Advantages of Total Bilirubin for Predicting Malignant Obstructive Jaundice, A Combination of the Pandemic Era and Limited Resources Settings

BACKGROUND: Hepatopancreatobiliary (HPB) cancer incidence and mortality are increasing worldwide. An initial diagnostic predictor is needed for recommending further diagnostic modalities, referral, and curative or palliative decisions. There were no studies conducted in area with limited accessibility setting of the COVID-19 pandemic, coupled with limited human resources and facilities. AIM: We aimed to investigate the advantages of total bilirubin for predicting malignant obstructive jaundice, a combination of the pandemic era and limited resources settings. METHOD(S): Data from all cholestasis jaundice patients at M. Djamil Hospital in Pandemic COVID-19 period from July 2020 to May 2022 were retrospectively collected. The data included demographics, bilirubin fraction results, and final diagnosis. Bivariate analysis for obtain demographic risk factor, and Receiver Operating Characteristics (ROC) analysis for getting bilirubin value. RESULT(S): Of a total 132 patients included, 35.6% were malignant obstructive jaundice, and Pancreatic adeno ca was the most malignant etiology (34.4%). Bivariate analysis showed a significant correlation between age and malignant etiology (p = 0,024). Direct and total Bilirubin reach the same level of Area Under Curve (AUC). Total bilirubin at the cutoff point level of 10.7 mg/dl had the most optimal results on all elements of ROC output, AUC 0.88, sensitivity 76.6%, specificity 90.1%, +LR 8.14, and-LR 0.26. CONCLUSION(S): The bilirubin fraction is a good initial indicator for differentiating benign and malignant etiology (AUC 0.8-0.9) in pandemic era and resource-limited areas to improve diagnostic effectiveness and reduce referral duration.Copyright © 2023 Avit Suchitra, M. Iqbal Rivai, Juni Mitra, Irwan Abdul Rachman, Rini Suswita, Rizqy Tansa.

Meeting the service needs of youth with and without a self-reported mental health diagnosis during COVID-19

Background: The COVID-19 pandemic catalyzed major changes in how youth mental health (MH) services are delivered. Understanding youth's MH, awareness and use of services since the pandemic, and differences between youth with and without a MH diagnosis, can help us optimize MH services during the pandemic and beyond. Objective(s): We investigated youth's MH and service use one year into the pandemic and explored differences between those with and without a self-reported MH diagnosis. Method(s): In February 2021, we administered a web-based survey to youth, 12-25 years, in Ontario. Data from 1373 out of 1497 (91.72%) participants were analyzed. We assessed differences in MH and service use between those with (N=623, 45.38%) and without (N=750, 54.62%) a self-reported MH diagnosis. Logistic regressions were used to explore MH diagnosis as a predictor of service use while controlling for confounders. Result(s): 86.73% of participants reported worse MH since COVID-19, with no between-group differences. Participants with a MH diagnosis had higher rates of MH problems, service awareness and use, compared to those without a diagnosis. MH diagnosis was the strongest predictor of service use. Gender and affordability of basic needs also independently predicted use of distinct services. Conclusion(s): Various services are required to mitigate the negative effects of the pandemic on youth MH and meet their service needs. Whether youth have a MH diagnosis may be important to understanding what services they are aware of and use. Sustaining pandemic-related service changes require increasing youth's awareness of digital interventions and overcoming other barriers to care.Copyright © 2023, Canadian Academy of Child and Adolescent Psychiatry. All rights reserved.

The Investigation of Change Fatigue in Teacher Candidates Following the Emergency Remote Teaching Process during the Pandemic

Education has gone through rapid changes during the emergency remote teaching period resulting by the COVID-19 pandemic. These changes, in part, have been associated with educational institutions attempting to implement a viable solution to the problem of distance education. Although organizational management theory literature suggests that great change in very little time results in a detrimental psychological phenomenon called change fatigue in employees and that this phenomenon has even been investigated in the context of teaching staff in the past;there have been no attempt at understanding change fatigue from a student perspective. This quantitative study attempts at proposing a structural equation model towards the understanding of how to change fatigue and other variables, namely, digital literacy, online learning attitude and school alienation that might have been influenced by it have affected teacher candidates after resuming face-to-face education followed by a 1.5 year of emergency remote teaching period. Results indicated that change fatigue predicts school alienation and yet;does not predict online learning attitude;hinting that there might be another category of alienating organizational change that universities have gone through that does not solely involve online education. Nevertheless, digital literacy is a beneficial skill for all students that helps bolster online learning attitudes and reduce overall school alienation.

