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1.
Travel Medicine and Infectious Disease ; 52:102535, 2023.
Article in English | ScienceDirect | ID: covidwho-2165904
2.
iScience ; : 105873, 2022.
Article in English | ScienceDirect | ID: covidwho-2165428

ABSTRACT

Summary Diagnostic services for tuberculosis (TB) are not sufficiently accessible in low-resource settings, where most cases occur, which was aggravated by the COVID-19 pandemic. Early diagnosis of pulmonary TB can reduce transmission. Current TB-diagnostics rely on detection of Mycobacterium tuberculosis (Mtb) in sputum requiring costly, time-consuming methods, and trained staff. In this study, quantitative lateral flow (LF) assays were used to measure levels of seven host proteins in sera from pre-COVID-19 TB-patients diagnosed in Europe and latently Mtb-infected individuals (LTBI), and from COVID-19 patients and healthy controls. Analysis of host proteins showed significantly lower levels in LTBI versus TB (AUC:0·94) and discriminated healthy individuals from COVID-19 patients (0·99) and severe COVID-19 from TB. Importantly, these host proteins allowed treatment monitoring of both respiratory diseases. This study demonstrates the potential of non-sputum LF assays as adjunct diagnostics and treatment monitoring for COVID-19 and TB based on quantitative detection of multiple host biomarkers.

3.
EBioMedicine ; 85: 104296, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2158739

ABSTRACT

BACKGROUND: COVID-19 is characterized by a heterogeneous clinical presentation, ranging from mild symptoms to severe courses of disease. 9-20% of hospitalized patients with severe lung disease die from COVID-19 and a substantial number of survivors develop long-COVID. Our objective was to provide comprehensive insights into the pathophysiology of severe COVID-19 and to identify liquid biomarkers for disease severity and therapy response. METHODS: We studied a total of 85 lungs (n = 31 COVID autopsy samples; n = 7 influenza A autopsy samples; n = 18 interstitial lung disease explants; n = 24 healthy controls) using the highest resolution Synchrotron radiation-based hierarchical phase-contrast tomography, scanning electron microscopy of microvascular corrosion casts, immunohistochemistry, matrix-assisted laser desorption ionization mass spectrometry imaging, and analysis of mRNA expression and biological pathways. Plasma samples from all disease groups were used for liquid biomarker determination using ELISA. The anatomic/molecular data were analyzed as a function of patients' hospitalization time. FINDINGS: The observed patchy/mosaic appearance of COVID-19 in conventional lung imaging resulted from microvascular occlusion and secondary lobular ischemia. The length of hospitalization was associated with increased intussusceptive angiogenesis. This was associated with enhanced angiogenic, and fibrotic gene expression demonstrated by molecular profiling and metabolomic analysis. Increased plasma fibrosis markers correlated with their pulmonary tissue transcript levels and predicted disease severity. Plasma analysis confirmed distinct fibrosis biomarkers (TSP2, GDF15, IGFBP7, Pro-C3) that predicted the fatal trajectory in COVID-19. INTERPRETATION: Pulmonary severe COVID-19 is a consequence of secondary lobular microischemia and fibrotic remodelling, resulting in a distinctive form of fibrotic interstitial lung disease that contributes to long-COVID. FUNDING: This project was made possible by a number of funders. The full list can be found within the Declaration of interests / Acknowledgements section at the end of the manuscript.


Subject(s)
COVID-19 , Lung Diseases, Interstitial , Humans , Lung/diagnostic imaging , Lung/pathology , Lung Diseases, Interstitial/pathology , Fibrosis , Biomarkers/analysis , Ischemia/pathology
4.
EMBO Mol Med ; : e14088, 2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2155876

ABSTRACT

Tuberculosis (TB) is a leading cause of morbidity and mortality from a single infectious agent, despite being preventable and curable. Early and accurate diagnosis of active TB is critical to both enhance patient care, improve patient outcomes, and break Mycobacterium tuberculosis (Mtb) transmission cycles. In 2020 an estimated 9.9 million people fell ill from Mtb, but only a little over half (5.8 million) received an active TB diagnosis and treatment. The World Health Organization has proposed target product profiles for biomarker- or biosignature-based diagnostics using point-of-care tests from easily accessible specimens such as urine or blood. Here we review and summarize progress made in the development of pathogen- and host-based biomarkers for active TB diagnosis. We describe several unique patient populations that have posed challenges to development of a universal diagnostic TB biomarker, such as people living with HIV, extrapulmonary TB, and children. We also review additional limitations to widespread validation and utilization of published biomarkers. We conclude with proposed solutions to enhance TB diagnostic biomarker validation and uptake.

