Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Association between COVID-19 and the development of chronic kidney disease in patients without initial acute kidney injury

While the association between COVID-19 and acute kidney injury (AKI) is well documented, the impact of COVID-19 on the development of advanced chronic kidney disease (CKD) remains unclear, particularly in patients without initial AKI. Using the TriNetX healthcare database, we conducted a matched cohort study comparing 141,587 COVID-19 and 141,587 influenza patients. We excluded patients with AKI within one month of infection and matched groups on demographics, comorbidities, and baseline laboratory values. The primary outcome was the incidence of advanced CKD (stages 3-5) at the 12-month follow-up. COVID-19 patients showed higher 12-month risks of advanced CKD (hazard ratio [HR]:2.02, 95% confidence interval [CI]:1.69-2.42, p < 0.0001), AKI (HR 3.04, 95%CI:2.61-3.55, p < 0.0001), and estimated glomerular filtration rate < 60 mL/min/1.73 m2 (HR:3.01, 95%CI:2.74-3.30, p < 0.0001) compared to influenza patients. Subgroup analyses showed consistently elevated risks across sexes and in patients over 45 years, while younger patients did not demonstrate an increased risk of advanced CKD at the 12-month follow-up. Diabetes mellitus and hypertension have emerged as the strongest predictors of advanced CKD development. In conclusion, COVID-19 is associated with an increased risk of long-term renal dysfunction compared with influenza, suggesting the need for extended monitoring of kidney function in high-risk populations.

Trends of respiratory viruses and factors associated with severe acute respiratory infection in patients presenting at a university hospital: a 6-year retrospective study across the COVID-19 pandemic

Background

The COVID-19 pandemic significantly disrupted the epidemiology of respiratory viruses, altering seasonal patterns and reducing circulation. While recovery trends have been observed, factors associated with severe acute respiratory infections (SARIs) during pre- and post-pandemic periods remain underexplored in middle-income countries.

Objective

This study aimed to analyze the trends in respiratory virus circulation and identify factors associated with SARI in patients attending a tertiary care university hospital in western Mexico over a six-year period spanning the pre-pandemic, pandemic, and post-pandemic phases.

Methods

A retrospective study was conducted using data from 19,088 symptomatic patients tested for respiratory viruses between 2018 and 2024. Viral trends were analyzed through interrupted time series (ITS) modeling, incorporating locally estimated scatterplot smoothing (LOESS) and raw positivity rates. Additionally, ITS analysis was performed to evaluate temporal changes in SARI proportions across different phases of the pandemic. Multivariate logistic regression models were applied to determine independent risk factors for SARI across different time periods.

Results

During the pandemic (2020-2021), respiratory virus positivity rates significantly declined, particularly for influenza, which experienced a sharp reduction but rebounded post-2022. Respiratory syncytial virus (RSV) demonstrated a delayed resurgence, whereas other respiratory viruses exhibited heterogeneous rebound patterns. ITS modeling of SARI proportions revealed a significant pre-pandemic increasing trend, followed by a slower rise during the pandemic, and a sharp post-pandemic drop in early 2022, before resuming an upward trajectory. Among older adults (>65 years), a marked increase in SARI was observed at the beginning of the pandemic, while younger groups showed more stable patterns. Logistic regression identified advanced age, male sex, cardiovascular disease, obesity, and immunosuppression as major risk factors for SARI, while vaccination consistently showed a protective effect across all periods and subgroups.

Conclusion

The COVID-19 pandemic induced persistent shifts in respiratory virus circulation, disrupting seasonal dynamics and modifying the burden of SARI. The findings underscore the importance of continuous surveillance, targeted vaccination programs, and early diagnostics to mitigate severe outcomes. These results highlight the need for adaptive public health strategies in middle-income countries to address evolving respiratory disease threats.

Correlation between peripheral lymphocyte subsets monitoring and COVID-19 pneumonia in kidney transplant recipients

OBJECTIVES

In kidney transplant recipients (KTRs), immune monitoring of peripheral lymphocyte subsets (PLS) reflects the real immune status and aids in the diagnosis of the occurrence and development of infectious diseases, including COVID-19. Exploring the PLS of COVID-19 pneumonia in KTRs is important.

METHODS

In this study, a total of 103 KTRs were divided into mild pneumonia (MP) and severe pneumonia (SP) groups, as well as a stable group. The clinical information and PLS data were assessed via t or Mann-Whitney test and receiver operating curve analysis. Logistic regression was employed to identify the risk factors, and Spearman's correlation analysis was used to identify correlations.

RESULTS

Lymphopenia is a common manifestation of COVID-19 in KTRs, and it is positively related to the severity of COVID-19 pneumonia. The CD3 + T-cell count had the highest AUC between the MP and the SP. Multiple PLS measures were found to be independent risk factors for COVID-19 pneumonia progression in KTRs.

CONCLUSIONS

This study revealed a robust correlation between PLS and severe COVID-19 pneumonia progression in KTRs. PLS monitoring could facilitate real-time diagnosis and therapy for infection, as well as timely and precisive adjustment of immunosuppression instructions, for KTRs with COVID-19.

Evaluation of limiting PEEP effectiveness in preventing barotrauma in critically ill COVID-19 patients: A retrospective study

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 can cause acute respiratory distress syndrome, requiring prolonged invasive mechanical ventilation. However, patients with coronavirus disease 2019 (COVID-19) undergoing invasive mechanical ventilation experience barotrauma. We assessed whether limiting the maximum positive end-expiratory pressure (PEEP) may prevent barotrauma more effectively than using PEEP/fraction of inspired oxygen (FiO2) in patients with COVID-19 undergoing invasive mechanical ventilation.

MATERIALS AND METHODS

We retrospectively included patients who met the diagnostic criteria at our center; they were divided into an ordinary PEEP group (PEEP/higher FiO2 table) and a limited PEEP group (maximum PEEP of <10 cmH2O) during intensive care unit admission. We evaluated the maximum ventilator variables for mechanical ventilation and limited PEEP to inhibit barotrauma as the primary outcome.

RESULTS

Patients in the ordinary PEEP group (n = 34) were significantly older and had higher body mass indexes than those in the limited PEEP group (n = 27). The maximum PEEP and maximum peak inspiratory pressure were significantly higher in the ordinary PEEP group than in the limited PEEP group. The ordinary PEEP group had a significantly higher incidence of barotrauma than the limited PEEP group.

CONCLUSIONS

Limiting the maximum PEEP to <10 cmH2O may prevent barotrauma in patients with COVID-19 undergoing invasive mechanical ventilation.

Myocarditis and Inflammatory Cardiomyopathy in Dilated Heart Failure

Inflammatory cardiomyopathy is a condition that is characterised by the presence of inflammatory cells in the myocardium, which can lead to a significant deterioration in cardiac function. The etiology of this condition involves multiple factors, both infectious and non-infectious causes. While it is primarily associated with viral infections, other potential causes include bacterial, protozoal, or fungal infections, as well as a wide variety of toxic substances and drugs, and systemic immune-mediated pathological conditions. In spite of comprehensive investigation, the presence of inflammatory cardiomyopathy accompanied by left ventricular dysfunction, heart failure or arrhythmia is indicative of an unfavourable outcome. The reasons for the occurrence of either favourable outcomes, characterised by the absence of residual myocardial injury, or unfavourable outcomes, marked by the development of dilated cardiomyopathy, in patients afflicted by the condition remain to be elucidated. The relative contributions of pathogenic agents, genomic profiles of the host, and environmental factors in disease progression and resolution remain subjects of ongoing discourse. This includes the determination of which viruses function as active inducers and which merely play a bystander role. It remains unknown which changes in the host immune profile are critical in determining the outcome of myocarditis caused by various viruses, including coxsackievirus B3 (CVB3), adenoviruses, parvoviruses B19 and SARS-CoV-2. The objective of this review is unambiguous: to provide a concise summary and comprehensive assessment of the extant evidence on the pathogenesis, diagnosis and treatment of myocarditis and inflammatory cardiomyopathy. Its focus is exclusively on virus-induced and virus-associated myocarditis. In addition, the extant lacunae of knowledge in this field are identified and the extant experimental models are evaluated, with the aim of proposing future directions for the research domain. This includes differential gene expression that regulates iron and lipid and metabolic remodelling. Furthermore, the current state of knowledge regarding the cardiovascular implications of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is also discussed, along with the open questions that remain to be addressed.

