric acid levels attracts more and more attention from clinicians every year [1]. In particular, a factor such as Covid-19 can cause a significant decrease in uric acid due to its increased excretion by the kidneys [2]. This retrospective study aimed to determine changes in the level of uric acid in different years, which allows us to assume the influence of different strains of Covid-19 on uric acid.ObjectivesTo analyze the relationship between uric acid levels through admission to the hospital and Covid-19 severity during 2020 and 2021 years.MethodsOur retrospective study includes 127 hospitalized patients with confirmed Covid-19 in 2021 and 63 patients in 2020 (only patients who didn't receive urate-lowering therapy). Most patients were over 45 years old (84,2% vs 90,5%), women and men almost equally. The severity of Covid-19 we determined by the type and presence of oxygen support ((1) without O2, (2) O2 by mask or nasal cannula, (3) continuous positive airway pressure, (4) positive bi-pressure in the airways or high-flow oxygen, (5) invasive ventilation). A chi-squared test and comparison of means were used.ResultsWe cannot establish the dependence of the uric acid level on the severity of the course of the Covid-19 disease, which is determined by the type of oxygen support in both 2020 and 2021. For example, in 2021, the difference between the least severe type (without O2) and the most severe (invasive ventilation) was almost the same (246.2 vs 277.12 µmol/L), as between O2 by mask or nasal cannula and positive bi-pressure in the airways or high-flow oxygen (257 vs 239.1 µmol/L). However, it was established that in 2020, higher indicators of the level of uric acid were observed for all types of oxygen support. For example, for patients who were without O2, it is higher by 72.95 µmol/L, which is statistically significant. In addition, we analyzed the dependence of the uric acid level on such indicators as the patient's age, the level of lymphocytes, C-reactive protein, and LDH at admission to the hospital. As a result of the analysis, it was found that the dependence is present for the LDH indicator (the lower the LDH, the higher the uric acid: chi-square at the level of 0.05), and for all other indicators, it was absent in 2021. In 2020, a positive relationship between CRP, LDH, and uric acid levels was also observed.ConclusionAlthough there is a trend towards lower uric acid levels in the background of Covid-19, it is not a marker of a severe disease course. The lower uric acid levels in 2021 are likely due to a feature of the strains circulating in 2021 that caused more significant renal excretion of uric acid.References[1]Hu F, Guo Y, Lin J, Zeng Y, Wang J, Li M, Cong L. Association of serum uric acid levels with COVID-19 severity. BMC Endocr Disord. 2021 May 8;21(1):97. DOI: 10.1186/s12902-021-00745-2. PMID: 33964922;PMCID: PMC8106517.[2]Dufour I, Werion A, Belkhir L, Wisniewska A, Perrot M, De Greef J, Schmit G, Yombi JC, Wittebole X, Laterre PF, Jadoul M, Gérard L, Morelle J;CUSL COVID-19 Research Group. Serum uric acid, disease severity, and outcomes in COVID-19. Crit Care. 2021 Jun 14;25(1):212. DOI: 10.1186/s13054-021-03616-3. PMID: 34127048;PMCID: PMC8201458.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

TYPE I INTERFERON SCORE IS ASSOCIATED WITH THE SEVERITY AND POOR PROGNOSIS IN ANTI-MDA5 ANTIBODY-POSITIVE DERMATOMYOSITIS PATIENTS