5.
Front Immunol ; 13: 1032331, 2022.
Article in English | MEDLINE | ID: covidwho-2154734

ABSTRACT

The SARS-CoV-2 virus continues to cause significant morbidity and mortality worldwide from COVID-19. One of the major challenges of patient management is the broad range of symptoms observed. While the majority of individuals experience relatively mild disease, a significant minority of patients require hospitalisation, with COVID-19 still proving fatal for some. As such, there remains a desperate need to better understand what drives this severe disease, both in terms of the underlying biology, but also to potentially predict at diagnosis which patients are likely to require further interventions, thus enabling better outcomes for both patients and healthcare systems. Several lines of evidence have pointed to dysregulation of the complement cascade as a major factor in severe COVID-19 outcomes. How this is underpinned mechanistically is not known. Here, we have focussed on the role of the soluble complement regulators Complement Factor H (FH), its splice variant Factor H-like 1 (FHL-1) and five Factor H-Related proteins (FHR1-5). Using a targeted mass spectrometry approach, we quantified these proteins in a cohort of 188 plasma samples from controls and SARS-CoV-2 patients taken at diagnosis. This analysis revealed significant elevations in all FHR proteins, but not FH, in patients with more severe disease, particularly FHR2 and FHR5 (FHR2: 1.97-fold, p<0.0001; FHR5: 2.4-fold, p<0.0001). Furthermore, for a subset of 77 SARS-CoV-2 +ve patients we also analysed time course samples taken approximately 28 days post-diagnosis. Here, we see complement regulator levels drop in all individuals with asymptomatic or mild disease, but regulators remain high in those with more severe outcomes, with elevations in FHR2 over baseline levels in this group. These data support the hypothesis that elevation of circulating levels of the FHR family of proteins could predict disease severity in COVID-19 patients, and that the duration of elevation (or lack of immune activation resolution) may be partly responsible for driving poor outcomes in COVID-19.


Subject(s)
COVID-19 , Complement Factor H , Humans , SARS-CoV-2 , Complement Activation , Immunologic Factors
6.
Int J Risk Saf Med ; 2022 Jul 20.
Article in English | MEDLINE | ID: covidwho-2154624

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, the Hillingdon Hospitals NHS Foundation Trust produced trust guidelines for the initial blood investigation of COVID-19 inpatients. However, insufficient education meant inconsistent adherence to this guidance. OBJECTIVE: To examine whether the implementation of a COVID-19 blood request panel improves adherence to local trust guidelines. METHOD: Between March and April 2020, initial blood investigations performed for positive COVID-19 cases were compared to guidelines. Results were presented locally and a COVID-19 panel was added to the electronic system that provided prompts for appropriate investigations. A re-audit between May and June 2020 was conducted to assess adherence post-intervention. RESULTS: 383 patients were identified in the initial audit cohort and a sample of 20 patients were re-audited. Adherence to Full Blood Count, Urea and Electrolytes, C-reactive Protein and Liver Function Tests increased to 100% from 99.7% (p = 0.8), 99.2% (p = 0.69), 98.7% (p = 0.61), and 96.6% (p = 0.4) respectively. Coagulation screen adherence increased to 90% from 72.8% (p = 0.09). Appropriate requesting of D dimers increased to 50% from 19.9% (p = 0.001). Inappropriate troponin requesting decreased to 26.3% from 38.9% (p = 0.23). CONCLUSION: A user-friendly COVID-19 panel of investigations resulted in improved adherence to guidelines. Clear communication and education are essential to help alleviate uncertainty during a pandemic.