Exploring Employee Well-Being during the COVID-19 Remote Work: Evidence from South Africa

Purpose: The COVID-19 pandemic has rapidly accelerated a shift to remote working for previously office-based employees in South Africa, impacting employee outcomes such as well-being. The remote work trend is expected to continue even post the pandemic, necessitating for organizational understanding of the factors impacting employee well-being. Using the Job Demands-Resources model as the theoretical framework, this study aims to understand the role of job demands and resources as predictors of employee well-being in the pandemic context. Design/methodology/approach: A self-administered online survey questionnaire was used to gather quantitative data about remote workers' (n = 204) perceptions of specifically identified demands, resources and employee well-being. Descriptive statistics, Pearson's correlation and moderated hierarchical regression were used to analyse the data. Findings: This study found that job demands in the form of work-home conflict were associated with reduced employee well-being. Resources, namely, job autonomy, effective communication and social support were associated with increased employee well-being. Job autonomy was positively correlated to remote work frequency, and gender had a significant positive association to work-home conflict. Social support was found to moderate the relationship between work-home conflict and employee well-being. Findings suggest that organizations looking to enhance the well-being of their remote workforce should implement policies and practices that reduce the demands and increase the resources of their employees. The significant association of gender to work-home conflict suggests that greater interventions are required particularly for women. This study advances knowledge on the role of demands and resources as predictors of employee well-being of remote workforces during COVID-19 and beyond. Originality/value: This paper provides insight on employee well-being during COVID-19 remote work. Further, the findings suggest that organizations looking to enhance the well-being of their remote workforce should implement policies and practices that reduce the demands and increase the resources of their employees. The significant association of gender to work-home conflict suggests that greater interventions are required particularly for women. To the best of the authors' knowledge, this is the first study carried out to explore the employee well-being during COVID-19 pandemic and will be beneficial to stakeholders for understanding the factors impacting employee well-being.

The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID19 Pandemic

The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they can provide for the current pandemic management. This work proposes using the susceptible-exposed-asymptomatic but infectious-symptomatic and infectious-recovered-deceased (SEAIRD) model for different learning models. The first analysis considers an unsupervised prediction, based directly on the epidemiologic compartmental model. After that, two supervised learning models are considered integrating computational intelligence techniques and control engineering: the fuzzy-PID and the wavelet-ANN-PID models. The purpose is to compare different predictor strategies to validate a viable predictive control system for the COVID19 relevant epidemiologic time series. For each model, after setting the initial conditions for each parameter, the prediction performance is calculated based on the presented data. The use of PID controllers is justified to avoid divergence in the system when the learning process is conducted. The wavelet neural network solution is considered here because of its rapid convergence rate. The proposed solutions are dynamic and can be adjusted and corrected in real time, according to the output error. The results are presented in each subsection of the chapter. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Awareness and Knowledge of Carpal Tunnel Syndrome among Adult Saudi Population

Introductions: The median nerve's occasional or persistent compression or entrapment in the carpal tunnel from the wrist to the hand causes carpal tunnel syndrome (CTS). The main symptoms are pain, tingling, swelling, and loss of grip strength and function in the thumb, index finger, middle finger, and thumb of thumb. This study examined Saudi adults' awareness and understanding of Carpal Tunnel Syndrome and its link with demographics and chronic conditions. Material(s) and Method(s): This cross-sectional study examined adults' knowledge, attitudes, and practices regarding carpal tunnel syndrome from 2021 to 2022 in different Saudi Arabian regions. This study used a researcher-created questionnaire. In the awareness category, general public questions included CTS clinical aspects, etiology, and effects on daily life. Practice questions covered CTS preventive and chronic diseases. Volunteers were selected following informed consent. Result(s): 420 participants aged 34.8 +/- 13.49 years. 280 (66.6%) were male, 140 (33.3%) females. 38 (9.04%) were non-Saudi workers, while 384 were Saudis. 235 (55.9%) individuals knew about wrist CTS and 161 (38.3%) about pain. 157 (37.3%) individuals experienced thumb tingling or numbness, while 117 and 142 agreed that CTS may produce thumb weakness (27.8%) and hand grip (35.2%). The older age group reported more thumb numbness or tingling than the other groups, although there was no statistical difference (p= 0.09). CTS was not associated with chronic disease;however, diabetes was the main comorbidity in all age groups (44;45.3%), especially in the middle age group (21;60%). 5.4% had CTS. CTS was rare during pregnancy (0.7%), however all age groups agreed that it could influence their employment and social life (p= 0.014 and < 0.00001). The average knowledge score was 43.3 +/- 40.5, whereas the awareness score was 50.1 +/- 44.2. These findings indicate that Saudis were aware of CTS clinical symptoms. Conclusion(s): The study examined Saudi adults' awareness and understanding of CTS and estimated the association between CTS and demographics and chronic conditions. The study found that adult CTS awareness and knowledge were sufficient and associated with age and quality of life. CTS awareness campaigns may lower risk and raise knowledge of prevention and treatment. People who work with discomfort or use computers for long periods of time without breaks are more prone to develop CTS. Larger research is needed to understand how physical exercise causes CTS.Copyright © 2023, Ibn Sina Trust. All rights reserved.

