COVID-19 Cases Research Articles

Comprehensive In silico and In vitro evaluation of Plectranthus amboinicus essential oil: A promising inhibitor of SARS-CoV-2 B.1.1.529 Omicron variant, proinflammatory biomarkers and diabetes-related enzymes

Existing challenges, such as the viral SARS-CoV-2 B.1.1.529 Omicron variants, adverse reactions, and limited availability of drugs for COVID-19 continue to challenge global health. Severe inflammatory response associated with COVID-19 has been shown to worsen diabetic conditions and finding a range of treatment options for COVID-19 is significant. The research investigated the potential of Plectranthus amboinicus (Lour.) Spreng. (Lamiaceae) essential oil (PEO), known for its bioactive terpene content, as a multifaceted therapeutic agent. In silico and in vitro approaches were conducted to evaluate its inhibitory effects on the replication of Omicron variant, its ability to modulate proinflammatory biomarkers, and its impact on diabetes-related enzymes. PEO was extracted by hydrodistillation method. GC-MS analysis revealed 62 compounds. In silico molecular docking showed that the top ten PEO major components exhibited strong binding affinities with Omicron 3CL protease (-4.0 to −6.1 kcal/mol) and spike-RBD protein (-6.1 to −9.2 kcal/mol). PEO (6.25–200 μg mL⁻¹) significantly inhibited the B.1.1.529 Omicron SARS-CoV-2 3CL protease and Spike-RBD. PEO showed a cytotoxic effect at >80 μg mL⁻¹ in LPS-induced macrophage and inhibited production of TNF-α from 6.25 to 50 μg mL⁻¹, indicating its potential to mitigate the cytokine storm in link with severe COVID-19 cases. In vitro, PEO at 6.25–200 μg mL⁻¹ significantly inhibited α-amylase and α-glucosidase enzymes, suggesting that PEO components could modulate key enzymes involved in glucose metabolisms. These findings showed the potential of PEO as an antiviral, anti-inflammatory, and antidiabetic agent and offer an opportunity to further clinical investigations in testing the efficacy as an alternative approach to managing COVID-19 and its complications.

An integrated approach for decomposing time series data into trend, cycle and seasonal components

ABSTRACT This study presents a methodology for decomposing time series data into trend, seasonal, and cyclical components using the moving linear model approach by Kyo and Kitagawa (Journal of Business Cycle Research, 19(3): 373-397, 2023). Our approach integrates seasonal adjustment and decomposition into a single framework. We evaluated our approach with two case studies: examining daily COVID-19 case data and the Index of Industrial Production (IIP) in Japan, comparing the results to seasonally adjusted IIP data. Performance metrics included the discrimination power index and the variance of the adjusted cyclical component. Our findings show that our method effectively extracts business cycle information, achieving higher discrimination power and greater adjusted variance compared to seasonally adjusted IIP data, highlighting the superior performance of our integrated seasonal adjustment method. We compared the proposed approach with a state-space modelling method by introducing an overall stability as a new indicator. The results demonstrated the stability of the estimations obtained with our proposed method.

Clinical characteristics of COVID-19 patients admitted to the intensive care unit of the largest public-sector hospital in Karachi: A retrospective, observational study.