Decoding prognostic factors in SARS-CoV-2 complications among patients with hematological disorders

Within the intricate tapestry of the global SARS-CoV-2 pandemic, this study delves into the intricate interplay of clinical data to elucidate prognostic factors associated with complications in patients concomitantly afflicted with hematological disorders and SARS-CoV-2. An exhaustive analysis of 71 individuals, spanning the period from November 2022 to March 2023, aims to unveil distinctive clinical characteristics and explicate the nuanced determinants steering the trajectory of the disease. The updated findings reveal a multi-faceted correlation, underscoring the complex interplay of clinical parameters. Among individuals with hematological disorders, anomalously elevated ferritin levels are closely associated with the development of SARS-CoV-2 pneumonia, while interferon-γ is intricately linked to the severity of SARS-CoV-2. Conversely, elevated ferritin levels, increased D-dimer and fibrin degradation products, along with significantly elevated iron levels, manifest a significant association with patient mortality. Intriguingly, those in patients in complete hematologic remission confront an augmented risk of developing SARS-CoV-2 pneumonia, while those abstaining from anti-tumor treatments exhibit mitigated case severity. This study unveils the intricate interplay of clinical factors impacting the prognosis of SARS-CoV-2 complications in individuals with hematological disorders. The cognizance of aberrant interferon-γ activation and nuanced associations with ferritin, iron levels, and coagulation markers contributes to a more holistic comprehension of the prognostic landscape.

The extent of carbapenem-resistant encoding genes in Klebsiella pneumoniae from COVID-19 and non-COVID-19 patients in a tertiary care center, Saudi Arabia

Rapid dissemination of Klebsiella pneumoniae carbapenemase (KPC) is a leading cause of treatment failure, significantly increasing morbidity and mortality rates among inpatients, particularly in the intensive care unit (ICU). This study aimed to detect the occurrence of carbapenemase- and carbapenem-resistant-encoding genes in K. pneumoniae isolates from COVID-19 positive and negative patients, and to assess their impact on patient outcomes. A prospective analysis was conducted at a tertiary care hospital in Saudi Arabia, collecting 97 carbapenem-resistant K. pneumoniae (CRKP) isolates from patients with COVID-19 during 2020-2021. Isolates were obtained from various clinical specimens. Antimicrobial susceptibility assays were performed using the Automated Vitek-2 system, and data were analyzed using IBM SPSS Statistics. The predominant carbapenemases identified were Oxacillinase-48 (OXA-48), followed by KPC and New Delhi metallo-β-lactamase (NDM), with Imipenemase (IMP) and Verona integron-encoded metallo-β-lactamase (VIM) being the least prevalent. COVID-19 did not significantly affect the distribution of these genes (P>0.05); however, COVID-19 status and age over 60 years significantly impacted the outcomes of CRKP patients. Other factors such as gender, total ICU or ward stay, and comorbidities did not significantly affect CRKP infection outcomes. The most common carbapenem-resistant genes identified were blaKPC, blaNDM, and blaOXA-48; however, they were not significantly associated with increased mortality.

Clinical Course and Mortality Predictors in Adult Hospitalized Patients with COVID-19 Infection-A Retrospective Cohort Study

Background and Objectives: Bulgaria had the highest mortality rate of COVID-19 in Europe and the second highest in the world based on statistical data. This study aimed to determine the mortality predictors in 306 adult patients with COVID-19 infection, treated at the COVID-19 Ward of St. George University Hospital in Plovdiv, Bulgaria in the period of August 2021-April 2022. Materials and Methods: All admitted and treated patients had a positive PCR test for SARS-CoV-2. They were assigned in three groups based on the severity rating scale published in NIH COVID-19 Treatment Guidelines by Stat Pearls Publishing, 2022. Demographic, clinical, and laboratory parameters and pre-existing comorbidities were investigated. Parametric and non-parametric methods were used for statistics. Logistic regression was applied for parameters significantly associated with mortality. Results: Data showed that demographic indicators were not significantly associated with poorer outcome. Among comorbidities, cardiovascular, chronic pulmonary and endocrine disorders were found to be related to poor survival rates (p = 0.003, p = 0.003 and p = 0.017 resp.) Clinical symptoms, such as sore throat, dry or productive cough and breathlessness, were determinants of poor outcome (p = 0.027, p = 0.029, p = 0.004 and p = 0.002 resp.). Laboratory parameters linked to mortality were elevated d-dimers (p = 0.015), ferritin (p = 0.009) and creatinine (p = 0.038). p02 < 50 and saturation < 90 also indicated a higher risk of death (p = 0.006 and p = 0021). Conclusions: Logistic regression showed that each stage of disease severity increased the risk of death 3.6 times, chronic pulmonary disorders increased it by 4.1, endocrine by 2.4 and dyspnea by 3.1 times.

Investigating the relationship between cycle threshold of SARS-CoV-2 RT-PCR, clinical features, and laboratory data in hospitalized COVID-19 patients in Semnan, Iran

Introduction

COVID-19, caused by the SARS-CoV-2 virus, has emerged as a global public health crisis. Understanding the factors associated with disease severity and outcomes is crucial for effective patient management. This study aimed to investigate the association between cycle threshold (CT) values, demographic data, medical history, clinical manifestations, and laboratory findings in hospitalized COVID-19 patients in Semnan, Iran.

Methods

A cross-sectional study was conducted on 86 patients with confirmed COVID-19 admitted to two hospitals in Semnan, Iran, between December 2022 and March 2023. Respiratory swab samples were collected RT-PCR was performed, CT values were obtained, and data were collected from medical records, including demographic information, medical history, clinical manifestations, and laboratory results. Statistical analysis was performed using SPSS software.

Results

The study included 86 COVID-19 patients, with a slightly higher representation of females (55.8%) and a mean age of 67.43 years. Pre-existing conditions like hypertension, diabetes mellitus, and ischemic heart disease were prevalent among hospitalized patients. A majority of patients (59.3%) had severe COVID-19, as indicated by lower CT values, while 31.4% exhibited oxygen saturation levels below 90%. Significant differences were observed in FBS, CRP, WBC, Hb, Cr, and SPo2 levels between severe and non-severe patients. Correlation analysis revealed associations between age, CRP, Cr, BUN, FBS, Vitamin D, TG, LDL, HDL, AST, ALP, and SPo2. Reflecting complex interactions between inflammatory markers, organ function, and lipid metabolism in COVID-19 patients.

Conclusion

This study provides valuable insights into the association between CT values, clinical characteristics, and laboratory findings in hospitalized COVID-19 patients. The findings underscore the importance of CT values in assessing disease severity and potential prognostication. Further research is warranted to validate these findings in larger and more diverse patient populations.

Differences in Characteristics, Treatments, and Mortality of Patients with COVID-19 Between 2022 and 2020-2021

In 2021, vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were developed and the Omicron variant emerged. This study compared the characteristics, treatments, and mortality of patients with coronavirus disease 2019 (COVID-19) between 2022 and 2020-2021, using administrative claims data linked including vaccine records in a Japanese city. Patients who underwent COVID-19 antigen or polymerase chain reaction tests and were diagnosed with COVID-19 were identified. Patient characteristics, treatments, and mortality were compared between 2022 and 2020-2021 among those diagnosed with COVID-19. We identified 26,262 patients with COVID-19. The mortality in 2022 was lower than that in 2020-2021 (0.6% vs. 1.7%; P < 0.01). Patients in 2022 were significantly less likely to receive oxygen therapy, high-flow nasal oxygenation, mechanical ventilation, steroids, and tocilizumab than those in 2020-2021. Among the deceased, the proportion of those aged ≥65 years was significantly higher in 2022 than in 2020-2021 (98.4% vs. 88.6%). The logistic regression analysis indicated, older age, male sex, and ≥3 comorbidities were associated with higher mortality, whereas ≥3 vaccinations were associated with lower mortality. Patients with COVID-19 in 2022 were less likely to require respiratory care or succumb to the disease. Older patients were more likely to die in 2022 than in 2020-2021.