Prevalence and predictors of depression, anxiety, and stress among recovered COVID-19 patients in Vietnam.

Background: During the COVID-19 pandemic, a high prevalence of mental health distress has been reported among people who have recovered from the disease. Objectives: To assess the prevalence of depression, anxiety, and stress as well as identify predictors among recovered COVID-19 patients after more than six months of being discharged in Dong Thap Province, Vietnam. Material and methods: The cross-sectional study was conducted among 549 eligible participants recruited by stratified sampling. Data was collected using the depression, anxiety and stress scale - 21 items had Content Validity Index = 0.9, and Cronbach's alpha for depression, anxiety and stress sub-scales were 0.95, 0.81, and 0.86, respectively. Descriptive statistics were used to measure the prevalence levels and distribution of characteristics of the participant, while factors influencing depression, anxiety, and stress were predicted using binary logistic regression. Results: The overall prevalence of depression, anxiety, and stress were 24.8% (95% CI: 21.2-28.6), 41.5% (95% CI: 37.4-45.8), and 25.3% (95% CI: 21.7-29.2), respectively. The predictors of depression were living in urban area (OR = 1.97; 95% CI: 1.27-3.08), holding a bachelor's degree (OR:3.51; 95% CI: 1.13-10.8), having a high monthly income (OR: 2.57; 95% CI: 1.03-6.38), diabetes (OR: 2.21; 95% CI: 1.04-4.68), heart disease (OR: 3.83; 95% CI: 1.79-8.17), respiratory disease (OR: 3.49; 95% CI: 1.24-9.84), and diarrhea (OR: 4.07; 95% CI: 1.06-15.6). Living in the urban area (OR: 1.57; 95% CI: 1.07-2.29), having sleep disturbance (OR: 2.32; 95% CI: 1.56-3.46), and fatigue (OR: 1.57; 95% CI: 1.03-2.39) were predictors for anxiety. Having respiratory disease (OR: 3.75; 95% CI: 1.47-9.60) or diarrhea (OR: 4.34; 95% CI: 1.18-15.9) were predictors of stress. Conclusion: People who have recovered from COVID-19 should be assessed for symptoms of depression, anxiety, and stress. Primary healthcare providers should develop interventions to support their recovery.

Risk factors for disease severity among children with Covid-19: a clinical prediction model.

BACKGROUND: Children account for a significant proportion of COVID-19 hospitalizations, but data on the predictors of disease severity in children are limited. We aimed to identify risk factors associated with moderate/severe COVID-19 and develop a nomogram for predicting children with moderate/severe COVID-19. METHODS: We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the state's pediatric COVID-19 case registration system. The primary outcome was the development of moderate/severe COVID-19 during hospitalization. Multivariate logistic regression was performed to identify independent risk factors for moderate/severe COVID-19. A nomogram was constructed to predict moderate/severe disease. The model performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and accuracy. RESULTS: A total of 1,717 patients were included. After excluding the asymptomatic cases, 1,234 patients (1,023 mild cases and 211 moderate/severe cases) were used to develop the prediction model. Nine independent risk factors were identified, including the presence of at least one comorbidity, shortness of breath, vomiting, diarrhea, rash, seizures, temperature on arrival, chest recessions, and abnormal breath sounds. The nomogram's sensitivity, specificity, accuracy, and AUC for predicting moderate/severe COVID-19 were 58·1%, 80·5%, 76·8%, and 0·86 (95% CI, 0·79 - 0·92) respectively. CONCLUSION: Our nomogram, which incorporated readily available clinical parameters, would be useful to facilitate individualized clinical decisions.