Objective: To characterize the clinical features of critically ill COVID-19 patients admitted to COVID-ICU and describe their outcomes. Study Design: Retrospective Observational study. Setting: Dr. Ruth K. M. Pfau Civil Hospital Karachi, Pakistan. Period: May 2020 to September 2021. Methods: The study aimed to investigate the clinical characteristics and outcomes of patients with confirmed or suspected COVID-19 who were admitted to the ICU. Patients in the study period confirmed or suspected COVID-19, admitted to the ICU for more than 24 hours, and committed to full treatment were included this study. Patients with COVID-19 discharged or died within 24 hours of admission were excluded. Results: The most commonly observed symptoms among the patients were shortness of breath (92.5%), fever (91.2%), cough without sputum (39.2%), altered consciousness (11.9%), and muscle aches (8.8%). Acute respiratory distress syndrome (ARDS) was identified as the most prevalent complication among COVID-19 patients, impacting 40.8% of the study population. A significant proportion of COVID-19 patients required mechanical ventilation and cardiac support. Specifically, (41.4%) of the patients required invasive mechanical ventilation, (47.4%) required non-invasive ventilation, and (26.3%) received cardiac support. Laboratory assessment showed that platelet counts varied significantly between survivors and non-survivors, with non-survivors exhibiting lower platelet counts. Gender differences were also observed among COVID-19 patients by age, with males having a higher mean age than females in all age categories, and the difference was statistically significant (p < 0.001) in all age categories except for the 30-44 years age category (p = 0.087). Age-wise recovery and mortality rates were analyzed, and the results showed that among both deceased and recovered patients, the proportion of deceased patients increased with age, while the proportion of recovered patients increased until the age range of 45-59 years for both males and females. The study found that 136 of the patients survived while 275 of the patients succumbed to the disease. Among the survivors, (31.3%) were male, and (36.2%) were female. Conclusion: The study emphasizes the importance of monitoring patients for potential complications and providing them with supportive care. Early detection and management of severe cases of COVID-19 are critical in preventing complications and improving patient outcomes.

The impact of radiologists’ characteristics on the detection of COVID-19 in chest CT scans

PurposeTo retrospectively assess the relationships between radiologists’ characteristics and their performance in interpreting chest CTs for COVID-19 detection. MethodsUsing DetectedX software, performance data were collected online from 74 radiologists from 29 countries, who each interpreted 30 anonymized digital chest CTs (15 positive and 15 negative scans for COVID-19). Radiologist-specific information was also collected: radiology experience, radiological specialty, number of lung CTs read weekly, familiarity with and education about COVID-19 presentation, and suspected COVID-19 cases seen weekly. The influence of this radiologist-specific information on the radiologists’ sensitivity, specificity, and ROC AUC was determined using regression analysis. ResultsRadiologists without respiratory imaging specialization had greater ROC AUCs (0.83 vs. 0.70, p = .006) and sensitivities (74.0% vs. 47.7%, p = .002) than their specialized peers. Radiologists without COVID-19 case encounters had greater sensitivity (80.6% vs. 63.1%, p = .017) but lower specificity (71.1% vs. 83.4%, p = .014) than those who encountered at least one case weekly. ConclusionSpecialization and prior experience with COVID-19 may impact the interpretation of suspected COVID-19 chest CTs. Clinical significanceThese results show the importance of diverse expertise and continuous training in managing novel diseases like COVID-19. Incorporating varied perspectives and experiences could enhance diagnostic accuracy and ensure a more comprehensive approach to disease management. In the case of novel diseases, specialization may not provide the same advantage as with more familiar disorders. The diagnostic value of specific experience with a novel disorder may help to compensate for a lack of specialization in the field, particularly in emergent situations. While specialization is important, generalization also holds value and utility in appropriate contexts.

Can Massive Religious Festival Celebrations Encourage a Faster Spread of a Pandemic? The Case of COVID-19 in Israel.

This paper attempts to evaluate how massive religious festivalcelebrations can encourage the faster spread of any pandemic according to our problem statement, such as the case of COVID-19. For example, we evaluate Israel's three major religions, namely Judaism, Christianity, and the Islamic festival celebrations, respectively. Firstly, we have the traditional Jewish festivities such asHanukkah, Yom Kippur, Sukkot, and Rosh Hashanah. In the Christian's traditional festivities celebrations, we identified Christmas, Easter Day, and All Saints Day. Finally, the Muslim festivities ofMuharram and the Birthday of theHoly Prophet Mohamad. Thepurpose of thisstudy wasto evaluate if these nine massive religious festival celebrations are the main reasons for the large spread of COVID-19 in Israel directly or indirectly. In fact, we propose a new methodology to evaluate the impact of any massive religious festivalcelebration andthe fast spread of any pandemic everywhere and anytime. The new indicator is entitled "The National Spread Levels of Infectious Diseases Risk from Massive Religious Festivities Index" (National-SLIDRMRF-Index). Finally, the major finding in this research is that any massive religious events can generate an exponential number of COVID-19 cases constantly. Therefore, this research concluded that we urgentlyneed a standardized index to monitor and control the expansion of any pandemic such as COVID-19 among different religious groups in the same country. At the same time, we give different policy recommendations to the Israeli government to constantlykeep major controls and measures ofdifferent religious events inJerusalem.