BackgroundAnti-MDA5 antibody-positive dermatomyositis (anti-MDA5+DM) is a rare autoimmune disease associated with a high mortality rate due to rapid-progressive interstitial lung disease (RP-ILD), particularly in East Asia[1]. MDA5, acts as a cytoplasmic sensor of viral RNA, thus activating antiviral responses including the type I interferon (IFN) signaling pathway[2]. The involvement of type 1 IFN in the pathogenesis of MDA5+DM has been proposed based on the significantly elevated expression of its downstream stimulated genes(ISG) in muscle, skin, lung, and peripheral blood[3;4]. Janus kinase inhibitor, which targets the IFN pathway, combined with glucocorticoid could improve the survival of early-stage MDA5+DM-ILD patients[5]. In clinical practice, there is still an urgent demand for sensitive biomarkers to facilitate clinical risk assessment and precise treatment.ObjectivesThis study aimed to investigate the clinical significance of interferon score, especially IFN-I score, in patients with anti-MDA5+DM.MethodsDifferent subtypes of idiopathic inflammatory myopathy, including anti-MDA5+DM(n=61), anti-MDA5-DM(n=20), antisynthetase syndrome(ASS,n=22),polymyositis(PM,n=6) and immune-mediated necrotizing myopathy(IMNM,n=9), and 58 healthy controls were enrolled.. A multiplex quantitative real-time PCR(RT-qPCR) assay using four TaqMan probes was utilized to evaluate two type I ISGs (IFI44, MX1, which are used for IFN-I score), one type II ISG (IRF1), and one housekeeping gene (HRPT1). Clinical features and disease activity index were compared between high and low IFN-I score groups in 61 anti-MDA5+DM patients. The association between laboratory findings and the predictive value of baseline IFN-I score level for mortality was analyzed.ResultsThe IFN scores were significantly higher in patients with anti-MDA5+DM than in HC (Figure 1A). The IFN-I score correlated positively with serum IFN α(r = 0.335, P =0.008), ferritin (r = 0.302, P = 0.018), and Myositis Disease Activity Assessment Visual Analogue Scale (MYOACT) score(r=0.426, P=0.001). Compared with patients with low IFN-I scores, patients with high IFN-I scores showed increased MYOACT score, CRP, AST, ferritin, and the percentages of plasma cells (PC%) but decreased lymphocyte count, natural killer cell count, and monocyte count. The 3-month survival rate was significantly lower in patients with IFN-I score > 4.9 than in those with IFN-I score ≤ 4.9(72.9% vs. 100%, P=0.044)(Figure 1B).ConclusionIFN score, especially IFN-I score, detected by multiplex RT-qPCR, can be a valuable biomarker for monitoring disease activity and predicting mortality in anti-MDA5+DM patients.References[1]I.E. Lundberg, M. Fujimoto, J. Vencovsky, R. Aggarwal, M. Holmqvist, L. Christopher-Stine, A.L. Mammen, and F.W. Miller, Idiopathic inflammatory myopathies. Nat Rev Dis Primers 7 (2021) 86.[2]G. Liu, J.H. Lee, Z.M. Parker, D. Acharya, J.J. Chiang, M. van Gent, W. Riedl, M.E. Davis-Gardner, E. Wies, C. Chiang, and M.U. Gack, ISG15-dependent activation of the sensor MDA5 is antagonized by the SARS-CoV-2 papain-like protease to evade host innate immunity. Nat Microbiol 6 (2021) 467-478.[3]G.M. Moneta, D. Pires Marafon, E. Marasco, S. Rosina, M. Verardo, C. Fiorillo, C. Minetti, L. Bracci-Laudiero, A. Ravelli, F. De Benedetti, and R. Nicolai, Muscle Expression of Type I and Type II Interferons Is Increased in Juvenile Dermatomyositis and Related to Clinical and Histologic Features. Arthritis Rheumatol 71 (2019) 1011-1021.[4]Y. Ye, Z. Chen, S. Jiang, F. Jia, T. Li, X. Lu, J. Xue, X. Lian, J. Ma, P. Hao, L. Lu, S. Ye, N. Shen, C. Bao, Q. Fu, and X. Zhang, Single-cell profiling reveals distinct adaptive immune hallmarks in MDA5+ dermatomyositis with therapeutic implications. Nat Commun 13 (2022) 6458.[5]Z. Chen, X. Wang, and S. Ye, Tofacitinib in Amyopathic Dermatomyositis–Associated Interstitial Lung Disease. New England Journal of Medicine 381 (2019) 291-293.AcknowledgementsThis work was supported by the National Natural Science Foundation of China [81974251], and Shanghai Hospital Develop ent Center, Joint Research of New Advanced Technology Project [SHDC12018106]Disclosure of InterestsNone Declared.

IDENTIFICATION OF FACTORS ASSOCIATED WITH A WORSE OUTCOME -EXITUS- IN PATIENTS WITH RHEUMATOID ARTHRITIS AND SEVERE INFECTION