Exploring Coronavirus Disease 2019 Risk Factors: A Text Network Analysis Approach

Background/Objectives: The coronavirus disease 2019 (COVID-19) pandemic has significantly affected global health, economies, and societies, necessitating a deeper understanding of the factors influencing its spread and severity. Methods: This study employed text network analysis to examine relationships among various risk factors associated with severe COVID-19. Analyzing a dataset of published studies from January 2020 to December 2021, this study identifies key determinants, including age, hypertension, and pre-existing health conditions, while uncovering their interconnections. Results: The analysis reveals five thematic clusters: biomedical, occupational, demographic, behavioral, and complication-related factors. Temporal trend analysis reveals distinct shifts in research focus over time. In early 2020, studies primarily addressed immediate clinical characteristics and acute complications of COVID-19. By mid-2021, research increasingly emphasized long COVID, highlighting its prolonged symptoms and impact on quality of life. Concurrently, vaccine efficacy became a dominant topic, with studies assessing protection rates against emerging viral variants, such as Alpha, Delta, and Omicron. This evolving landscape underscores the dynamic nature of COVID-19 research and the adaptation of public health strategies accordingly. Conclusions: These findings offer valuable insights for targeted public health interventions, emphasizing the need for tailored strategies to mitigate severe outcomes in high-risk groups. This study demonstrates the potential of text network analysis as a robust tool for synthesizing complex datasets and informing evidence-based decision-making in pandemic preparedness and response.

Dynamic biomarkers and Cox regression with time-dependent covariate for mortality prediction in severe fever with thrombocytopenia syndrome

Severe fever with thrombocytopenia syndrome (SFTS) is a fatal tick-borne infectious disease that lacks effective treatments. Dynamic analysis that reflects changes in the SFTS patient's condition is needed. This study aimed to evaluate the time-dependent predictive performance of key biomarkers using a time-dependent Cox regression model. A retrospective multicenter cohort study was conducted on 440 SFTS patients hospitalized in South Korea between 2013 and 2024. Time-dependent Cox regression and time-dependent receiver operating characteristic (ROC) analyses were applied to assess the prognostic value of Blood Urea Nitrogen (BUN), Prothrombin Time (PT), and Activated Partial Thromboplastin Time (aPTT). Missing data were handled using multiple imputation. aPTT consistently demonstrated high predictive accuracy (AUC > 0.90) throughout the disease course, indicating its sustained role in coagulopathy. PT exhibited strong early-stage predictive power (AUC = 0.86 on day 2) but declined over time, reflecting its utility for early monitoring. BUN showed a progressive increase in predictive performance (AUC = 0.70 on day 2 to AUC = 0.78 on day 8), supporting its relevance in later stages of disease progression. Non-survivors exhibited significantly higher levels of BUN, PT, and aPTT compared to survivors. This study demonstrates the utility of time-dependent analysis for evaluating dynamic biomarker changes in SFTS patients. aPTT is a robust predictor throughout the disease course, while PT is valuable for early-stage assessment and BUN for later-stage management. These findings suggest the importance of integrating dynamic biomarker monitoring into clinical decision-making to improve prognosis in SFTS patients.

Risk Factors Affecting the Severity, Mortality, and Intensive Care Unit Admission of COVID-19 Patients: A Series of 1075 Cases

BACKGROUND

The clinical spectrum of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is broad; it can range from asymptomatic cases to mild upper respiratory tract illness, respiratory failure, and severe multiorgan failure resulting in death. Therefore, it is important to identify the clinical course of the disease and the factors associated with mortality.

OBJECTIVE

The aim of this study is to identify the risk factors associated with the severity of the disease, intensive care unit admission, and mortality in COVID-19 patients.

METHODS

A total of 1075 patients with clinical and radiological findings compatible with COVID-19 pneumonia and positive SARS-CoV-2 PCR were selected and retrospectively screened. All included patients were classified according to the 7th edition of the 2019 Coronavirus Disease Guidelines published by the National Health Commission of China.

RESULTS

It was observed that elevated white blood count (WBC) increased the severity of COVID-19 by 3.26 times and the risk of intensive care unit (ICU) admission by 3.47 times. Patients with high D-dimer levels had a 91% increased risk, and those with high fibrinogen levels had a 2.08 times higher risk of severe disease. High C-reactive protein (CRP) values were found to increase disease severity by 6.89 times, mortality by 12.84 times, and ICU admission by 3.37 times.

CONCLUSIONS

Identifying the factors associated with disease severity, ICU admission, and mortality in COVID-19 patients could help reduce disability and mortality rates in pandemics.

Immuno-μSARS2 Chip: A Peptide-Based Microarray to Assess COVID-19 Prognosis Based on Immunological Fingerprints

A multiplexed microarray chip (Immuno-μSARS2) aiming at providing information on the prognosis of the COVID-19 has been developed. The diagnostic technology records information related to the profile of the immunological response of patients infected by the SARS-CoV-2 virus. The diagnostic technology delivers information on the avidity of the sera against 28 different peptide epitopes and 7 proteins printed on a 25 mm2 area of a glass slide. The peptide epitopes (12-15 mer) derived from structural proteins (Spike and Nucleocapsid) have been rationally designed, synthesized, and used to develop Immuno-μSARS2 as a multiplexed and high-throughput fluorescent microarray platform. The analysis of 755 human serum samples (321 from PCR+ patients; 288 from PCR- patients; 115 from prepandemic individuals and classified as hospitalized, admitted to intensive-care unit (ICU), and exitus) from three independent cohorts has shown that the chips perform with a 98% specificity and 91% sensitivity identifying RT-PCR+ patients. Computational analysis utilized to correlate the immunological signatures of the samples analyzed indicate significant prediction rates against exitus conditions with 82% accuracy, ICU admissions with 80% accuracy, and 73% accuracy over hospitalization requirement compared to asymptomatic patients' fingerprints. The miniaturized microarray chip allows simultaneous determination of 96 samples (24 samples/slide) in 90 min and requires only 10 μL of sera. The diagnostic approach presented for the first time here could have a great value in assisting clinicians in decision-making based on the information provided by the Immuno-μSARS2 regarding progression of the disease and could be easily implemented in diagnostics of other infectious diseases.

Combination of fibrosis-4 score and D-dimer: a practical approach to identify poor outcome in COVID-19

AIM

Fibrosis-4 (FIB-4) score and D-dimer (DD) have emerged as prognostic markers in coronavirus disease 2019 (COVID-19). However, precise cutoff points remain undefined, and their combined use has been scarcely studied. We aimed to analyze FIB-4 and DD performance, individually and combined, to predict outcomes among COVID-19 patients.

METHODS

From March to December 2020, hospitalized COVID-19 patients were evaluated based on clinical and laboratory tests from their first day of hospitalization. Primary outcome was inhospital mortality, and secondary outcomes included hospital stay length, ICU admission and duration, need for hemodialysis, ventilatory support, and extent of lung involvement. Optimal FIB-4 and DD cutoff points to predict mortality were established to maximize sensitivity and specificity. A sequential diagnostic strategy using both markers was subsequently evaluated.