[Treatment of toxic hepatitis in COVID-19 patients].

BACKGROUND: The article reflects the clinical significance of the early diagnosis of toxic hepatitis in patients who have undergone a new coronavirus infection with the determination of clinical and laboratory predictors of the response to therapy. A dynamic analysis of the effectiveness of toxic hepatitis therapy in patients of three experimental groups and a control group is presented. AIM: The aim of the present study is to increase the effectiveness of the treatment of toxic hepatitis in patients who have undergone COVID-19. MATERIALS AND METHODS: On the basis of the newly created infection centers of the Central Clinical Hospital "RZhD-Medicine" and Vishnevsky 3-rd Central Military Clinical Hospital 996 patients with COVID-19, who had clinical and laboratory signs of toxic liver damage (cytolytic and/or cholestatic syndromes) against the background of COVID-19 therapy. RESULTS: On the 14th day from the start of therapy in group 3, there was a significant decrease in the clinical manifestations of jaundice in 163 (72.8%) patients, on the 21st day of treatment, this symptom was stopped in all patients. In groups 1 and 2, the decrease in clinical manifestations of jaundice was significantly lower - 122 (55.2%) and 134 (58.8%); p<0.05. At the end of therapy, no manifestations of jaundice were observed in all experimental groups, while in the control group, symptom reduction was achieved only in 47 (14.5%) patients. CONCLUSION: The use of drugs with hepatoprotective effect in the form of monotherapy in groups 1 (UDCA) and 2 (ademethionine) showed a low therapeutic effect with positive dynamics of clinical and laboratory indicators of toxic hepatitis activity. The use of combined treatment in group 3 (UDCA and ademethionine) demonstrated the maximum therapeutic effect, pronounced positive dynamics in the form of normalization of clinical and laboratory indicators of toxic hepatitis activity.

Method for determining predictor factor for worse outcomes in kidney transplant recipients infected with coronavirus disease 2019 in a systematic review and meta-analysis research.

The systematic review and meta-analysis were conducted for COVID-19 infections in kidney transplant patients. Recent research on this topic was still scarce and limited meta-analysis research discussion, specific to some risks or treatment in kidney transplantation patients with COVID-19 infection. Therefore, this article demonstrated the fundamental steps to conducting systematic review and meta-analysis studies to derive a pooled estimate of predictor factors of worse outcomes in kidney transplant patients with positive for the SARS-CoV- 2 test•PICOT Framework to determine the research scope•PRISMA strategy for study selection•Forest Plot for meta-analysis study.

Delayed Care Seeking and Outcomes of Testicular Torsion among Children during the COVID-19 Pandemic: A Systematic Review and Meta-Analysis

Introduction Since the onset of coronavirus disease 2019 (COVID-19), stay-at-home orders and fear caused by the pandemic have had a significant effect on the timing and outcomes of testicular torsion. However, the evidence was limited since the study results were inconsistent. This study aims to examine the hospitalization rates, timing, and outcomes of testicular torsion in children before and during the pandemic. Materials and Methods Using PubMed, Embase, and Google Scholar databases, we conducted a systematic search and meta-analysis of studies reporting the timing and outcomes of children admitted with testicular torsion before and during the COVID-19 pandemic. Subgroup analyses were conducted to explore possible sources of heterogeneity. Result The outcomes of 899 testicular torsion patients from eight studies were evaluated. Our study found an increased hospitalization rate for patients with testicular torsion (incidence rate ratio = 1.60, 95% confidence interval [CI]: 1.27-2.03;p = 0.001). Despite a significant increase in the duration of symptoms during the COVID-19 pandemic (weighted mean difference = 11.04, 95% CI: 2.75-19.33;p = 0.009), orchiectomy rates did not increase (odds ratio = 1.33, 95% CI: 0.85-2.10;p = 0.147). Conclusion During the COVID-19 pandemic, hospitalization rates for testicular torsion and the duration of symptoms among children increased significantly. Moreover, the rate of orchiectomy did not increase during the pandemic, indicating that pediatric emergency services have remained efficient and have prevented an increase in the number of orchiectomies performed despite pandemic-related closures and delays in transporting patients to medical care.