BackgroundInfections constitute an important and frequent cause of morbidity and mortality in patients with chronic inflammatory and systemic autoimmune rheumatic diseases. In rheumatoid arthritis (RA), this increased risk has been related to the immune system alterations inherent to the disease, the drugs used to control it (corticosteroids, DMARDs and immunosuppressants) and associated comorbidities. Most studies focus on the search for factors associated with the development of infections but do not explore the worst outcome: patient failure.ObjectivesTo identify factors that help to predict an unfavorable outcome (exitus) after a severe infection in patients with rheumatoid arthritis.MethodsThis study was a retrospective case-control study at a single institution over a 10-year period. Patients with a diagnosis of rheumatoid arthritis with hospital admission for infection from January 1, 2010, to December 31, 2019 (pre-pandemic SARS-COV-2) were selected. The main variable was exitus due to the infectious episode. We collected: age, sex, time of evolution of RA, previous treatment and at the time of admission, number of admissions for infection, location of the infection, comorbidities, and other associated serious diseases. The statistics included a descriptive analysis of the different variables (expressed as median and interquartile range -IR- for quantitative variables and percentages for qualitative variables), and the association study using the χ2 test or Fisher's exact test for qualitative variables, and t-student or Mann-Whitney U and Kruskal Wallis for quantitative variables.ResultsWe obtained 152 patients (71.7% female, 28.3% male), with a total of 214 episodes of admission for infection (115 patients with 1 episode (75.7%), 25 (16.4%) with 2 episodes, 6 being the maximum number of episodes recorded). The median age at admission was 77 years, and the median time of RA evolution was 8 years (IR 4-16). The location of the infection responsible for admission was mainly respiratory and urinary. Forty-eight patients died in the episode (31.6% of the sample, 15 males and 33 females, median age 81.5 years (IR 69.5-86.5)). Comparing the patients with unfavorable outcomes (exitus) with the rest, we only found a statistically significant difference in the number of previous admissions (p=0.011), and in the coexistence of some other serious disease (exitus 85.4%, rest 61.5% p=0.003). There were no differences by sex, age, time of RA evolution, drugs, location of the infection, or comorbidities.ConclusionA history of hospital admission due to infection, and having another serious disease, are factors associated with an unfavorable outcome (exitus) in patients with RA admitted for an infectious process.References[1] Listing J, Gerhold K, Zink A. The risk of infections associated with rheumatoid arthritis, with its comorbidity and treatment. Rheumatology 2013;52(1):53-61.[2] George MD, Baker JF, Winthrop K, Hsu JY, Wu Q, Chen L, et al. Risk for serious infection with low-dose glucocorticoids in patients with Rheumatoid Arthritis: A cohort study. Ann Intern Med. 2020;173(11):870-8.[3] Singh JA, Cameron C, Noorbaloochi S, Cullis T, Tucker M, Christensen R, et al. Risk of serious infection in biological treatment of patients with rheumatoid arthritis: A systematic review and meta-analysis. The Lancet. 2015;386(9990):258-65.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

Liver dysfunction as a respiratory prognostic factor in covid-19 patients.

Respiratory dysfunction is a main clinical symptom of COVID-19. Liver dysfunction is also frequently reported in patients with COVID-19 and considered to be related to a poor prognosis. However, the precise mechanisms behind these findings remain unclear. We investigated the clinical features and prognostic factors related to liver dysfunction in 26 COVID-19 pa-tients. The patients with liver dysfunction had markedly higher WBC, neutrophils, CRP, and frequency of oxygen administration and markedly lower PaO2/FIO2 ratios. The patients with liver dysfunction had longer mean hospital stays. In conclusion, liver dysfunction at hospital admission may be an important prognostic factor for respiratory failure in patients with COVID-19. We must administer intensive care to these patients earlier to inhibit severe disease progression.Copyright ©2021 The Japan Society of Hepatology.

LABORATORY PARAMETERS ASSOCIATED WITH CODIV-19 CYTOKINE STORM DEVELOPMENT

BackgroundSince the end of 2019, physicians became more and more familiar with SARS-CoV-2 infection and the variety of forms in which it may present and evolve. There have been a lot of studies trying to understand and predict why some patients develop a dysregulation of the immune response, with an exaggerated release of pro-inflammatory cytokines, called cytokine storm (1–4). There is scarce evidence in Romania regarding this aspect.ObjectivesThis study aims to verify the correlation between some laboratory parameters and the development of cytokine storm in SARS-CoV-2 infection in a cohort of over 200 patients admitted in a tertiary hospital from Romania, hoping that early identification of these risk factors of progression to a severe form of the disease can bring considerable benefit to patient care.MethodsThis is an analytical, observational, case-control study which includes 219 patients (all COVID-19 hospitalized patients on the Internal Medicine 3 department of Colentina Clinical Hospital, Bucharest, from 01 March 2020 to 1 April 2021). A series of data were collected, the laboratory parameters being the most important, including: albumin, lymphocyte (percentage), neutrophil (absolute value), aspartate aminotransferase, alanine aminotransferase, D-dimers, lactate dehydrogenase (LDH), anionic gap, chloremia, potassium and the BUN:creatinine ratio (BUN - blood urea nitrogen). The laboratory parameters used for the statistical analysis represent the average values of the first 7 days of hospitalization for those who did not develop cytokine storm, respectively until the day of its development, for the others. Patients were classified into these groups, those who developed cytokine storm, respectively those who did not have this complication taking into account the clinical and paraclinical criteria (impairment of respiratory function, elevations of certain markers 2-3 times above the upper limit of normal, those who died as a result of SARS-CoV-2 infection). Then Binary Univariate Logistic Regression was applied in order to verify the individual impact of every laboratory parameter on cytokine storm development. Furthermore, all laboratory parameters were subsequently included in the multivariate analysis, using the backward selection technique to achieve a model as predictive as possible.ResultsWe mention that the analysis of demographic data was previously performed, showing no statistically significant relationship between patient gender, age or comorbidities (history of neoplasm, lung diseases, cardiac pathology, obesity, type II diabetes and hypertension) and their evolution to cytokine storm. After performing binary univariate logistic regression we concluded that 8 of the 13 laboratory analyzes have had a significant change between groups (ferritin, PCR, albumin, Lymphocyte, Neutrophils, TGO, LDH, BUN:creatinine ratio). Only 150 patients were then included in the multivariate analysis. After the analysis, some of the variables lost their statistical significance, the final model including C-reactive protein, neutrophilia, LDH, ferritin and the BUN:creatinine ratio. This model correctly predicts the development of cytokine storm in 88% of cases.ConclusionHigh C-reactive protein, neutrophilia, LDH, ferritin and the BUN:creatinine ratio are risk factors for cytokine storm development and should be monitored in all COVID-19 patients in order to predict their evolution.References[1]Pedersen SF et all. SARS-CoV-2: A storm is raging[2]Mehta P et al. COVID-19: consider cytokine storm syndromes and immunosuppression[3]Hu B et al. The cytokine storm and COVID-19.[4]Caricchio R et al. Preliminary predictive criteria for COVID-19 cytokine stormAcknowledgements:NIL.Disclosure of InterestsNone Declared.