RESULTS

Among 518 patients (61 ± 16 years, 64% men), the inhospital mortality rate was 18%. FIB-4 outperformed DD in predicting mortality (area under the receiver operating characteristic curve: 0.76 vs. 0.65, P = 0.003) and was chosen as the first step in sequential analysis. Mortality was higher in patients with FIB-4 ≥1.76 vs. FIB-4 <1.76 (26 vs. 5%, P < 0.001) and DD ≥2000 ng/ml vs. DD <2000 ng/ml (38 vs. 16%, P < 0.001). Using FIB-4 as a screening test (cutoff = 1.76, 90% sensitivity) followed by DD (cutoff = 2000 ng/ml; 90% specificity) identified a subgroup with higher mortality when compared with FIB-4 alone (48 vs. 26%, P < 0.001), missing the identification of only 2% of deaths.

CONCLUSION

Sequential use of FIB-4 and DD represents a comprehensive strategy to identify high-risk COVID-19 patients at hospital admission, potentially minimizing unnecessary DD tests in those deemed low-risk by FIB-4.

Biomarkers for Early Predicting In-Hospital Mortality in Severe Fever with Thrombocytopenia Syndrome and Differentiating It from Hemorrhagic Fever with Renal Syndrome

Purpose

Severe fever with thrombocytopenia syndrome (SFTS) has a high mortality rate and is easily misdiagnosed as hemorrhagic fever with renal syndrome (HFRS), particularly in resource-limited rural areas where early diagnosis remains challenging. This study used routine laboratory parameters, epidemiology and clinical manifestations to develop a model for the early diagnosis of SFTS and identify fatal risk factors, ultimately reducing mortality of SFTS.

Patients and Methods

This retrospective cohort study included 141 SFTS and 141 HFRS patients. Of these, 94 patients with SFTS were allocated to the model cohort for mortality risk identification by using multivariable Cox regression analysis. Sensitivity, specificity, and predictive values were calculated from validation cohort to assess the clinical values. Then, we analyzed 62 SFTS and 113 HFRS using multivariable logistic regression to identify SFTS. Receiver operating characteristic (ROC) curve analysis was used to evaluate their diagnostic value.

Results

Multivariate Cox regression analysis showed that blood urea nitrogen (BUN) ≥10.22mmol/L activated partial thromboplastin time (APTT) ≥58.05s and D-dimer ≥4.68mg/L were the risk factors for death in SFTS. This combined indicators had an area under the curve (AUC) of 0.91 (95% CI: 0.847-0.973), with a sensitivity and specificity of 86%, respectively. Any indicator was achieved the cutoff, and sensitivity and specificity in the validation group were 93% and 54%. Multivariable logistic regression showed that age (OR: 1.10) and initial laboratory indicators including WBC (OR: 0.48), Cr (OR: 0.86), CK (OR: 1.01), and APTT (OR: 1.09) can be used to identify SFTS from HFRS. This model achieved an AUC value of 0.97 (95% CI: 0.977-0.999) and 0.98 (95% CI: 0.958-1.000) in validation cohort.

Conclusion

In resource-limited rural hospitals, the integration of routine laboratory parameters with epidemiology and clinical manifestations demonstrates enhanced sensitivity for early SFTS identification and mortality risk stratification to reduce mortality rate.

Delayed viral clearance and altered inflammatory responses affect severity of SARS-CoV-2 infection in aged mice

Epidemiological investigations consistently demonstrate an overrepresentation of the elderly in COVID-19 hospitalizations and fatalities, making the advanced age as a major predictor of disease severity. Despite this, a comprehensive understanding of the cellular and molecular mechanisms explaining how old age represents a major risk factor remain elusive. To investigate this, we compared SARS-CoV-2 infection outcomes in young adults (2 months) and geriatric (15-22 months) mice. Both groups of K18-ACE2 mice were intranasally infected with 500 TCID50 of SARS-CoV-2 Delta variant with analyses performed on days 3, 5, and 7 post-infection (DPI). Analyses included pulmonary cytokines, lung RNA-seq, viral loads, lipidomic profiles, and histological assessments, with a concurrent evaluation of the percentage of mice reaching humane endpoints. The findings unveiled notable differences, with aged mice exhibiting impaired viral clearance, reduced survival, and failure to recover weight loss due to infection. RNA-seq data suggested greater lung damage and reduced respiratory function in infected aged mice. Additionally, elderly-infected mice exhibited a deficient antiviral response characterized by reduced Th1-associated mediators (IFNγ, CCL2, CCL3, CXCL9) and diminished number of macrophages, NK cells, and T cells. Furthermore, mass-spectrometry analysis of the lung lipidome indicated altered expression of several lipids with immunomodulatory and pro-resolution effects in aged mice such as Resolvin, HOTrEs, and NeuroP, but also DiHOMEs-related ARDS. These findings indicate that aging affects antiviral immunity, leading to prolonged infection, greater lung damage, and poorer clinical outcomes. This underscores the potential efficacy of immunomodulatory treatments for elderly subjects experiencing symptoms of severe COVID-19.

Outcomes of COVID-19 During the First Wave in Saudi Arabia: An Observational Study of ICU Cases from a Single Hospital

Background/Objectives: Mortality from COVID-19 in intensive care units (ICUs) was not clearly reported in many regions during the first wave. We aimed to assess the characteristics and outcomes of ICU patients with COVID-19 in Saudi Arabia. Methods: This was a secondary data analysis of the Convalescent Plasma Trial. All patients who were recruited from King Fahad Hospital of the University (KFHU) in the Eastern Region of Saudi Arabia between 13 March 2020 and 13 September 2020 were included. Characteristics and outcomes, differences in characteristics and outcomes between Saudi and non-Saudi populations, and predictors of mortality were assessed. Results: The KFHU recruited 185 ICU patients with COVID-19. Of those, 90 (48.6%) were Saudi, and 95 (51.4%) were non-Saudi. The overall mean age was 56.7 years, and 71.9% were males. Compared with Saudis, non-Saudis were younger, with a mean age of 54.4 years, were more likely to be males (81.1%), and had a higher median respiratory rate (28.0 breaths/min vs. 24.0), a lower percentage of blood-oxygen saturation (86.0% vs. 91.0%), and higher median levels of ferritin per µg/L (820 vs. 550). The overall mortality rate was 33.0% (n = 61). The mortality rate in non-Saudis (42.1%) was higher than that in Saudis (23.3%). The variables associated with increased mortality included non-Saudi status (odds ratio [OR] 2.66; 95% CI: 1.05, 6.72), ferritin (OR 1.01; 95% CI: 1.00, 1.02), and intubation (OR 8.55; 95% CI: 2.92, 24.97). Conclusions: Since the mortality rate in non-Saudis was greater than that in Saudis, more efforts should be made to improve social determinants of health across non-Saudis in our region.

Independent and combined effects of long-term air pollution exposure and genetic predisposition on COVID-19 severity: A population-based cohort study

The relationships between air pollution, genetic susceptibility, and COVID-19-related outcomes, as well as the potential interplays between air pollution and genetic susceptibility, remain largely unexplored. The Cox proportional hazards model was used to assess associations between long-term exposure to air pollutants and the risk of COVID-19 outcomes (infection, hospitalization, and death) in a COVID-19-naive cohort (n = 458,396). Additionally, associations between air pollutants and the risk of COVID-19 severity (hospitalization and death) were evaluated in a COVID-19 infection cohort (n = 110,216). Furthermore, this study investigated the role of host genetic susceptibility in the relationships between exposure to air pollutants and the development of COVID-19-related outcomes. Long-term exposure to air pollutants was significantly associated with an increased risk of COVID-19-related outcomes in the COVID-19 naive cohort. Similarly, in COVID-19 infection cohort, hazard ratios (HRs) for COVID-19 hospital admission were 1.23 (1.19, 1.27) for PM2.5 and 1.22 (1.17, 1.26) for PM10, whereas HRs for COVID-19 death were 1.28 (1.18, 1.39) for PM2.5 and 1.25 (1.16, 1.36) for PM10. Notably, significant interactions were found between PM2.5/PM10 and genetic susceptibility in COVID-19 death. In COVID-19 infection cohort, participants with both high genetic risk and high air pollutants exposure had 1.86- to 1.97-fold and 1.91- to 2.14-fold higher risk of COVID-19 hospitalization and death compared to those with both low genetic risk and low air pollutants exposure. Exposure to air pollution is significantly associated with an increased burden of severe COVID-19, and air pollution-gene interactions may play a crucial role in the development of COVID-19-related outcomes.