7.
Journal of Pharmaceutical Negative Results ; 13:1537-1549, 2022.
Article in English | EMBASE | ID: covidwho-2164828

ABSTRACT

Aim - For diagnosis of social anxiety disorder, general anxiety disorder, and other mental disorders, using salivary biomarkers as an adjunct diagnostic method will be able to play a major role to avoid misdiagnosis and underrecognition of mental illnesses. Background - According to World Health Organization (WHO) estimates, roughly 280 million people worldwide suffer from depression that begins with Social Anxiety Disorder or Generalized Anxiety Disorder. According to a study on natural disasters, an estimated 10.00% of people would also have serious psychological difficulties as a result of the ongoing pandemic, such as mood disorders, anxiety disorders, or Posttraumatic stress disorder (PTSD). Method-:A comprehensive literature search was done using various databases like EBSCO, Google Scholar, Pubmed, and Embase from 1937 to 2021. The keywords used for the search were "Generalized anxiety disorder in covid 19", "Post-traumatic stress disorder", "Depression", "Salivary biomarkers AND stress", and "misdiagnosis AND mental illnesses".The articles were selected by the authors on the basis of inclusion and exclusion criteria. Clinical significance- Saliva is utilized as a stress indicator since it is secreted by an inherent response controlled by the autonomic nervous system. In future research, the 2 salivary biomarkers might act as an adjunct diagnostic method which will be helpful for early diagnosis as most of the diagnosis of mental illness depends on patients' subjective response. The salivary biomarkers which can be used as an adjunct diagnostic method of mental disorders are Salivary alpha-amylase,Malondialdehyde, Nitrogen, and Oxygen Reactive species, Salivary IgA, Cortisol levels, and G6PD deficiency. Conclusion(s): For the diagnosis of generalized anxiety disorder which is one of the symptoms of depression and other mental illnesses. In the future, research can be focussed on salivary biomarkers which can be helpful in the early diagnosis of generalized anxiety disorder or other mental disorders. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

8.
PeerJ ; 2022.
Article in English | ProQuest Central | ID: covidwho-2164156

ABSTRACT

Background The severe form of COVID-19 can cause a dysregulated host immune syndrome that might lead patients to death. To understand the underlying immune mechanisms that contribute to COVID-19 disease we have examined 28 different biomarkers in two cohorts of COVID-19 patients, aiming to systematically capture, quantify, and algorithmize how immune signals might be associated to the clinical outcome of COVID-19 patients. Methods The longitudinal concentration of 28 biomarkers of 95 COVID-19 patients was measured. We performed a dimensionality reduction analysis to determine meaningful biomarkers for explaining the data variability. The biomarkers were used as input of artificial neural network, random forest, classification and regression trees, k-nearest neighbors and support vector machines. Two different clinical cohorts were used to grant validity to the findings. Results We benchmarked the classification capacity of two COVID-19 clinicals studies with different models and found that artificial neural networks was the best classifier. From it, we could employ different sets of biomarkers to predict the clinical outcome of COVID-19 patients. First, all the biomarkers available yielded a satisfactory classification. Next, we assessed the prediction capacity of each protein separated. With a reduced set of biomarkers, our model presented 94% accuracy, 96.6% precision, 91.6% recall, and 95% of specificity upon the testing data. We used the same model to predict 83% and 87% (recovered and deceased) of unseen data, granting validity to the results obtained. Conclusions In this work, using state-of-the-art computational techniques, we systematically identified an optimal set of biomarkers that are related to a prediction capacity of COVID-19 patients. The screening of such biomarkers might assist in understanding the underlying immune response towards inflammatory diseases.

9.
Frontiers in Public Health ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2163186

ABSTRACT

IntroductionCardiac injury has received considerable attention due to the higher risk of morbidity and mortality associated with coronavirus disease. However, in a developing country, there is a scarcity of data on cardiac injury in COVID-19 patients related to inflammatory biomarkers. MethodsTherefore, the present research retrospectively analyzes data from three territorial hospitals in Pakistan's Punjab province to investigate the potential impact of the cardiac injury on the mortality and severity of COVID-19-infected patients. We evaluated 2,051 patients between January 16 and April 18, 2022, with confirmed COVID-19. The in-hospital mortality recorded for the selected sample size was about 16.28%. ResultsThe majority of the participants were identified as male (64%) with a median age of 65 years. Also, fever, fatigue, and dyspnea were reported as common symptoms. An aggregate of 623 patients (30.38%) had a cardiac injury, and when these patients are compared to those without cardiac injury, the participants were significantly older and had more comorbidities with higher leukocyte counts, elevated levels of C-reactive protein, interleukin-6, procalcitonin, myohemoglobin, creatinine kinase-myocardial band, serum creatinine, high-sensitivity troponin-I, N-terminal pro-B-type natriuretic peptide had a significant amount of multiple ground-glass opacity and bilateral pulmonary infiltration in radiographic results. Participants with heart injury required more non-invasive or invasive mechanical respiration than those who did not have a cardiac injury. Individuals with cardiac injury had higher rates of sepsis, acute respiratory distress syndrome (ARDS), d-dimer concentration, and respiratory failure than those without cardiac injury. Patients who had had a cardiac injury died at a higher rate than those who had not suffered cardiac damage. In the multivariable logistic regression analysis, participants with cardiac injury showed greater odds of COVID-19 mortality and were found associated with older age (OR = 1.99, 95% CI = 0.04-3.19), elevated cardiac troponin I (OR = 18.64, 95% CI = 13.16-23.01), the complication of sepsis (OR = 10.39, 95% CI = 7.41-13.39) and ARDS (OR = 6.65, 95% CI = 4.04-8.91). ConclusionCardiac injury is a frequent complication among patients with coronavirus-induced infection in Punjab, Pakistan, and it is significantly linked to a greater risk of in-hospital mortality.