Assessing the influence of nursing home size and care models on COVID-19 case and mortality rates

IntroductionThis study examines the impact of COVID-19 on older adults in traditional nursing homes, Green Houses (GHs), and Continuing Care Retirement Communities-Nursing Homes (CCRCNHs). MethodsCOVID-19 cases and deaths from CMS and LTCFocus data across 11 states from 6/2020 to 9/2022 were used, and Poisson regressions to compare care settings while adjusting for covariates. ResultsCCRCNH and GH residents were older (84.4 and 83.1 years) than those in traditional NHs (77.5 and 77.6 years, p < 0.0001), with more female and White individuals. COVID-19 risk was higher in CCRCNHs (RR 1.51, 95 % CI 1.10–2.07), large NHs (RR 1.57, 95 % CI 1.14–2.15), and highest in small NHs (RR 1.80, 95 % CI 1.32–2.47). Mortality rates across NH types showed no significant difference. ConclusionThe study shows that smaller, person-centered GHs are more effective in controlling COVID-19 infection, suggesting a need to rethink care models to incorporating GH features for better outcomes.GEORGE2 07-AUG-2024 11:31.

Spatiotemporal Ecologic Analysis of COVID-19 Vaccination Coverage and Outcomes, Oklahoma, USA, February 2020-December 2021.

Data on COVID-19 cases, deaths, hospitalizations, and vaccinations in Oklahoma, USA, have not been systematically described. The relationship between vaccination and COVID-19-related outcomes over time has not been investigated. We graphically described data collected during February 2020-December 2021 and conducted spatiotemporal modeling of monthly increases in COVID-19 cumulative death and hospitalization rates, adjusting for cumulative case rate, to explore the relationship. A 1 percentage point increase (absolute change) in the cumulative vaccination rate was associated with a 6.3% (95% CI 1.4%-10.9%) relative decrease in death outcome during April-June 2021, and a 1.9% (95% CI 1.1%-2.6%) relative decrease in death outcome and 1.1% (95% CI 0.5%-1.7%) relative decrease in hospitalization outcome during July-December 2021; the effect on hospitalizations was driven largely by data from urban counties. Our findings from Oklahoma suggest that increasing cumulative vaccination rates might reduce the increase in cumulative death and hospitalization rates from COVID-19.

In silico exploration of phytocompounds from AYUSH-64 medicinal plants against SARS CoV-2 RNA-dependent RNA polymerase

BackgroundThe AYUSH 64 formulation helps to treat mild to moderate cases of COVID-19. Although several drugs have been proposed to combat COVID-19, no medication is available for SARS-CoV-2 infection. The RNA-dependent RNA polymerase (RdRp) is the pivotal enzyme of SARS-CoV-2 replication, so it could be considered a better drug target for experimental studies. ObjectiveThe AYUSH-64 formulation plants exhibited multiple therapeutic properties; thus, the present study aims to screen the phytocompounds of these plants against SARS CoV2 RdRp to identify specific compounds that could potentially affect COVID-19 infection. Materials and methodsPatchDock and AutoDock tools were used for docking experiments. MD simulations and Density Functional Theory (DFT) calculations of protein-ligand Picroside-I and Remdesivir complexes were carried out in GROMACS v2019.4 and Gaussian 09 software, respectively. ResultsAmong the tested, five phytocompounds (Picroside I, Oleanolic acid, Arvenin I, II, and III) from AYUSH-64 medicinal plants showed possible binding with RdRp catalytic residues (Ser759, Asp760, and Asp761). Of these, Picroside I exhibited hydrogen bond interactions with NTP entry channel residues (Arg553 and Arg555). The MM-PBSA free energy, RMSD, Rg, PCA, and RMSF analysis suggested that the Picroside I complex showed stable binding interactions with RdRp in the 50 ns simulation. In addition to this, Picroside I revealed its robust and attractive nature toward the target protein, as confirmed by DFT. ConclusionThe results of this study have proposed that Picroside I from AYUSH 64 medicinal plant compounds was the selective binder of catalytic and NTP entry channel residues of SARS-CoV2 RdRp thereby; it may considered as a potential inhibitor of SARS-CoV2 RdRp.