Americans' COVID-19 risk perceptions and risk perception predictors changed over time

Identifying and understanding risk perceptions—"how bad are the harms” to humans or to what they value that people see as potentially or actually arising from entities or events—has been critical for risk analysis, both for its own sake, and for expected associations between risk perceptions and subsequent outcomes, such as risky or protective behavior, or support for hazard management policies. Cross-sectional surveys have been the dominant method for identifying and understanding risk perceptions, yielding valuable data. However, cross-sectional surveys are unable to probe the dynamics of risk perceptions over time, which is critical to do while living in a dynamically hazardous world and to build causal understandings. Building upon earlier longitudinal panel studies of Americans' Ebola and Zika risk perceptions using multi-level modeling to assess temporal changes in these views and inter-individual factors affecting them, we examined patterns in Americans' COVID-19 risk perceptions in six waves across 14 months. The findings suggest that, in general, risk perceptions increased from February 2020 to April 2021, but with varying trends across different risk perception measures (personal, collective, affective, affect, severity, and duration). Factors in baseline risk perceptions (Wave 1) and inter-individual differences across waves differed even more: baseline ratings were associated with how immediate the threat is (temporal distance) and how likely the threat would affect people like oneself (social distance), and following the United States news about the pandemic. Inter-individual trend differences were shaped most by temporal distance, whether local coronavirus infections were accelerating their upward trend, and subjective knowledge about viral transmission. Associations of subjective knowledge and risk trend with risk perceptions could change signs (e.g. from positive to negative) over time. These findings hold theoretical implications for risk perception dynamics and taxonomies, and research design implications for studying risk perception dynamics and their comparison across hazards. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

SERVICE LEADERSHIP AND WORK PERFORMANCE: AN ANALYSIS FROM THE PERCEPTION OF PUBLIC SECTOR EMPLOYEES IN THE CONTEXT OF COVID-19.

Objective: This study sought to analyze whether service leadership predicts work performance on municipal employees in the province of San Martin - Peru, in the context of the COVID-19 pandemic. Material(s) and Method(s):The design is non-experimental, cross-sectional, and predictive. We analyzed data of 424 municipal employees from the districts: Morales, Tarapoto, and Banda Shilcayo, aged between 20 and 65 years, of both sexes. The instruments used were: Service Leadership Scale (ELSVA), created by Dennis,Winston, Page, and Wong (2003);and Individual Work Performance Scale, created by Koopmans et al., (2014), both scales validated by Gabini and Salessi (2016). Result(s) and Conclusion(s): The beta coefficients indicate that leadership (predictor variable) significantly predicted work performance (beta =,512, p < .01);it is inferred that service leadership qualities of employees predict the effectiveness of workers in their respective job positions.Copyright © 2023, Accion Medica S.A.. All rights reserved.

Clinical profile and outcomes of patients with COVID-19 respiratory failure requiring renal replacement therapy: a machine learning analysis of 13,576 patients

Introduction: Acute kidney injury (AKI) is a frequent and severe complication of COVID-19 infection in ICU patients. We propose a structured data-driven methodology and develop a model to predict the use of renal replacement therapy for patients on respiratory support with Covid-19 in 126 ICUs from 42 Brazilian hospitals. Method(s): Adult ICU patients (March 2020-December 2021) with confirmed SARS-CoV-2 infection and need of ventilatory support at D1 admission in the ICU. Main outcome was the need of RRT. We estimated 3 prediction models: Logistic Regression (LR), Random Forest (RF) and XGB Boosting. Models were derived in the training set and evaluated in the test set following an 80/20 split ratio, and models' parameters were selected using fivefold cross-validation. We evaluated and selected the best model in terms of discrimination (AUC) and calibration (Brier's Score). Variable importance was estimated for each predictor variable. Result(s): 13,575 ICU patients with need of respiratory support, of which 1828 (14%) needed RRT. ICU and hospital mortality were respectively 15.7%, 20.3% (non-RRT) and 54.3%, 69% (RRT). Mean age was 63.9 and 55.3 years (RRT vs non-RRT). Mean ICU LOS was 27.8 vs. 12 days, in RRT vs non-RRT. RF and XGB models both showed higher discrimination performance compared to LR (95% confidence interval [95% CI]: 0.84 [0.81-0.85] and 0.83 [0.80-0.85] vs 0.78 [0.75-0.80]). RF and XGB models presented similar calibration (Brier's Score: ([95% CI]: 0.09 [0.09- 0.10] and 0.09 [0.09-0.10]), also better than in LR (0.11 [0.10-0.12]). The final model (RF) showed no sign of under or overestimation of predicted probabilities in calibration plots. Conclusion(s): The need of RRT among patients on respiratory support diagnosed with Covid-19 was accurately predicted through machine learning methods. RF and XGB based models using data from general intensive care databases provides an accurate and practical approach for the early prediction of use of RRT in COVID-19 patients.