10.
Frontiers in Medicine ; 9 (no pagination), 2022.
Article in English | EMBASE | ID: covidwho-2163042

ABSTRACT

Background: Systemic biomarkers for severity of SARS-CoV-2 infection are of great interest. In this study, we evaluated a set of collagen metabolites and extracellular matrix remodeling biomarkers including procollagen type III amino terminal propeptide (PIIINP), tissue inhibitor of metalloproteinases 1 (TIMP-1) and hyaluronic acid (HA) as prognostic indicators in COVID-19 patients. Method(s): Ninety COVID-19 patients with the absence of chronic liver diseases were enrolled. Serum PIIINP, TIMP-1, and HA were measured and correlated with inflammatory indices and clinical variables. Patients were stratified for disease severity according to WHO criteria in two groups, based on the requirement of oxygen support. Result(s): Serum TIMP-1, but not PIIINP and HA was significantly higher in patients with WHO score >=5 compared to patients with WHO score <5 [PIIINP: 7.2 (5.4-9.5) vs. 7.1 (4.5-9.9), p = 0.782;TIMP-1: 298.1 (20.5-460) vs. 222.2 (28.5-452.8), p = 0.01;HA: 117.1 (55.4-193.7) vs. 75.1 (36.9-141.8), p = 0.258]. TIMP-1 showed moderate correlation with CRP (r = 0.312, p = 0.003) and with LDH (r = 0.263, p = 0.009). CRP and serum LDH levels were significantly higher in COVID-19 patients with WHO score >=5 compared to the group of patients with WHO score < 5 [15.8 (9-44.5) vs. 9.3 (3.4-33.8), p = 0.039 and 373 (282-465) vs. 289 (218-383), p = 0.013, respectively]. Conclusion(s): In patients with COVID-19, circulating TIMP-1 was associated with disease severity and with systemic inflammatory index, suggesting that TIMP-1 could represent a promising non-invasive prognostic biomarker in COVID-19 patients. Interestingly, our results prompted that serum TIMP-1 level may potentially be used to select the patients for therapeutic approaches targeting matrix metalloproteases pathway. Copyright © 2022 Brusa, Terracciano, Bruzzese, Fiorenza, Stanziola, Pinchera, Valente, Gentile, Cittadini, Mormile, Mormile and Portella.

11.
Practical Neurology ; 2022.
Article in English | ProQuest Central | ID: covidwho-2161977

ABSTRACT

Functional cognitive disorders (FCDs) are a common cause of subjective and mild cognitive impairment. Isolated FCDs commonly present to the cognitive clinic, but examination of the nature of the symptoms suggests that they can also be understood as a transdiagnostic feature of many other conditions. This article examines methods of formulating the cognitive difficulties in order to identify treatment targets in people with FCDs.