Effectiveness of Original Monovalent and Bivalent COVID-19 Vaccines Against COVID-19-Associated Hospitalization and Severe In-Hospital Outcomes Among Adults in the United States, September 2022-August 2023.

Assessments of COVID-19 vaccine effectiveness are needed to monitor the protection provided by updated vaccines against severe COVID-19. We evaluated the effectiveness of original monovalent and bivalent (ancestral strain and Omicron BA.4/5) COVID-19 vaccination against COVID-19-associated hospitalization and severe in-hospital outcomes. During September 8, 2022 to August 31, 2023, adults aged ≥ 18 years hospitalized with COVID-19-like illness were enrolled at 26 hospitals in 20 US states. Using a test-negative case-control design, we estimated vaccine effectiveness (VE) with multivariable logistic regression adjusted for age, sex, race/ethnicity, admission date, and geographic region. Among 7028 patients, 2924 (41.6%) were COVID-19 case patients, and 4104 (58.4%) were control patients. Compared to unvaccinated patients, absolute VE against COVID-19-associated hospitalization was 6% (-7%-17%) for original monovalent doses only (median time since last dose [IQR] = 421 days [304-571]), 52% (39%-61%) for a bivalent dose received 7-89 days earlier, and 13% (-10%-31%) for a bivalent dose received 90-179 days earlier. Absolute VE against COVID-19-associated invasive mechanical ventilation or death was 51% (34%-63%) for original monovalent doses only, 61% (35%-77%) for a bivalent dose received 7-89 days earlier, and 50% (11%-71%) for a bivalent dose received 90-179 days earlier. Bivalent vaccination provided protection against COVID-19-associated hospitalization and severe in-hospital outcomes within 3 months of receipt, followed by a decline in protection to a level similar to that remaining from previous original monovalent vaccination by 3-6 months. These results underscore the benefit of remaining up to date with recommended COVID-19 vaccines.

Association of thrombophilic genes (MTHFR, MTR and MTRR) polymorphisms and homocysteine level in relation to the increased risk of thrombosis among COVID-19 patients

BackgroundPatients with COVID-19 have an increased risk of thrombosis and coagulopathy. Homocysteine, an amino acid essential to coagulation, is thought to be involved in such conditions, as its level is mediated by the presence of some single nucleotide polymorphisms (SNPs) in certain genes including MTHFR, MTR and MTRR. AimThe current study aimed to assess the significant role of MTHFR (C677T and A1298C), MTR A2756G and MTRR A66G SNPs as risk factors for thrombosis among Egyptian COVID-19 patients and their effect on homocysteine level. Subjects and methodsThis case-control study was carried out on 90 Egyptian COVID-19 cases, divided into 45 non-complicated cases and 45 complicated cases with thrombosis, in addition to 80 healthy control individuals. DNA was isolated from blood samples of all the participants. The genotyping was performed using real-time PCR; in addition, serum homocysteine level was estimated. ResultsThe MTHFR (C677T and A1298C), MTR A2756G and MTRR A66G variants revealed a significant higher risk of thrombosis under different genetic models including the homozygous comparison of the co-dominant (20 % vs. 2.3 %, OR = 15.88, p = 0.007), the dominant (62.2 % vs. 33.3 % OR = 3.29, p = 0.006) and the allelic models (41.1 % vs. 17.8 %, OR = 3.2, p < 0.001) for MTHFR C677T and also the dominant (77.8 % vs. 51.1 %, OR = 3.3, p = 0.008) and the allelic models (52.2 % vs. 31.1 %, OR = 2.4, p = 0.004) for MTHFR A1298C. In addition, the heterozygous comparison of the co-dominant (60 vs. 11.1, OR = 12.7, p < 0.001), the dominant (62.2 % vs. 11.1 %, OR = 13.1, p < 0.001) and the allelic models (32.2 % vs. 5.6 %, OR = 8.08, p < 0.001) for MTR A2756G and the heterozygous and homozygous comparisons of the co-dominant model [(53.3 % vs. 31.1 %, OR = 3.4, p = 0.03) and (13.4 % vs. 2.2 %, OR = 12.0, p = 0.049), respectively], the dominant (66.4 % vs. 33.3 %, OR = 4.0, p = 0.001) and the allelic models (40 % vs. 17.8 %, OR = 3, p = 0.001) for MTRR A66G. Moreover, MTHFR (C677T and A1298C), MTR A2756G, and MTRR A66G variants were also associated with high levels of serum homocysteine (p = 0.045, 0.001, 0.005 and 0.039, respectively). The homocysteine level was related to the disease severity by its correlation with higher LDH (rs = 0.49, p < 0.001), CRP (rs = 0.44, p < 0.001), IL-6 (rs = 0.46, p < 0.001) and D-dimer (rs = 0.66, p < 0.001) levels. The multivariate regression analysis showed that homocysteine and the dominant models of MTHFR (C677T and A1298C), MTR A2756G and MTRR A66G were independent predictors of susceptibility to thrombosis among COVID-19 patients [(OR = 1.02, p = 0.007), (OR = 1.15, p = 0.043), (OR = 1.2, p = 0.024), (OR = 1.42, p < 0.001), (OR = 1.19, p = 0.021), respectively]. ConclusionMTHFR (C677T and A1298C), MTR A2756G, and MTRR A66G gene variants were associated with high homocysteine and D-dimer levels that carried a risk for thrombosis among COVID-19 patients and associated with the disease progression.