Comprehensive Analysis of Potential Common Pathogenic Mechanisms for COVID-19 Infection and Gastric Cancer

A growing body of data suggests that the prevalence of COVID-19 pneumonia in patients with stomach cancer is much higher than in the general population. However, these mechanisms are still not fully understood. After a thorough examination of shared differentially expressed genes (DEGs) for gastric cancer (GC) and COVID-19 pneumonia, we performed functional annotation, protein-protein interaction (PPI) networks, module design, and pivot gene identification. qPCR was used to verify the expression of hub genes in GC. Finally, a pivotal gene transcription factor-gene regulatory network was created and validated. According to functional enrichment analysis, common genes are mainly enriched in biological processes such as extracellular matrix tissue and extracellular structural tissue. Finally, five genes were found to be pivotal genes in the pathogenesis of GC and COVID-19 pneumonia: BGN (biglycan), UBE2C (ubiquitin-conjugating enzymes 2C), SPP1 (secreted phosphoprotein 1), THBS2 (thrombospondin 2), and COL1A1 (type I collagen alpha 1). These shared pathways and pivotal genes could provide new insights for more mechanistic studies.

The Current Status, Hotspots, and Development Trends of Nanoemulsions: A Comprehensive Bibliometric Review

Nanoemulsions, which are characterized by their nanometer-scale droplets, have gained significant attention in different fields, such as medicine, food, cosmetics, and agriculture, because of their unique properties. With an increasing number of countries engaging in research on nanoemulsions, interest in their properties, preparation methods, and applications has increased. Hence, tracing the relevant research on nanoemulsions published in the past ten years on a global scale, by conducting data mining and visualization analysis on a sufficiently large text dataset through bibliometrics, sorting out and summarizing certain indicators, the development history, research status and research hotspots in the field of nanoemulsions can be clearly revealed, providing reference value and significance for subsequent research. This bibliometric review examines the research landscape of nanoemulsions from 2013-2023 via the SCI-E and SSCI databases, providing insights into the current status, hotspots, and future trends of this field. To offer a comprehensive overview, this analysis includes publication counts, author keywords, institutional contributions, research areas, prolific authors, highly cited papers and hot research papers. The findings reveal that China led in nanoemulsions research, followed by USA, India, and Brazil, with the University of Massachusetts emerging as a key player with the highest average number of citations per article (ACPP) and h-index. Food Chemistry, Pharmaceutics, and the Journal of Drug Delivery Science and Technology are among the top journals publishing in this area. Chemistry, pharmacology, and pharmacy emerged as the primary research domains, with McClements DJ as the most prolific and influential author. In keyword analysis, essential oil nanoemulsions are currently the main preparation direction, and various characteristics of nanoemulsions, such as their bioavailability, stability, biocompatibility, and antioxidant and antibacterial properties, have also been studied extensively. Research hotspots are focused mostly on the development of new applications and technologies for nanoemulsions.

Comparative Analysis of Neuropsychiatric Adverse Reactions Associated with Remdesivir and Nirmatrelvir/Ritonavir in COVID-19 Treatment: Insights from EudraVigilance Data

Remdesivir (RDV) and nirmatrelvir/ritonavir (NMVr) are among the most widely used antivirals in the treatment of COVID-19, aiming to reduce disease severity and progression. Adverse neuropsychiatric effects, such as anxiety, sleep disturbances, and movement disorders, have emerged as significant concerns associated with these treatments. To better understand the safety profiles of RDV and NMVr, this study performs a pharmacovigilance analysis of individual case safety reports (ICSRs) from the EudraVigilance (EV) database. Objectives: This study evaluates the risk of neuropsychiatric adverse events associated with RDV and NMVr. Comparisons with other antiviral drugs, including darunavir, sofosbuvir, ribavirin, tenofovir, ritonavir, and sotrovimab, are also performed to develop a comprehensive understanding of the safety profiles. Methods: A retrospective analysis of ICSRs submitted to EV until 7 July 2024, with data extraction on 12 July 2024, was conducted. Demographic characteristics (age, sex, geographic region, and reporter type) and case severity were included in the descriptive analysis. Disproportionality analysis using reporting odds ratio (ROR) and 95% confidence intervals (CI) was performed to compare adverse drug reaction (ADRs) frequencies across 27 system organ classes (SOCs), with emphasis on "Nervous system disorders" and "Psychiatric disorders. Results: The total number of ICSRs was significantly higher for NMVr (n = 8078) compared to RDV (n = 3934). Nervous system disorders accounted for 3.07% of the total RDV reports and for 17.31% of NMVr reports, while psychiatric disorders represented 0.92% of the total ADRs reported for RDV (n = 60) and 3.61% for NMVr (n = 672). On the other hand, RDV showed a significantly lower frequency of reporting headache compared to NMVr (ROR: 0.1057; 95% CI: 0.0676-0.1653). Conclusions: NMVr presents a higher risk of neuropsychiatric ADRs than RDV, underscoring the need for enhanced monitoring, particularly in patients with preexisting central nervous system (CNS) conditions. These findings contribute to optimizing antiviral safety and informing clinical decision making.

Geographic inequalities and factors associated with unfavorable outcomes in diabetes-tuberculosis and diabetes-covid comorbidities in Brazil

The rapid spread of COVID-19 have overwhelmed health systems, especially in the care of chronic disease such as tuberculosis and diabetes. The objective of the study was to analyze the magnitude and relevance of tuberculosis-diabetes and diabetes-COVID-19 comorbidities in spatial risk areas and their factors associated with unfavorable outcomes in the Brazilian population between 2020 and 2022. An ecological study was carried out in Brazilian municipalities. The population was composed by cases of tuberculosis-diabetes and diabetes-COVID-19 comorbidities, registered in the Influenza Epidemiological Surveillance Information System (SIVEP-GRIPE) and in DATASUS from 2020 to 2022. The Scan Statistics technique was used to identify spatial risk clusters. Binary logistic regression was then employed to understand the relationship between outcomes and comorbidities, considering clinical and sociodemographic variables. A total of 24,750 cases of tuberculosis-diabetes comorbidity were identified, which consisted of an incidence of 3.2 cases per 100,000 inhabitants. Risk clusters were identified in the Central-West and North regions. 303,210 cases of diabetes- COVID-19 comorbidity were identified, resulting in an incidence of 0.4 cases per 100,000 inhabitants. São Paulo-SP, Rio de Janeiro-RJ and Belo Horizonte-MG were the municipalities with the highest spatial risk of illness. The analysis of the spatial risk areas revealed distinct patterns in the geographic distribution of comorbidities. Based on the findings, it is concluded that comorbidities between tuberculosis and diabetes, as well as between COVID-19 and diabetes, represent significant challenges for public health in Brazil, deserving attention from health authorities and the scientific community.

Epidemiological and clinical characteristics of COVID-19 mortality: a retrospective study

Background

The global impact of SARS-CoV-2 and its associated coronavirus disease (COVID-19) has necessitated urgent characterization of prognostic biomarkers. This study aimed to delineate the epidemiological and clinical predictors of mortality among hospitalized COVID-19 patients.

Methods

A retrospective cohort study was conducted on 123 patients with laboratory-confirmed COVID-19 admitted to Huoshenshan Hospital (Wuhan, China) from 1 February 2020 to 30 April 2020. Kaplan-Meier curve and multivariate Cox regression were used to assess the independent factors with survival time. Statistical significance was set at a p-value of <0.05.