12.
World Allergy Organization Journal ; 16(1):100727, 2023.
Article in English | ScienceDirect | ID: covidwho-2159925

ABSTRACT

Asthma imposes a heavy morbidity burden during childhood;it affects over 10% of children in Europe and North America and it is estimated to exceed 400 million people worldwide by the year 2025. In clinical practice, diagnosis of asthma in children is mostly based on clinical criteria;nevertheless, assessment of both physiological and pathological processes through biomarkers, support asthma diagnosis, aid monitoring, and further lead to better treatment outcomes and reduced morbidity. Recently, identification and validation of biomarkers in pediatric asthma has emerged as a top priority across leading experts, researchers, and clinicians. Moreover, the implementation of non-invasive biomarkers for the assessment and monitoring of paediatric patients with asthma, has been prioritized;however, only a proportion of them are currently included in the clinical practise. Although, the use of non-invasive biomarkers is highly supported in recent asthma guidelines for documenting diagnosis and supporting monitoring of asthmatic patients, data on the Pediatric population are limited. In the present report, the Pediatric Asthma Committee of the World Allergy Organization (WAO), aims to summarize and discuss available data for the implementation of non-invasive biomarkers in the diagnosis and monitoring in children with asthma. Information on the most studied biomarkers, including spirometry, oscillometry, markers of allergic sensitization, fractional exhaled nitric oxide, and the most recent exhaled breath markers and "omic” approaches, will be reviewed. Practical limitations and considerations based on both experts' opinion and critical review of the literature, on the utility of all "well-known” and newly introduced non-invasive biomarkers will be presented. A critical commentary on biomarkers' use in diagnosing and monitoring asthma during the COVID-19 pandemic, cost and availability of biomarkers in different settings and in developing countries, the differences on the biomarkers use between Primary Practitioners, Pediatricians, and Specialists and their role on the longitudinal aspect of asthma is provided.

13.
Silicon ; 14(17):11741-11748, 2022.
Article in English | ProQuest Central | ID: covidwho-2158188

ABSTRACT

Biomedical applications adapt Nano technology-based transistors as a key component in the biosensors for diagnosing life threatening diseases like Covid-19, Acute myocardial infarction (AMI), etc. The proposed work introduces a new biosensor, based on Graphene Field Effect Transistor (GFET), which is used in the diagnosis of Myoglobin (Mb) in human blood. Graphene-based biosensors are faster, more precise, stronger, and more trustworthy. A GFET is created in this study for the detection of myoglobin biomarker at various low concentrations. Because graphene is sensitive to a variety of biomarker materials, it can be employed as a gate material. When constructed Graphene FET is applied to myoglobin antigens, it has a significant response. The detection level for myoglobin is roughly 30 fg/ml, which is quite high. The electrical behavior of the GFET-based biosensor in detecting myoglobin marker is ideal for Lab-on-Chip platforms and Cardiac Point-of-Care Diagnosis.

14.
Studies in Computational Intelligence ; 1060:245-256, 2023.
Article in English | Scopus | ID: covidwho-2157979

ABSTRACT

This paper presents a factor graph-based model that takes comorbidities and clinical measurements as inputs and predicts intensive care unit (ICU) admissions 3 days and 7 days in advance for hospitalized COVID-19 patients. We applied the proposed model on a COVID-19 cohort from a large medical center in Chicago (with records from March 2020 to August 2021). We used the first occurrence of the Delta variant in the U.S., February 2021, as the threshold to divide the dataset into pre-Delta data (533 patients) and post-Delta data (56 patients). Our model demonstrated 0.82 AUC on the pre-Delta data and 0.87 AUC on the post-Delta data in 7-day predictions. Our contribution is a model that (i) explains relationships between different clinical features and provides interpretations for ICU admissions, (ii) outperforms existing methods for 7-day predictions, and (iii) maintains more robustness than existing models in predictions under the influence of the Delta variant. The proposed model could be used as a predictive tool in clinical practice to help clinicians in decision-making by predicting which patients will need ICU support in the future. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

15.
Journal of Clinical and Diagnostic Research ; 16(11):EC12-EC15, 2022.
Article in English | EMBASE | ID: covidwho-2155788