Comparison of the therapeutic effect of Paxlovid and Azvudine in the treatment of COVID-19: A retrospective study

BackgroundCOVID-19 pneumonia has spread across China and globally since late 2019, becoming a pandemic. Its extremely contagious nature as well as high morbidity and mortality rates have attracted widespread attention globally. For the treatment of SARS-CoV-2 pneumonia, two commonly used antiviral drugs in the clinic are nirmatrelvir/ritonavir(Paxlovid) and Azvudine, while the therapeutic efficacy of the two drugs and their impact on patient prognosis remain inconclusive. Therefore, the aim of this study is to investigate the effects of two antiviral drugs, Azvudine and Paxlovid, on the disease development and prognosis of patients with COVID-19. MethodsThis study collected and analyzed in Inner Mongolia hospital treated 267 cases of COVID - 19 patients. According to the use of antiviral medications, the participants in this experiment were split into the Azvudine and Paxlovid groups. The effectiveness of the medications was evaluated using the length of hospitalization, Nucleic acid into negative time for the first time, and laboratory indices such as total protein, lymphocytes, leukocytes, albumin, creatinine, and platelets. ResultsCompared with the Azvudine group, patients in the Paxlovid group had a shorter recovery time, a higher degree of rise in lymphocytes, a faster recovery of the immune system, a lower rise in creatinine, and a lesser renal burden, but patients in the Paxlovid group had a greater decrease in total protein. ConclusionIn assessing patient conditions for treatment selection, Paxlovid may be preferable for individuals with renal insufficiency or those exhibiting compromised immune responses. Conversely, for patients experiencing malnutrition or cirrhotic hypoproteinemia, Azvudine could be considered to mitigate the reduction in protein levels.

Mutational and evolutionary dynamics of non-structural and spike proteins from variants of concern (VOC) of SARS-CoV-2 in India

Monitoring the genetic diversity and emerging mutations in SARS-CoV-2 remains crucial for understanding its evolution, given the virus's persistence in India. This study analyzes lineage dynamics, mutation screening, structural analysis, and phylodynamics of SARS-CoV-2 variants of concern (VOC) in India from October 2020 to September 2023. The predominant variants identified were alpha, beta, delta, and omicron, with delta and omicron making up 76.05 % of sequenced genomes. The B.1.617.2 lineage of the delta variant was the major contributor to COVID-19 cases before the rise of omicron. Mutation screening of non-structural proteins (NSPs) and spike proteins revealed distinct profiles for each VOC. Co-mutation patterns were analyzed, showing structural and energetic alterations. Phylogenetic analysis indicated that nsp1, nsp3, nsp4, nsp13, and nsp14 were strongly associated with increased mutation load. The study also highlighted that nsp14 and spike have similar mutability patterns, underscoring nsp14's critical role in SARS-CoV-2 infectivity and persistence. This research provides a comprehensive view of SARS-CoV-2's evolution and persistence in India.