Results

The cohort exhibited a mortality rate of 49.6% (61/123), with the critical clinical type (HR = 7.970, p = 0.009), leukocytosis (HR = 3.408, p = 0.006), and lymphopenia (HR = 0.817, p = 0.038) emerging as independent predictors of reduced survival. Critical-type patients demonstrated significantly elevated inflammatory markers (neutrophils: 10.41 ± 6.23 × 109/L; CRP: 104.47 ± 29.18 mg/L) and coagulopathy (D-dimer: 5.21 ± 2.34 μg/ml) compared to non-critical cases. Deceased patients exhibited pronounced metabolic derangements, including hyperglycemia (9.81 ± 2.07 mmol/L) and hepatic dysfunction (ALP: 174.03 ± 30.13 U/L).

Conclusion

We revealed the epidemiological and clinical features of different clinical types of SARS-CoV-2 as summarized in this paper. We found that critical type, leukocyte, and lymphocyte are risk factors that affect survival time, which could be an early and helpful marker to improve management of COVID-19 patients.

Development and validation of a nomogram to assess the occurrence of liver dysfunction in patients with COVID-19 pneumonia in the ICU

The global pandemic of novel coronavirus pneumonia (COVID-19) has resulted in millions of deaths over the past three years. As one of the most commonly affected extra-pulmonary organs, numerous studies have reported varying degrees of liver injury in a significant proportion of patients with COVID-19, particularly in severe and critically ill patients. Early prediction of liver dysfunction in hospitalized patients would facilitate the clinical management of COVID-19 and improve clinical prognosis, but reliable and valid predictive models are still lacking.MethodsWe collected data from 286 patients with RT-PCR confirmed COVID-19 admitted to various ICUs from the case system. These patients were randomly divided into a training cohort (50%) and a validation cohort (50%). In the training cohort, we first used ROC curves to measure the predictive efficiency of each of the variables for the development of liver damage during hospitalization in patients with COVID-19, followed by LASSO regression analysis to screen the variables for predictive models and logistic regression analysis to identify relevant risk factors. A nomogram based on these variables was created following the above model. Finally, the efficiency of the prediction models in the training and validation cohorts was assessed using AUC, consistency index (C index), calibration curves and Decision Curve Analysis.ResultsOut of a total of 80 parameters for COVID-19 patients admitted to the ICUs, 10 were determined to be significantly associated with the occurrence of liver dysfunction during hospitalization. Based on these predictors, further prediction models were used to construct and develop a nomogram that was offered for practical clinical application. The C-index of the column line graphs for the training and validation cohorts was 0.956 and 0.844 respectively. in addition, the calibration curves for the model showed a high degree of agreement between the predicted and actual incidence of liver dysfunction in patients with COVID-19.ConclusionBy developing a predictive model and associated nomogram, we predicted the incidence of liver dysfunction during hospitalization in patients with COVID-19 in the ICU. The model's predictive performance was determined in both the training and validation cohorts, contributing to the clinical management of COVID-19.

Novel Insights into CKMB, Myoglobin, and Troponin I Levels as Predictors of COVID-19 Severity and Hospitalization Outcomes

Background: COVID-19 has largely become an endemic disease in many regions, with sporadic outbreaks, with some areas where the disease shows a seasonal pattern like the influenza virus. The focus has shifted towards managing mild and moderate forms of disease through outpatient care, aiming to prevent healthcare system overload. Consequently, identifying markers that could be used in stratifying the risk and the prognostic assessment has become crucial. Cardiovascular implications of COVID-19 are a critical area of research due to their significant impact on disease severity, mortality, and morbidity. Methods: We conducted a retrospective, observational study and included 472 patients, diagnosed with COVID-19, all of whom were admitted to Prof. Dr. Matei Bals National Institute of Infectious Disease, Bucharest, Romania. Levels of cardiac biomarkers like creatine kinase (CK), creatine kinase-myocardial band (CKMB), myoglobin, troponins, and NT-pro-BNP were measured and analyzed in relation to clinical presentation and outcomes. Results: We combined CKMB, myoglobin, and troponin I to predict hospital length of stay (LOS). Our model significantly predicted LOS (F = 12.537, p = 0.0001), with higher levels associated with prolonged stays (β = 0.166, p = 0.000). Logistic regression demonstrated that the combination of elevated CKMB and myoglobin levels significantly increased the odds of a longer LOS (OR = 1.679, p = 0.000). Furthermore, we found significant correlations with acute respiratory failure (p = 0.001), severe forms of disease (p = 0.000), and the development of complications during hospitalization (p = 0.027). Conclusions: These findings emphasize the value of combining cardiac biomarkers to stratify risk and predict hospital outcomes in COVID-19 patients. Routine cardiac monitoring and targeted management strategies could decrease the risk of complications, reducing the LOS. Our findings highlight the potential of cardiac biomarkers as prognostic tools to stratify risk, guide clinical interventions, and improve outcomes in COVID-19 patients.

Long COVID in ARDS Survivors: Insights from a Two-Year-Follow-Up Study After the First Wave of the Pandemic

Objectives: To compare the health status, exercise capacity, and health-related quality of life (HRQoL) in survivors of COVID-19-associated acute respiratory distress syndrome (ARDS) at 8, 12, and 24 months post-diagnosis. Methods: We conducted a prospective, single-center follow-up study embedded within a larger multicenter cohort of adults with COVID-19 who required hospital admission. Eligible participants underwent clinical interviews, physical examinations, chest radiography, and the 6-min walk test (6MWT). Standardized scales were used to assess post-traumatic stress disorder (PTSD), anxiety, depression, and HRQoL. Results: Out of 1295 patients with COVID-19, 365 developed ARDS, of whom 166 survived. After excluding deaths and loss to follow-up, 95 patients were monitored for 24 months. Over 60% of patients had persistent symptoms, though significant improvements were recorded in quality of life and physical recovery. More than 70% recovered their previous physical capacity, but 15% did not return to their usual lifestyle habits. Symptoms such as arthralgia and fatigue decreased, but cognitive issues, such as memory loss and insomnia, persisted. Radiological improvements were noted, although pulmonary function remained impaired. The prevalence of PTSD and anxiety decreased, while depression remained stable at around 30%. Conclusions: Long COVID continues to impose significant physical, mental, and social challenges. Symptoms like fatigue and anxiety have a profound impact on daily life. Strategies are urgently needed to help patients regain health and resume their normal lives.

Age-associated differences in mucosal and systemic host responses to SARS-CoV-2 infection

Age is among the strongest risk factors for severe outcomes from SARS-CoV-2 infection. Here we describe upper respiratory tract (URT) and peripheral blood transcriptomes of 202 participants (age range of 1 week to 83 years), including 137 non-hospitalized individuals with mild SARS-CoV-2 infection and 65 healthy individuals. Among healthy children and adolescents, younger age is associated with higher URT expression of innate and adaptive immune pathways. SARS-CoV-2 infection induces broad upregulation of URT innate and adaptive immune responses among children and adolescents. Peripheral blood responses among SARS-CoV-2-infected children and adolescents are dominated by interferon pathways, while upregulation of myeloid activation, inflammatory, and coagulation pathways is observed only in adults. Among SARS-CoV-2-infected individuals, fever is associated with blunted URT immune responses and more pronounced systemic immune activation. These findings demonstrate that immune responses to SARS-CoV-2 differ across the lifespan, from distinct signatures in childhood and adolescence to age-associated alterations in adults.