Assessment of serum neopterin levels in patients hospitalized with severe COVID-19

Background: COVID-19 has caused a considerable number of hospital admissions in China since December 2019. Many COVID-19 patients experience signs of acute respiratory distress syndrome, and some are even in danger of dying. Background: to measure the serum levels of D-dimer, Neutrophil-Lymphocyte count ratio (NLR), and neopterin in patients hospitalized with severe COVID-19 in Baghdad, Iraq. And to determine the cut-off values (critical values) of these markers for the distinction between the severe patients diagnosed with COVID-19 and the controls. Materials and methods: In this case-control study, we collect blood from 89 subjects, 45 were severe patients hospitalized in many Baghdad medical centers who were diagnosed with COVID-19 infection, and 44 were apparently healthy subjects as a control. The time of collection is from September 15 th to December 31 th, 2021. The optimal cut-off points (critical values) and prognostic relevance of D-dimer, Neutrophil-Lymphocyte count ratio (NLR), and neopterin were investigated using (ROC) curves analysis. Results: In severe patients hospitalized with COVID-19 the levels of D-dimer, NLR, and neopterin were statistically significantly higher than in control participants (P < 0.005). The D-dimer, NLR, and neopterin tests have areas under the receiver operating characteristic (ROC) curves of 0.920, 0.90, and 0.74 respectively, and their critical values for the differentiation between the severe patients and control were 0.22 micro g/ml, 2.56, and 3.02 nmol/L. Conclusions: D-dimer, NLR, and neopterin levels in sever COVID-19 patients were higher than control, with values of greater than 0.22 micro g/ml, 2.56 and 3.02 nmol/L respectively was linked to a severe COVID-19 infection with good sensitivity and selectivity.

TIME MANAGEMENT AND RISK FACTORS IN LIFE-THREATENING ANCA-VASCULITIS

BackgroundAccuracy of diagnosis and prompt therapeutic intervention are the mainstay in patients with ANCA-associated vasculitis(AAV) suffering from life-threatening complications [1].However, there is no definition of therapeutic window in vital AAV, nor its impact on patient outcome regarding length of hospital stay, intensive care unit(ICU) admission or survival.ObjectivesThe aim of the study is to analyze the process of care from the perspective of time management in vital organ involvement AAV patients and to identify potential risk factors for ICU admission.MethodsA retrospective multicenter study identified AAV patients with life-threatening organ involvement, defined as alveolar hemorrhage, rapidly progressive renal failure, myocarditis and cerebral granuloma. Demographic data was collected. Key time frames were recorded, namely the interval from acute symptom onset to hospital presentation, days until imaging(plain X-ray, cardiac ultrasound, CT-scan), time to therapeutic intervention with corticosteroids or biologic/non-biologic immunosuppression(cyclophosphamide or rituximab) and to renal replacement therapy(RRT) or plasmapheresis. Time to ICU admission, hospital length-of-stay, Birmingham Vasculitis Activity Score(BVAS) were also noted. Statistical analysis was performed using SPSS and Chi-square and Pearson correlation tests were applied.Results66 patients with AAV were enrolled, out of which 17 fulfilled inclusion criteria. Mean age in the study group was 58.6±11.1 years old,10 patients(58.8%) were females and 7 (41.2%) males.11(64.7%) patients were c-ANCA positive, while 6 (35.3%) had p-ANCA and all were diagnosed with AAV prior to life-threatening event. Two patients had COVID-19 triggered AAV.In the study group, the most frequent critical organ suffering was rapidly progressive renal failure(12), followed by alveolar hemorrhages(10), 2 cerebral granulomas and one acute myocarditis. Three patients(17.6%) had more than one vital manifestation. Ten patients(58.8%) had more than three additional non-organ-threatening manifestations. Mean interval from AAV diagnosis to emergency admission was 30.1± 61.1 days, median 3 and from severe episode onset to hospitalization 1.65±0.18 days, median 1. There was only one death in the study group. Three patients were admitted in the ICU in 0.59±1.5 days following hospital presentation and required either RRT or plasma exchange within 2.66 days. Imaging examination was performed unanimously the day upon hospital admission. All patients received corticosteroids in the first 5.95±14.3 days, while immunosuppression was given to 13(76.5%) patients within 11.5±15.5 days from hospitalization.12 patients(70.5%) suffered from associated infections. Mean BVAS(13.6±6.76) correlated to ICU admission(p 0.013, r 0.58).Patients in ICU revealed higher BVAS(22±9.53) versus non-ICU(11.8±4.76).Hospital length of stay was 14.7±10.7 days(median 14) and showed no relationship to the type of severe organ involvement. The need for ICU caring was dominant in males(p 0.05) and confirmed in patients with proteinuria(p 0.012) and at least two major organ damage.ConclusionThis study shows that severity risk factors for potential ICU admission for life-threatening AAV appear to be male gender, proteinuria and the number of affected organs.Moreover, BVAS should be considered a useful tool to predict patients' risk for intensive care management since a higher score indicates a more aggressive disease.However, time to investigational or therapeutic intervention did not correlate to patient outcome in AAV.References[1]Geetha, D., Seo, P. (2011). Life-Threatening Presentations of ANCA-Associated Vasculitis. In: Khamashta, M., Ramos-Casals, M. (eds) Autoimmune Diseases. Springer, London. https://doi.org/10.1007/978-0-85729-358-9_8Acknowledgements:NIL.Disclosure of InterestsNone Declared.