ABSTRACT

Introduction: Abnormalities in Complete Blood Count (CBC) are frequently observed in Coronavirus Disease-2019 (COVID-19) infection. So, CBC can serve as a simple tool for the early diagnosis of COVID-19. Aim(s): To evaluate the diagnostic ability of CBC test in COVID-19 infection. Material(s) and Method(s): In this retrospective observational study, data were collected from 102 adult non critical care patients who presented with acute fever between May 2020 and December 2020. Among 102 patients' data, 48 were found Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) positive ('cases') and 54 were RT- PCR negative ('controls'). Non parametric Mann-Whitney test was used to compare the differences in CBC. The p-value <0.05 was considered statistically significant. Receiver Operator Characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of CBC tests in COVID-19. For this, RT-PCR was used as the 'gold standard' and CBC as the index test. Area Under Curve (AUC) was determined for each of the CBC tests. All statistical analysis were done using Medcalc software. Result(s): The mean age of cases was 48+/-14 years (62% males;38% females) and controls was 45+/-15 years (55% males;45% females). Median values for haemoglobin, haematocrit, Red Blood Cell (RBC) count and Red cell Distribution Width (RDW) were significantly higher (p-value <0.05) and total White Blood Cell (WBC) count, eosinophil differential count, absolute eosinophil count, lymphocyte count, absolute lymphocyte count, immature granulocyte count were significantly lower in COVID-19 patients as compared to controls. Significant differences were observed for eosinophil (differential% and absolute) count. Almost all the platelet parameters were lower in COVID-19 patients (except Neutrophil Lymphocyte Ratio);although the platelet count was only mildly reduced in the RT-PCR positive cases (133-475 X 103/muL;median-227.98 X 103/muL). Higher AUC values were observed with Eosinophil-differential %, Eosinophil-absolute count, Eosinophil Lymphocyte Ratio (ELR) and NLR. Conclusion(s): Eosinophil count and associated ratio (Eosinophil Lymphocyte Ratio) are diagnostically useful and can serve as biomarkers for COVID-19. Further larger studies are needed to unravel the underlying mechanism and their clinical utility. Copyright © 2022 Authors. All rights reserved.

16.
Vojnosanitetski Pregled ; 79(9):849-856, 2022.
Article in English | EMBASE | ID: covidwho-2154551

ABSTRACT

Background/Aim. Coronavirus disease 2019 (COVID-19) is a predominantly respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The aim of this study was to determine whether there were parameters that could predict the development of a severe clinical picture and fatal outcomes in COVID-19 patients. Methods. The study involved 632 patients treated at the Clinic for Infectious Diseases, University Clinical Center Kragujevac, from June 2020 to February 2021. All patients were divided into two groups according to the need for oxygen therapy (Sat 02 < 94 %). Results. Our results showed that high body mass index (BMI) was singled out as a risk factor for the development of a severe clinical picture (BMI, ORadjusted = 1.263;95% CI = 1.117-1.427;p < 0.001). Prothrombin time (ORadjusted = 1.170;95% CI = 1.004-1.364;p = 0.045), as well as low albumin values (ORadjusted = 0.878;95% CI = 0.804-0.958;p = 0.003), had a predictive significance for the development of a severe clinical picture. Factors that were of predictive importance in patients with fatal outcomes were C-reactive protein (CRP) (ORadjusted = 1.010;95% CI = 1.001-1.019;p = 0.031), lactate dehydrogenase (LDH) (ORadjusted = 1.004;95% CI = 1.001-1.006;p = 0.002), and X-ray of the lungs (ORadjusted = 1.394;95% CI = 1.170-1.661;p < 0.001). Conclusion. The study showed that routine, clinical laboratory parameters can be important in the early detection of patients with a potentially severe clinical picture and fatal outcomes. In patients with a mild clinical picture, CRP, LDH, ferritin, and serum albumin levels may timely indicate disease progression. Monitoring these parameters is of essential importance for the timely clinical assessment of patients with COVID-19 and, thus, the prompt application of adequate therapeutic protocols in the treatment of these patients. Copyright © 2022 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

17.
7th International Conference on Data Science and Engineering, ICDSE 2021 ; 940:89-110, 2022.
Article in English | Scopus | ID: covidwho-2148667

ABSTRACT

The coronavirus pandemic led to the collapse of the healthcare systems of several countries worldwide, including the highly developed ones. The sudden rise in hospitalization requirements for the patients suffering from the disease, caused a tremendous pressure not only on the healthcare system but also on the frontline workers. So, for early diagnosis and prognosis of the patients, identification of the biomarkers pertaining to the coronavirus disease became an essential requirement. Thus, a machine learning (ML) based mortality prediction model was developed that was able to predict the mortality of the patients using a combination of only six features. The six selected features included, four identified biomarkers, namely, lactate dehydrogenase (LDH), neutrophils percentage (NP), fibrin degradation products (FDP), and erythrocyte sedimentation rate (ESR);and, other two features as age and the coronavirus detection test. The developed model with a novel semiautomated method of medical data handling technique, achieved an accuracy of over 98%, and was able to predict the final outcome of the patients on an average of 8 days in advance. The corresponding work was carried out with the intent to ease the burden on the healthcare system, by providing a faster and accurate clinical assessment of the patients suffering from the coronavirus disease. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