Geospatial modelling of COVID19 mortality in Oman using geographically weighted Poisson regression GWPR

The year 2020 witnessed the arrival of the global COVID-19 pandemic, which became the most devastating public health disaster in the last decade. Understanding the underlying spatial variations of the consequences of the pandemic, particularly mortality, is crucial for plans and policies. Nevertheless, few studies have been conducted on the key determinants of COVID-19 mortality and how these might vary geographically across developing nations. Therefore, this research aims to address these gaps by adopting the Geographically Weighted Poisson Regression (GWPR) model to investigate spatial heterogeneity of COVID-19 mortality in Oman. The findings indicated that local GWPR performed better than global Ordinary Least Square (OLS) model, and the relationship between risk factors and mortality cases varied geographically at a subnational scale. The local parameter estimates of the model revealed that elderly populations, respiratory diseases, and population density were significant in predicting mortality cases. The elderly population variable was the most influential regressor, followed by respiratory diseases. The formulated policy recommendations will provide decision-makers and practitioners with key factors related to pandemic mortality so that future interventions and preventive measures can mitigate high fatality risks.

Clinical Outcomes of Hospitalized Immunocompromised Patients With COVID-19 and the Impact of Hyperinflammation: A Retrospective Cohort Study

Purpose

Immunocompromised patients are at increased risk for severe outcomes from COVID-19 due to their altered immune responses, yet their inflammatory profiles and the interplay between immunosuppression remain poorly understood. We aimed to illustrate the inflammation profile and clinical outcomes of hospitalized immunocompromised patients with COVID-19.

Methods

We conducted a retrospective study using a multicenter database and included adult hospitalized patients with Corona virus disease 2019 (COVID-19) in China's late 2022 COVID-19 wave. Crude and adjusted 28- and 60-day mortality was compared between the two groups. Inflammatory phenotypes were evaluated by serum interleukin-6 (IL-6) and C-reactive protein (CRP) level. The interplay between overt inflammation and immunosuppression was analyzed.

Results

Among the 4078 included patients, 348 (8.5%) were immunocompromised. Immunocompromised patients had lower crude mortality but higher adjusted mortality at 28-day (hazard ratio [HR] = 1.55; 95% CI 1.08 to 2.23) and 60-day (HR = 1.47; 95% CI 1.05 to 2.06). Besides, immunocompromised patients had a higher risk of developing hyperinflammation (odd ratio [OR] =1.92; 95% CI 1.47 to 2.50, p <0.001). Moreover, hyperinflammation mediated a major part of the deleterious survival effect of immunosuppression on COVID-19.

Conclusion

Immunodeficiency not only increases short-term mortality risk but also predisposes patients to hyperinflammation. The complex interplay between immunosuppression, hyperinflammation, and COVID-19 outcomes warrants more detailed profiling of inflammation and immunity in this population.

COVID-19 related complications

The COVID-19 pandemic has significantly impacted global healthcare systems, revealed vulnerabilities and prompted a re-evaluation of medical practices. Acute complications from the virus, including cardiovascular and neurological issues, have underscored the necessity for timely medical interventions. Advances in diagnostic methods and personalized therapies have been pivotal in mitigating severe outcomes. Additionally, Long COVID has emerged as a complex challenge, affecting various body systems and leading to respiratory, cardiovascular, neurological, psychological, and musculoskeletal problems. This broad spectrum of complications highlights the importance of multidisciplinary management approaches that prioritize therapy, rehabilitation, and patient-centered care. Vulnerable populations such as paediatric patients, pregnant women, and immunocompromised individuals face unique risks and complications, necessitating continuous monitoring and tailored management strategies to reduce morbidity and mortality associated with COVID-19.

High nasopharyngeal and serum IL-6 levels and the - 573G > C polymorphism (rs1800796) are linked with the risk of severe COVID-19 in a Mexican population: a case‒control study

BACKGROUND

COVID-19 was the leading cause of death in Mexico between 2020 and 2021. SARS-CoV-2 infection varies widely among individuals and populations. Since variations in genes related to the immune response may play a role in the susceptibility to and outcome of COVID-19, the associations of gene polymorphisms (SNPs) of IL-6 (- 573G > C, rs1800796), TNF-α (- 308G > A, rs1800629), and IFN-γ (- 1615 C > T, rs2069705) with the expression levels of these proteins in the nasopharynx and serum were evaluated in a Mexican population with mild, severe, or critical COVID-19.

METHODS

A total of 560 COVID-19 patients (309 mild, 163 severe, and 88 critical cases) and 560 age- and sex-matched COVID-19-negative controls were recruited for this case‒control study. The selected SNPs were genotyped via allelic discrimination. Logistic regression analysis was conducted considering four models of inheritance, and ORs were determined for each genotypic variant, adjusting for associated comorbidities in the multivariate model. The nasopharyngeal mRNA expression levels of IL-6, IFN-γ and TNF-α were determined. The levels of IL-6, IFN-γ, IFN-α2, and TNF-α in the serum were quantified. Significant differences were assessed via the Wilcoxon Mann‒Whitney U test.

RESULTS

The C allele of the IL-6 - 573 SNP was associated with a greater risk of mild and severe COVID-19 (OR: 2.3, CI: 1.897-2.838, p = 0.0001; and OR: 1.5, CI: 1.167-1.949, p = 0.002, respectively), whereas the A allele of the TNF-α - 308 SNP and the T allele of the IFN-γ - 1615 SNP were shown protective roles against severe COVID-19 (OR: 0.3, CI: 0.189-0.537, p = 0.0001; and OR: 0.7, CI: 0.563-1.006, p = 0.05) and against critical COVID-19 (OR: 0.3, CI: 0.158-0.640, p = 0.001; and OR: 0.4, CI: 0.290-0.678, p = 0.0001), adjusting for diabetes and hypertension. Nasopharyngeal IL-6 expression levels were lower in mild COVID-19 patients (p = 0.001) than in critical patients (p = 0.005). Serum IL-6 levels were significantly elevated in the critical cases (p = 0.01).

CONCLUSIONS

Our results revealed that the IL-6 - 573 G > C SNP and increased IL-6 nasopharyngeal and serum levels are associated with the risk of severe COVID-19 in a Mexican population.

Evaluation of the effects of pre-exposure treatment with hydroxychloroquine on the risk of COVID-19 infection and on the efficacy of anti-COVID-19 vaccination during lupus or Gougerot-Sjögren's disease: Prepcov multicentre trial

OBJECTIVES

Some patients with SLE or Gougerot-Sjögren's disease (GSD) receive long-term treatment with hydroxychloroquine (HCQ), sometimes combined with immunosuppressive therapy (IS). This study sought to assess whether long-term HCQ therapy that had been initiated long before the COVID-19 pandemic had a protective or adverse effect on COVID-19 risk, severity of infection or immunity protection.

METHODS

This prospective multicentre study included 547 patients with SLE, GSD, autoimmune hepatitis, primary biliary cholangitis or cured viral hepatitis C divided into four groups according to HCQ (+/-) and IS (+/-) intake prior to the pandemic: HCQ+IS+ (n=112), HCQ+IS- (n=121), HCQ-IS+ (n=115) and HCQ-IS- (n=199). When COVID-19 vaccination was possible, patients were vaccinated as recommended. Vaccination efficacy was prospectively assessed on the basis of the postvaccination antibody titre.

RESULTS

Compared with HCQ+IS+ patients, HCQ-IS+ patients had a decreased risk of COVID-19 infection (p<0.001). Compared with HCQ+IS+ patients, HCQ-IS- patients had a decreased risk of contracting COVID-19 (p<0.001). Patients in the HCQ-IS+ or HCQ-IS- group had a lower risk of symptomatic or severe infection than HCQ+IS+ patients did (p=0.001 and p<0.001, respectively). Only patients who had two or more exposures (to vaccine and/or infection) had an increased likelihood of COVID-19 immunity after the last dose (p<0.001).

CONCLUSIONS

HCQ treatment that was initiated before the pandemic did not protect against COVID-19 infection. Moreover, non-exposure to HCQ treatment (combined or not with IS) was associated with decreased risk of COVID-19 infection and of developing a symptomatic or severe infection. HCQ and IS do not influence the vaccine response. Only two or more doses of vaccine result in a good vaccine response.