Machine Learning and Laboratory Values in the Diagnosis, Prognosis and Vaccination Strategy of COVID-19

In March 2020, the World Health Organization (WHO) declared a pandemic status for COVID-19 disease caused by SARS-CoV-2 infection. Early diagnosis undoubtedly plays a fundamental role in the management of emergencies for the treatment of infected patients, whose prognosis may benefit from early treatment and containment of contagions in asymptomatic or pauci-symptomatic subjects. To date, the gold-standard technique for diagnosing SARS-CoV-2 infection is the identification of viral genomic material (RNA) by molecular diagnosis. To improve the pandemic management, the need for enhanced diagnostic capacity for SARS-CoV-2 infections soon emerged, with rapid, accurate, and easily accessible methods. Machine learning (ML) models could help define the diagnosis and, in some cases, even the prognosis of COVID-19 patients. This chapter describes ML models based on laboratory tests combined with other biometric parameters;the applications aimed at optimizing diagnosis and prognosis were mainly described. Finally, the vaccination campaign against SARS-CoV-2. The fields most considered were the heterogeneity in patient selection, laboratory parameters used, the machine learning models and their validation and implementation. Furthermore, we briefly describe artificial intelligence's potentialities in planning different strategies for the vaccination campaigns against SARS-COV-2 through laboratory tests. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Common Prognostic Biomarkers and Outcomes in Patients with COVID-19 Infection in Saudi Arabia.

Background: COVID-19 is a respiratory disease that eventually became a pandemic, with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently been reported to help in early prediction and managing severe cases, which might improve outcomes. Our study aimed to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in COVID-19 patients and its effect on the outcome. Methods: We have collected retrospective data on socio-demographics, medical history, biomarkers, and disease outcomes from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID-19 in our cohort. The presence of abnormal inflammatory biomarkers (D-dimer, CRP, troponin, LDH, ferritin, and t white blood cells) was significantly associated with unstable COVID-19 disease. In addition, patients with evidence of severe respiratory disease, particularly those who required mechanical ventilation, had higher biomarkers when compared to those with stable respiratory conditions (p < 0.001). Conclusion: Identifying biomarkers predicts outcomes for COVID-19 patients and may significantly help in their management.

Biruni Index as a Novel Diagnostic Tool for the Early Prediction of Mortality in Critical Patients With COVID-19: A Cohort Study.

BACKGROUND: The aim of this study was to find out the potential risk factors associated with mortality in severe coronavirus disease 2019 (COVID-19) patients hospitalized due to viral bronchopneumonia, and to establish a novel COVID-19 mortality index for daily use. METHODS: The study included 431 quantitative real-time polymerase chain reaction (qRT-PCR)-confirmed COVID-19-positive patients admitted to the intensive care unit in a tertiary care hospital. Patients were divided into training and validation cohorts at random (n= 285 and n= 130, respectively). Biruni Index was developed by multivariate logistic regression analysis for predicting COVID-19-related mortality. RESULTS: In univariate logistic regression analysis, age, systolic and diastolic blood pressures, respiratory and pulse rates per minute, D-dimer, pH, urea, ferritin, and lactate dehydrogenase levels at first admission were statistically significant factors for the prediction of mortality in the training cohort. By using multivariate logistic regression analysis, all of these statistically significant parameters were used to produce Biruni Index. Statistically significant differences in Biruni Index were observed between ex and non-ex groups in both training and validation cohorts (P < 0.001 for both comparisons). Areas under receiver operating characteristic (ROC) curve for Biruni Index were 0.901 (95CI%: 0.864-0.938, P < 0.001) and 0.860 (95CI%: 0.795-0.926, P < 0.001) in training and validation cohorts, respectively. CONCLUSION: As a pioneering clinical study, Biruni Index may be a useful diagnostic tool for clinicians to predict the mortality in critically ill patients with COVID-19 hospitalized due to severe viral bronchopneumonia. However, Biruni Index should be validated with larger series of multicenter prospective clinical studies.