ANALYSIS FACTORS AFFECTING COVID-19 MORTALITY USING COUNT REGRESSION

The ”2019 novel coronavirus” known as “ the 2019-nCoV” or simply“COVID-19” has been declared by the World Health organization (WHO), in first quarter of 2020, as a world pandemic and a public health emergency of international concern. Alas, many details related to the COVID-19 have remained unsolved completely. The success of government strategies in fighting the COVID-19 relays mainly on the results from epidemiological or statistical studies. Statistical models play a major role in providing reliable results based on appropriate analyses. Traditional (one-part) models, mixture models and mixed-effects models for counts are used to investigate effects of the WHO-regions and Cumulated COVID-19 cases on the outcome variable COVID-19 new deaths tolls. Overall result reveals there is a strong association between number of new deaths COVID-19 with predictors including the WHO regions and cumulated cases.Besides, models that account for the overdispersion feature have smallest AICs and have reasonable regression model fits.

Exploring the air pollution with particulate matter - PM10, COVID-19 cases evolution in Romania and exposure to aeroallergens

Exploring the air pollution with particulate matter - PM10, COVID-19 cases evolution in Romania and exposure to aeroallergens

Estimation of Epidemiological Parameters for COVID-19 Cases in Burkina Faso Using African Vulture Optimization Algorithm (AVOA)

In this paper, we present a mathematical model that accounts for virus transmission through deceased individuals to simulate the dynamics of COVID-19 spread in Burkina Faso. The existence and uniqueness of the model’s solution have been proven. The basic reproduction number was calculated using the Jacobian determinant method. The stability of the disease-free and endemic equilibrium points was studied. To estimate the model parameters, we used African Vulture Optimization Algorithm (AVOA). We then used this algorithm to estimate the parameters of the developed model using daily reported COVID-19 cases in Burkina Faso from March 11 to April 20, 2020. The results obtained show that the proposed model is more realistic for simulating the spread of COVID-19 in Burkina Faso.

Performance of rapid antigen tests to detect SARS-CoV-2 variant diversity and correlation with viral culture positivity: implication for diagnostic development and future public health strategies.

Despite the availability of vaccines, COVID-19 continues to be a major health concern, and antigen-based rapid diagnostic tests (Ag-RDTs) are commonly used as point-of-care or at-home diagnostic tests. In this study, we evaluated the performance of two commercially available Ag-RDTs and a research Ag-RDT to detect multiple SARS-CoV-2 variants using upper respiratory tract swab samples from clinical COVID-19 cases. Furthermore, we determined whether Ag-RDT results correlated with culture positivity, a potential proxy of viral transmissibility. Our results have important implications to inform future testing and response strategies during periods of high COVID-19 transmission with new variants.

Repeated time-series cross-validation: A new method to improved COVID-19 forecast accuracy in Malaysia

Forecasting COVID-19 cases is challenging, and inaccurate forecast values will lead to poor decision-making by the authorities. Conversely, accurate forecasts aid Malaysian government authorities and agencies (National Security Council, Ministry of Health, Ministry of Finance, Ministry of Education, and Ministry of International Trade and Industry) and financial institutions in formulating action plans, regulations, and legal acts to control COVID-19 spread in the country. Therefore, this study proposes Repeated Time-Series Cross-Validation, a new data-splitting strategy to identify the best forecasting model that is capable of producing the lowest error measures value and a high percentage of forecast accuracy for COVID-19 prediction in Malaysia. Some of the highlights of the proposed method are:•A total of 21 models, five data partitioning sets, and four error measures to improve the forecast accuracy of daily COVID-19 cases in Malaysia.•The best model selected produces the lowest error measure value for the Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Absolute Scaled Error (MASE).•The average 8-day forecast accuracy is 90.2 %. The lowest and highest forecast accuracy was 83.7 % and 98.7 %.