18.
Small ; : e2206349, 2022.
Article in English | PubMed | ID: covidwho-2148477

ABSTRACT

Infection classification is the key for choosing the proper treatment plans. Early determination of the causative agents is critical for disease control. Host responses analysis can detect variform and sensitive host inflammatory responses to ascertain the presence and type of the infection. However, traditional host-derived inflammatory indicators are insufficient for clinical infection classification. Fingerprints-based omic analysis has attracted increasing attention globally for analyzing the complex host systemic immune response. A single type of fingerprints is not applicable for infection classification (area under curve (AUC) of 0.550-0.617). Herein, an infection classification platform based on deep learning of dual plasma fingerprints (DPFs-DL) is developed. The DPFs with high reproducibility (coefficient of variation <15%) are obtained at low sample consumption (550 nL native plasma) using inorganic nanoparticle and organic matrix assisted laser desorption/ionization mass spectrometry. A classifier (DPFs-DL) for viral versus bacterial infection discrimination (AUC of 0.775) and coronavirus disease 2019 (COVID-2019) diagnosis (AUC of 0.917) is also built. Furthermore, a metabolic biomarker panel of two differentially regulated metabolites, which may serve as potential biomarkers for COVID-19 management (AUC of 0.677-0.883), is constructed. This study will contribute to the development of precision clinical care for infectious diseases.

19.
Reviews in the Neurosciences ; 33(1):79-92, 2022.
Article in English | APA PsycInfo | ID: covidwho-2124849

ABSTRACT

Coronavirus disease 2019 (COVID-19) is an infectious respiratory disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Evidence-based emerging reports of neurological manifestations show that SARS-CoV-2 can attack the nervous system. However, little is known about the biomarkers in disease in neuropsychiatric and neuroimmunological disorders. One of the important keys in the management of COVID-19 is an accurate diagnosis. Biomarkers could provide valuable information in the early detection of disease etiology, diagnosis, further treatment, and prognosis. Moreover, ongoing investigations on hematologic, biochemical, and immunologic biomarkers in nonsevere, severe, or fatal forms of COVID-19 patients provide an urgent need for the identification of clinical and laboratory predictors. In addition, several cytokines acting through mechanisms to emerge immune response against SARS-CoV-2 infection are known to play a major role in neuroinflammation. Considering the neuroinvasive potential of SARS-CoV-2, which can be capable of triggering a cytokine storm, the current evidence on inflammation in psychiatry and neurodegenerative by emerging neuroinflammation is discussed in this review. We also highlighted the hematologic, biochemical, and immunologic biomarkers in COVID-19 diagnosis. COVID-19 prognostic biomarkers in patients with neuropsychiatric and neuroimmunological diseases are also explained. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

20.
Allergy Asthma Immunol Res ; 14(6): 604-652, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2144267

ABSTRACT

In the last few decades, there has been a progressive increase in the prevalence of allergic rhinitis (AR) in China, where it now affects approximately 250 million people. AR prevention and treatment include allergen avoidance, pharmacotherapy, allergen immunotherapy (AIT), and patient education, among which AIT is the only curative intervention. AIT targets the disease etiology and may potentially modify the immune system as well as induce allergen-specific immune tolerance in patients with AR. In 2017, a team of experts from the Chinese Society of Allergy (CSA) and the Chinese Allergic Rhinitis Collaborative Research Group (C2AR2G) produced the first English version of Chinese AIT guidelines for AR. Since then, there has been considerable progress in basic research of and clinical practice for AIT, especially regarding the role of follicular regulatory T (TFR) cells in the pathogenesis of AR and the use of allergen-specific immunoglobulin E (sIgE) in nasal secretions for the diagnosis of AR. Additionally, potential biomarkers, including TFR cells, sIgG4, and sIgE, have been used to monitor the incidence and progression of AR. Moreover, there has been a novel understanding of AIT during the coronavirus disease 2019 pandemic. Hence, there was an urgent need to update the AIT guideline for AR by a team of experts from CSA and C2AR2G. This document aims to serve as professional reference material on AIT for AR treatment in China, thus improving the development of AIT across the world.

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