Is the prognostic nutritional index a predictor of Covid-19 related hospitalizations and mortality?

Introduction Prognostic nutritional index (PNI) is a novel inflammation marker that useful in predicting prognosis of certain conditions. We aimed to study PNI of the outpatient and inpatient subjects with established Covid-19 and also aimed to compare PNI of deceased and survived Covid-19 patients. Methods The patients with Covid-19 whom presented to outpatient or inpatient clinics of Abant Izzet Baysal University Hospital were enrolled to the study. PNI levels of the inpatients and outpatients, deceased and survived were compared. PNI values of deceased and survived in inpatients were also compared. Results Study population was consisted of 4419 subjects (2907 outpatients and 1512 inpatients). PNI of the inpatient (41.55 (36.42-47.1)) group was significantly lower than the PNI of the outpatient (51.95 (47.95-55.75)) subjects (p<0.001). The sensitivity and specificity of PNI (≤46.2 level) in determination of requirement inpatient treatment were 71.2% and 83.5%, respectively. PNI of the deceased patients (37(33.39-40.86)) was lower than the PNI of the survivors (50.45(45.6-54.65)), (p<0.001). The sensitivity and specificity of PNI at ≤44.55 level in determining mortality were 89.22% and 78.87%, respectively. Conclusion We suggest that PNI could serve as a reliable prognostic index in covid-19 patients. Reduced level of PNI should alert physicians since it is associated with need for hospitalization and mortality in this population. © 2023 Kamuzu University of Health Sciences.

Comparative analysis of factors associated with the severe course of COVID-19 in the age groups under 60 and over 60 years of age

Introduction: Coronavirus infection is a disease that causes respiratory failure and complications in certain groups of people, leading to death. The factors associated with the severe course of COVID-19 have been fairly well studied by now;at the present stage, it is necessary to search for and study them in separate groups of people that differ in age, gender, ethnicity, the presence of background diseases, etc. to develop more personalized approaches to severe disease prevention. Background: To conduct a comparative analysis of the factors associated with the severe course of COVID-19 in people under and over 60 years of age and evaluate their prognostic significance in combination of factors. Materials and methods: A retrospective analysis of the clinical and laboratory parameters of 812 COVID-19 patients was carried out. Multiple logistic regression analysis was used to identify factors associated with the development of severe COVID-19. ROC analysis was performed to assess the prognostic significance of the set of identified statistically significant factors in the development of a severe course of COVID-19. Results: Multivariate logistic regression analysis showed that patients under 60 diabetes mellitus (OR=2,561, p=0,048), lymphopenia (OR=2,133, p=0,030), and pneumonia at admission (OR=2,556, p=0,011), rapid breathing (OR=3,497, p=0,001), low saturation (OR=4,076, p=0,006) were significantly associated with the development of severe COVID-19. At the same time, in patients older than 60 years, the presence of diabetes mellitus (OR=1,899, p=0,029), rapid breathing (OR=2,338, p=0,007) and low saturation (OR=4,248, p < 0,0001) were significantly associated with the development of a severe course of COVID-19. In groups under 60 and over 60 years of age, the prognostic value of the combination of all statistically significant factors corresponding to the groups was equal to the average level (AUC=0,760 and AUC=0,709, respectively) Conclusion: Factors associated with the development of a severe course of COVID-19 in elderly and middle-aged people have some differences related to the pathogenesis of the disease. For individuals under 60 years of age, factors associated with severe COVID-19 are diabetes mellitus, the presence of pneumonia on admission, dyspnea, low oxygen saturation, and lymphopenia. For individuals over 60 years of age, factors associated with severe COVID-19 are the presence of diabetes mellitus, shortness of breath, and low saturation. The combination of all the studied factors significantly increases the risk of developing a severe course of COVID-19 in both age groups.