Significantly Increased Public Interest in Sleep Disorder during the COVID-19 Pandemic: An Analysis of Google Trends Data

Background: The COVID-19 pandemic has had a profound impact on sleep disorders. Previous studies have shown that people's sleep time is delayed. Methods: Analyze the public's interest to the keyword "sleep disorder" during the COVID-19 pandemic from December 2019 to December 2022 using Google Trends. The study also focused on the search trend data of the top three countries with high to low overall search frequency for this keyword. Results: It has been observed that during the peak period of the COVID-19 pandemic, the public's search interest for "sleep disorder" has significantly increased. Analyzing Google Trends from December 2019 to December 2022, the top three countries with high interest in searching for "sleep disorder" are the United States, the Philippines, and Canada. It shows that search interest in the United States is an increasing trend year by year, and the overall trend is relatively stable. The search trend for "sleep disorder" among Filipino netizens fluctuates greatly and is generally on a downward trend. The search trend for "sleep disorder" among Canadian netizens is moderate, and the overall trend is like that of Filipinos. It is worth noting that the Google Trends for "sleep disorder" among Filipino and Canadian netizens has changed from an overall increase to an overall decrease in 2020 as the watershed. This indicates a temporal correlation between the surge in COVID-19 cases and online search for "sleep disorder". Conclusion: It shows that public interest in "sleep disorder" has significantly increased during the COVID-19 pandemic, and there may be a certain correlation between the COVID-19 pandemic and sleep disorders. These are worthy of further exploration by researchers, especially the changes in people's daily routines caused by the COVID-19 pandemic, which in turn affect people's sleep quality.

Investigation the Role of Calcium and Vitamin D3 And Some Biochemical Parameters in Patients with Renal Failure of Renal Failure

Coronavirus Disease 2019 is a primarily respiratory illness that can cause thrombotic disorders. Elevation of D-dimer is a potential biomarker for poor prognosis in COVID-19, though optimal cutoff value for D-dimer to predict mortality has not yet been established. This study aims to assess the accuracy of admission D-dimer in the prognosis of COVID-19 and to establish the optimal cutoff D-dimer value to predict hospital mortality. Clinical and laboratory parameters and outcomes of confirmed COVID-19 cases admitted to four hospitals in Kathmandu were retrospectively analyzed. Admitted COVID-19 cases with recorded D-dimer and definitive outcomes were included consecutively. D-dimer was measured using immunofluorescence assay and reported in Fibrinogen Equivalent Unit (μg/ml). The receiver operating characteristic curve was used to determine the accuracy of D-dimer in predicting mortality, and to calculate the optimal cutoff value, based on which patients were divided into two groups and predictive value of D-dimer for mortality was measured. D-dimer levels were higher in COVID-19 patients and were related with markers of inflammation, and after treatments, D-dimer levels decreased which was synchronous with hsCRP levels in patients with good clinical prognosis. Also, the low correlation between Padua VTE score and D-dimer levels weakened the role of D-dimer in the prediction of thrombosis.The abnormal changes of D-dimer and inflammatory factors suggest that aggressive anticoagulant therapy might be needed.

A longitudinal study of hospital workers' mental health from fall 2020 to the end of the COVID-19 pandemic in 2023.

Most longitudinal studies of healthcare workers' mental health during COVID-19 end in 2021. We examined trends in hospital workers eight times, ending in 2023. A cohort of healthcare workers at one organization was surveyed at 3-month intervals until Spring 2022 and re-surveyed in Spring 2023 using validated measures of common mental health problems. Of 538 workers in the original cohort, 289 (54%) completed the eighth survey. Repeated-measures ANOVA revealed significant changes in psychological distress (F = 7.4, P < .001), posttraumatic symptoms (F = 14.1, P < .001), and three dimensions of burnout: emotional exhaustion (F = 5.7, P < .001), depersonalization (F = 2.7, P = .01), and personal accomplishment (F = 2.8, P = .008). Over time, psychological distress and depersonalization increased, posttraumatic symptoms and personal accomplishment decreased, and emotional exhaustion fluctuated significantly without net change. Most measures did not improve significantly in the year prior to the declaration of the pandemic's end. The lack of improvement in psychological distress, emotional exhaustion, depersonalization, and personal accomplishment during the period in which COVID-19 case rates declined and public health measures were relaxed is a concerning indication of the chronicity of the impact of the pandemic on healthcare workers.