Exploring Bhutanese Primary School Teachers' Technological Knowledge

The COVID-19 pandemic has disrupted the normal functions of schools globally. Online learning is a new concept in Bhutan. Nonetheless, classes have begun using various online learning platforms to continue their operations during the pandemic. This study examined primary school teachers' perceived information technology knowledge and proficiency. The participants of this study consisted of 124 primary teachers from two western districts of Bhutan. Data were collected using an online survey. The study's findings suggested that although the majority of participants (98.2%) had access to personal digital devices, slow internet connection and high internet data subscription charges (60.7%) were cited as significant challenges. Findings also revealed that a small percentage of the participants, less than 12 (9.7%) teachers in this study preferred to teach entirely in an online learning environment. The results of multiple linear regression suggested that only technological pedagogical knowledge (TPK) [t = 2.68, p = 0.008, [beta] = 0.236] and perceived information technology proficiency of teachers (PITP) [t = 3.55, p = 0.001, [beta] = 0.306] were statistically significant predictors of technological knowledge (TK).

Ferritin level predicts in-hospital mortality in hypertensive patients with COVID-19

Aim. This study aimed to establish the predictive ability of serum ferritin levels for severe / critical condition development, need for supplemental oxygen, and in-hospital mortality in hypertensive patients with COVID-19-associated pneumonia.Materials and methods. 135 unvaccinated patients hospitalized for COVID-19-associated pneumonia were enrolled in the study. 78.5 % of patients were hypertensive.Results. Among hypertensive patients, the median ferritin level at admission was 315.5 (169.0-396.0) ng/mL in patients with moderate condition, 374.0 (171.0-709.5) ng/mL in patients developed severe condition, and 489.0 (362.0-1128.5) ng/mL in pa-tients developed critical condition (P = 0.03). Serum ferritin level at admission was higher in non-survivors (539.0 (440.0-1128.5) ng/mL) than that in survivors (332.5 (172.0-545.0) ng/mL, P = 0.02). Hypertensive patients who required supplemental oxygen had higher median serum ferritin level (446.0 (187.0-763.0) ng/mL) than patients without the requirement of supplemental oxygen (324.0 (165.0-401.0) ng/mL, P = 0.02). There was poor discrimination ability of ferritin level in the prediction of severe / critical conditions (AUC = 0.628, P = 0.02) and the need for supplemental oxygen (AUC = 0.629, P = 0.02). There was an acceptable discrimination ability of ferritin level in the in-hospital mortality prediction (AUC = 0.701, P = 0.03);the Youden index was 0.54, the associated criterion was >438.0 ng/mL with 83.3 % sensitivity and 70.7 % specificity. Ferritin level >438.0 ng/mL at admission was associated with a significant increase in in-hospital mortality (OR = 12.04 (2.47-58.62), P = 0.002).Conclusions. Serum ferritin level at hospital admission increases with the severity of COVID-19 in hypertensive patients. Serum ferritin level predicts in-hospital mortality in hypertensive patients. However, its predictive ability for the disease progression to severe/critical conditions and the need for supplemental oxygen is poor. A ferritin level of 438.0 ng/mL is proposed to be a cut-off value for the prediction of in-hospital mortality.

Prevalence of adverse drug reactions associated with emergency department visits and risk factors for hospitalization