Prognostic criteria for the development of severe clinical forms of COVID-19 in medical organization workers

Employees of medical organizations are one of the risk groups for infection with a new coronavirus infection (COVID-19), including with the development of severe clinical forms. The aim of the study was to analyze the clinical manifestations of a new coronavirus infection in medical workers with the determination of laboratory markers for the development of severe COVID-19. Material and methods. The study included 186 medical workers who had COVID-19 in 2020. In 67 people (observation group), the disease occurred in the form of pneumonia, in 119 people (comparison group) - acute respiratory infection caused by SARS-CoV-2. In the acute period of the disease, a laboratory examination was carried out: a general clinical blood test, CD-typing of lymphocyte subpopulations, assessment of biochemical parameters, determination of parameters of the hemostasis system and cytokine levels. Using the binary logistic regression method, we have built multifactor models. To determine the threshold values of the indicators, we used ROC analysis. Statistical processing of materials was carried out using Microsoft Office 2016 and IBM SPSS Statistics (version 26). The differences were considered statistically significant at p<0.05. Results and discussion. The most frequent clinical manifestations of COVID-19 were: weakness, fever, myalgia, arthralgia, difficulty in nasal breathing, serous-mucous discharge from the nose, sore throat, cough, feeling of "tightness" in the chest, shortness of breath, headache, pain in the eyeballs, dizziness, anosmia, ageusia and dyspeptic manifestations in the form of diarrhea, nausea or vomiting. Markers associated with the development of severe pneumonia associated with COVID-19 have been identified. Threshold values of laboratory parameters for predicting the severe course of COVID-19 were determined: the number of platelets (less than 239x109/l), lymphocytes (less than 1.955x109/l), cytotoxic T-lymphocytes (less than 0.455x109/l), T-helper cells (less than 0.855x109/l), NK-cells (less than 0.205x109/l), ESR (more than 11.5 mm/h), LDH (more than 196 units/l), total protein (less than 71.55 g/l), D-dimer (more than 0.325 mcg/ml), CRP (more than 4.17 mg/l), IL-6 (more than 3.63 pg/l). Conclusion. The data obtained make it possible to predict the possibility of developing a severe variant of the COVID-19 course.Copyright © 2022 Infectious Diseases: News, Opinions, Training. All rights reserved.

Prognostic Factors for Covid-19 on Admission Profile and Air Pollutants.

It has been reported that the severity and lethality of Covid-19 are associated with coexisting underlying diseases (hypertension, diabetes, etc.) and cardiovascular diseases (coronary artery disease, atrial fibrillation, heart failure, etc.) that increase with age, but environmental exposure such as air pollutants may also be a risk factor for mortality. In this study, we investigated patient characteristics at admission and prognostic factors of air pollutants in Covid-19 patients using a machine learning (random forest) prediction model. Age, Photochemical oxidant concentration one month prior to admission, and level of care required were shown to be highly important for the characteristics, while the cumulative concentrations of air pollutants SPM, NO2, and PM2.5 one year prior to admission were the most important characteristics for patients aged 65 years and older, suggesting the influence of long-term exposure.

Role of non-coding RNAs in tuberculosis and their potential for clinical applications.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains the leading cause of mortality due to infectious diseases, only surpassed in 2020 by COVID-19. Despite the development in diagnostics, therapeutics, and evaluation of new vaccines for TB, this infectious disease remains uncontrollable due to the emergence of multidrug-resistant (MDR) and extremely drug-resistant (XDR) TB, among other factors. The development in transcriptomics (RNomics) has enabled the study of gene expression in TB. It is considered that non-coding RNAs (ncRNAs) from host [microRNAs (miRNAs)] and Mtb [small RNAs (sRNAs)] are important elements in TB pathogenesis, immune resistance, and susceptibility. Many studies have shown the importance of host miRNAs in regulating immune response against Mtb via in vitro and in vivo mice models. The bacterial sRNAs play a major role in survival, adaptation, and virulence. Here, we review the characterization and function of host and bacteria ncRNAs in TB and their potential use in clinical applications as diagnostic, prognostic, and therapeutic biomarkers.

C-reactive protein lymphocyte index in COVID-19: a little-explored tool

Background: COVID-19 develops severe inflammatory responses that can lead to death. It is essential in a pandemic to have accessible instruments to estimate the prognosis of the disease. The lymphocyte-to-C-reactive protein ratio (LCR) is a predictive biomarker studied in oncology, which could have some advantages in COVID-19 patients in the early stages of the disease. Our objective was to estimate the risk of LCR < 100 and mortality in hospitalized patients with COVID-19. Methods: hospitalized patients with COVID-19 seen between March to October 2020 were included. The patients were grouped according to LCR < 100 and LCR > 100. A Cox regression model was performed to estimate the association between LCR < 100 and mortality. Results: we included 730 patients with COVID-19. The mean age at diagnosis was 49.9 years (SD 16.8) and 401 (55%) were men. Cox regression model showed an association between LCR < 100 and mortality (HR 6.2;95% CI 1.6 to 23.5;p 0.008), adjusting by age. severe pneumonia, intensive care requirements, and comorbidities. Conclusion: LPCR < 100 in the initial assessment of hospitalized patients with COVID-19 suggests a higher risk of mortality.

Upfront Oncotype DX in early breast cancer management

Introduction: Oncotype DX, a 21 gene assay has prognostic and chemotherapy predictive value. During COVID pandemic, guidance issued extended use of genomic testing to avoid chemotherapy to node positive patients. We aimed to identify impact of Oncotype DX testing in pre-operative setting of early breast cancer. Method(s): We retrospectively reviewed those patients where MDT recommended upfront Oncotype DX testing from 1st March 2020 till Sept 2022. Result(s): 59 patients were identified. The mean age was 55.7 +/- 11.4 years. Two-thirds were postmenopausal. Four-fifth had symptomatic presentation. the mean tumour size was 28.8 +/- 8.7 mm. Invasive ductal carcinoma was seen in 81% (N=48). Progesterone receptor positivity was seen in 93% (n=55). Node positivity was seen in 44% (n=26) while nodes were negative in 56% (n=33). Overall, low, intermediate and high score was seen in 47% (n=28), 8% (n=5) and 45% (n=26) respectively. In node negative patients, low, intermediate, and high score was seen in 45% (n=15), 10% (n=3) and 45% (n=15) respectively. Chemotherapy was avoided in 55% patients. In node positive patients, low, intermediate, and high score was seen in 50% (n=15), 8% (n=2) and 42% (n=11) respectively. Overall, chemotherapy was avoided in 23% patients with node positive disease. Conclusion(s): Upfront Oncotype DX testing can be used in node negative breast cancer patients. However, it should be used very cautiously in node positive women.Copyright © 2023

BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data.

Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge from the datasets collected from 930 COVID-19 patients hospitalized in Italy during the first wave of COVID-19 (March-June 2020). The dataset consists of twenty-five biomarkers from electronic health record and Chest X-ray (CXR) images. It is found that the system can diagnose low- or high-risk patients with an accuracy, sensitivity, and F1-score of 89.03%, 90.44%, and 89.03%, respectively. The system exhibits 6% higher accuracy than the systems that employ either CXR images or biomarker data. In addition, the system can calculate the mortality risk of high-risk patients using multivariate logistic regression-based nomogram scoring technique. Interested physicians can use the presented system to predict the early mortality risks of COVID-19 patients using the web-link: Covid-severity-grading-AI. In this case, a physician needs to input the following information: CXR image file, Lactate Dehydrogenase (LDH), Oxygen Saturation (O2%), White Blood Cells Count, C-reactive protein, and Age. This way, this study contributes to the management of COVID-19 patients by predicting early mortality risk. Supplementary Information: The online version contains supplementary material available at 10.1007/s00521-023-08606-w.

Clinical trial-identified inflammatory biomarkers in breast and pancreatic cancers.

Breast cancer and pancreatic cancer are two common cancer types characterized by high prevalence and high mortality rates, respectively. However, breast cancer has been more well-studied than pancreatic cancer. This narrative review curated inflammation-associated biomarkers from clinical studies that were systematically selected for both breast and pancreatic cancers and discusses some of the common and unique elements between the two endocrine-regulated malignant diseases. Finding common ground between the two cancer types and specifically analyzing breast cancer study results, we hoped to explore potential feasible methods and biomarkers that may be useful also in diagnosing and treating pancreatic cancer. A PubMed MEDLINE search was used to identify articles that were published between 2015-2022 of different kinds of clinical trials that measured immune-modulatory biomarkers and biomarker changes of inflammation defined in diagnosis and treatment of breast cancer and pancreatic cancer patients. A total of 105 papers (pancreatic cancer 23, breast cancer 82) were input into Covidence for the title and abstract screening. The final number of articles included in this review was 73 (pancreatic cancer 19, breast cancer 54). The results showed some of the frequently cited inflammatory biomarkers for breast and pancreatic cancers included IL-6, IL-8, CCL2, CD8+ T cells and VEGF. Regarding unique markers, CA15-3 and TNF-alpha were two of several breast cancer-specific, and CA19 and IL-18 were pancreatic cancer-specific. Moreover, we discussed leptin and MMPs as emerging biomarker targets with potential use for managing pancreatic cancer based on breast cancer studies in the future, based on inflammatory mechanisms. Overall, the similarity in how both types of cancers respond to or result in further disruptive inflammatory signaling, and that point to a list of markers that have been shown useful in diagnosis and/or treatment method response or efficacy in managing breast cancer could potentially provide insights into developing the same or more useful diagnostic and treatment measurement inflammatory biomarkers for pancreatic cancer. More research is needed to investigate the relationship and associated inflammatory markers between the similar immune-associated biological mechanisms that contribute to breast and pancreatic cancer etiology, drive disease progression or that impact treatment response and reflect survival outcomes.