Objective: Adverse drug reactions increase morbidity and mortality, prolong hospital stay and increase healthcare costs. The primary objective of this study was to determine the prevalence of emergency department visits for adverse drug reactions and to describe their characteristics. The secondary objective was to determine the predictor variables of hospitalization for adverse drug reactions associated with emergency department visits. Method(s): Observational and retrospective study of adverse drug reactions registered in an emergency department, carried out from November 15th to December 15th, 2021. The demographic and clinical characteristics of the patients, the drugs involved and the adverse drug reactions were described. Logistic regression was performed to identify factors related to hospitalization for adverse drug reactions. Result(s): 10,799 patients visited the emergency department and 216 (2%) patients with adverse drug reactions were included. The mean age was 70 +/- 17.5 (18-98) years and 47.7% of the patients were male. A total of 54.6% of patients required hospitalization and 1.6% died from adverse drug reactions. The total number of drugs involved was 315 with 149 different drugs. The pharmacological group corresponding to the nervous system constituted the most representative group (n = 81). High-risk medications, such as antithrombotic agents (n = 53), were the subgroup of medications that caused the most emergency department visits and hospitalization. Acenocumarol (n = 20) was the main drug involved. Gastrointestinal (n = 62) disorders were the most common. Diarrhea (n = 16) was the most frequent adverse drug reaction, while gastrointestinal bleeding (n = 13) caused the highest number of hospitalizations. Charlson comorbidity index behaved as an independent risk factor for hospitalization (aOR 3.24, 95% CI: 1.47-7.13, p = 0.003, in Charlson comorbidity index 4-6;and aOR 20.07, 95% CI: 6.87-58.64, p = 0.000, in Charlson comorbidity index >= 10). Conclusion(s): The prevalence of emergency department visits for adverse drug reactions continues to be a non-negligible health problem. High-risk drugs such as antithrombotic agents were the main therapeutic subgroup involved. Charlson comorbidity index was an independent factor in hospitalization, while gastrointestinal bleeding was the adverse drug reaction with the highest number of hospital admissions.Copyright © 2022 Sociedad Espanola de Farmacia Hospitalaria (S.E.F.H)

On a Fractional Variable-Order Model of MERS-CoV

In this paper, a non-integer variable-order epidemiological model is presented to study the human-to-human transmission of Middle East respiratory syndrome coronavirus (MERS-CoV) pandemic in two areas. In the presented SISImodel, the human population is divided into two compartments;susceptible and infectious compartments. The impact of the memory which changes with time in the sense of Caputo's derivative of fractional variable-order is studied through the numerical solutions of the proposed model. The numerical solutions are obtained via predictor corrector method. Moreover, the equilibrium points and stability of the model are illustrated. © 2023 NSP Natural Sciences Publishing Cor

A case study of Covid-19 epidemic in India via new generalised Caputo type fractional derivatives.

The first symptomatic infected individuals of coronavirus (Covid-19) was confirmed in December 2020 in the city of Wuhan, China. In India, the first reported case of Covid-19 was confirmed on 30 January 2020. Today, coronavirus has been spread out all over the world. In this manuscript, we studied the coronavirus epidemic model with a true data of India by using Predictor-Corrector scheme. For the proposed model of Covid-19, the numerical and graphical simulations are performed in a framework of the new generalised Caputo sense non-integer order derivative. We analysed the existence and uniqueness of solution of the given fractional model by the definition of Chebyshev norm, Banach space, Schauder's second fixed point theorem, Arzel's-Ascoli theorem, uniform boundedness, equicontinuity and Weissinger's fixed point theorem. A new analysis of the given model with the true data is given to analyse the dynamics of the model in fractional sense. Graphical simulations show the structure of the given classes of the non-linear model with respect to the time variable. We investigated that the mentioned method is copiously strong and smooth to implement on the systems of non-linear fractional differential equation systems. The stability results for the projected algorithm is also performed with the applications of some important lemmas. The present study gives the applicability of this new generalised version of Caputo type non-integer operator in mathematical epidemiology. We compared that the fractional order results are more credible to the integer order results.

The analysis of a time delay fractional COVID-19 model via Caputo type fractional derivative.

Novel coronavirus (COVID-19), a global threat whose source is not correctly yet known, was firstly recognised in the city of Wuhan, China, in December 2019. Now, this disease has been spread out to many countries in all over the world. In this paper, we solved a time delay fractional COVID-19 SEIR epidemic model via Caputo fractional derivatives using a predictor-corrector method. We provided numerical simulations to show the nature of the diseases for different classes. We derived existence of unique global solutions to the given time delay fractional differential equations (DFDEs) under a mild Lipschitz condition using properties of a weighted norm, Mittag-Leffler functions and the Banach fixed point theorem. For the graphical simulations, we used real numerical data based on a case study of Wuhan, China, to show the nature of the projected model with respect to time variable. We performed various plots for different values of time delay and fractional order. We observed that the proposed scheme is highly emphatic and easy to implementation for the system of DFDEs.