TRIAL REGISTRATION NUMBER

NCT04481633.

Thromboembolic Events in the Era of COVID-19: A Detailed Narrative Review

COVID-19, caused by the SARS-CoV-2 virus, is not only characterized by respiratory symptoms but is also associated with a wide range of systemic complications, including significant hematologic abnormalities. This is a comprehensive review of the current literature, using PubMed and Google Scholar, on the pathophysiology and incidence of thromboembolic events in COVID-19 patients and thromboprophylaxis. COVID-19 infection induces a prothrombotic state in patients through the dysregulation of the renin-angiotensin-aldosterone system (RAAS), endothelial dysfunction, elevated von Willebrand factor (vWF), and a dysregulated immune response involving the complement system and neutrophil extracellular traps (NETs). As a result, thromboembolic complications have emerged in COVID-19 cases, occurring more frequently in severe cases and hospitalized patients. These thrombotic events affect both venous and arterial circulation, with increased incidences of deep venous thrombosis (DVT), pulmonary embolism (PE), systemic arterial thrombosis, and myocardial infarction (MI). While DVT and PE are more common, the literature highlights the potential lethal consequences of arterial thromboembolism (ATE). This review also briefly examines the ongoing discussions regarding the use of anticoagulants for the prevention of thrombotic events in COVID-19 patients. While theoretically promising, current studies have yielded varied outcomes: Some suggest potential benefits, whereas others report an increased risk of bleeding events among hospitalized patients. Therefore, further large-scale studies are needed to assess the efficacy and safety of anticoagulants for thromboprophylaxis in COVID-19 patients.

Spatial analysis of COVID-19 incidence and mortality rates in northwest iran for future epidemic preparedness

The COVID-19 pandemic has underscored the critical need for effective public health strategies to combat infectious diseases. This study examines the epidemiological characteristics and spatial distribution of COVID-19 incidence and mortality in Zanjan Province, northwest Iran, to inform future epidemic preparedness. Using data from 39,739 hospitalized COVID-19 cases recorded between February 2020 and September 2021, sourced from the Medical Care Monitoring Center, we conducted descriptive and geospatial analyses. Demographic, clinical, and spatial variables were analyzed using logistic regression and advanced spatial techniques, including Kernel Density Estimation and Local Moran's I, to identify risk factors and disease hotspots. Results revealed that women accounted for 52% of cases, with higher incidence rates, while men exhibited higher mortality rates (7.86% vs. 7.80%). Urban areas, particularly the provincial capital, were identified as hotspots, with the highest patient density (20,384 cases per 10 km²). Comorbidities such as HIV/AIDS (OR: 4.85), chronic liver disease (OR: 3.6), chronic blood diseases (OR: 2.8), and cancer (OR: 2.5) significantly increased mortality risk, with ventilator use showing the highest odds ratio for death (OR = 91). Vaccination significantly reduced mortality, with fully vaccinated individuals experiencing a 6.3% mortality rate compared to 8.1% in unvaccinated individuals. Spatial analysis highlighted population density and mobility as key drivers of disease spread. These findings emphasize the importance of integrating spatial and epidemiological data to enhance pandemic preparedness. Targeted interventions in urban hotspots, early detection systems, and prioritizing vaccination for high-risk populations are critical for mitigating future outbreaks. This study provides a foundation for evidence-based public health strategies to strengthen global epidemic response and improve preparedness for future health crises.

Relationship Between Periodontitis and the Severity of Lung Infection Caused by COVID-19: A Case-Control Observational Study

Background and Aims

The ongoing COVID-19 pandemic necessitates a deeper understanding of risk factors associated with severe outcomes. Chronic Periodontitis, a persistent inflammatory condition affecting the gums, may be linked to increased COVID-19 severity. This study aimed to determine the relationship between periodontitis and the severity of lung infection caused by COVID-19.

Methods

This observational study was conducted at Valiasr Hospital, Zanjan, Iran, between 2019 and 2020. Participants included individuals with COVID-19-related pneumonia (cases) and a control group without COVID-19. Pneumonia severity was assessed using the Pneumonia Severity Index, while periodontal status was evaluated through clinical parameters such as the Plaque Index, Gingival Index, and probing depth (PD). Statistical analyses included Chi-square, Fisher's exact, Mann-Whitney U tests, and multivariate models to examine associations and control for potential confounders, including age, gender, education, and place of residence.

Results

The study included 160 participants, with 86 classified as COVID-19 cases and 74 as controls. Analysis revealed no significant disparities in demographic variables between the two groups. Additionally, no notable differences were observed in the distribution of periodontal conditions. However, a significant correlation emerged between periodontal indices and COVID-19 severity (p < 0.05). Further analysis showed a significant relationship between periodontal conditions and the severity of lung involvement in COVID-19. Logistic regression analysis identified PD as the only significant predictor of COVID-19 severity, with an odds ratio of 1.083 (95% CI: 1.002-1.171, p = 0.04), indicating an 8.3% increase in the odds of severe COVID-19 per unit increase in PD. Additionally, multinomial logistic regression highlighted associations between PD, extent of involvement, and disease type with the severity of COVID-19 pulmonary involvement, reinforcing their potential as predictive factors.

Conclusion

Further research is warranted to validate these observations, elucidate the underlying mechanisms, and explore potential interventions targeting periodontal health as a strategy for COVID-19 risk reduction.

SARS-CoV-2 Spike S1 Subunit Triggers Pericyte and Microvascular Dysfunction in Human Pancreatic Islets

The COVID-19 pandemic has profoundly affected human health; however, the mechanisms underlying its impact on metabolic and vascular systems remain incompletely understood. Clinical evidence suggests that SARS-CoV-2 directly disrupts vascular homeostasis, with perfusion abnormalities observed in various tissues. The pancreatic islet, a key endocrine miniorgan reliant on its microvasculature for optimal function, may be particularly vulnerable. Studies have proposed a link between SARS-CoV-2 infection and islet dysfunction, but the mechanisms remain unclear. Here, we investigated how SARS-CoV-2 spike S1 protein affects human islet microvascular function. Using confocal microscopy and living pancreas slices from organ donors without diabetes, we show that a SARS-CoV-2 spike S1 recombinant protein activates pericytes, key regulators of islet capillary diameter and β-cell function, and induces capillary constriction. These effects are driven by a loss of ACE2 from pericytes' plasma membrane, impairing ACE2 activity and increasing local angiotensin II levels. Our findings highlight islet pericyte dysfunction as a potential contributor to the diabetogenic effects of SARS-CoV-2 and offer new insights into the mechanisms linking COVID-19, vascular dysfunction, and diabetes.

ARTICLE HIGHLIGHTS

Different components of the renin-angiotensin system are expressed by vascular cells in human pancreatic islets. The islet microvasculature is responsive to vasoactive angiotensin peptides. This pancreatic renin-angiotensin system is targeted upon incubation with a SARS-CoV-2 spike recombinant protein. SARS-CoV-2 spike activates pericytes and constricts capillaries in human islets. Islet vascular dysfunction could contribute to dysglycemia in some patients with COVID-19.

Factors associated with mortality among patients aged 12 years and above requiring hospitalization for severe respiratory illness (SRI): Findings from the COVID-19 vaccine effectiveness evaluation in Kenya and Mali, 2022-2023

BACKGROUND

Mortality attributed to respiratory illnesses is well characterized in children <5 years. However, there is paucity of data among older populations. Here, we leveraged data from the COVID-19 Vaccine Effectiveness Evaluation to establish the factors associated with mortality among patients with severe respiratory illness (SRI) in Kenya and Mali.

METHODS

We enrolled patients (≥ 12 years) requiring hospitalization for SRI, defined as acute onset (≤ 14 days) of at least two of the following: cough, fever (reported/measured temperature of ≥38 °C), chills, rigors, myalgia, headache, sore throat, fatigue, congestion or runny nose, loss of taste or smell, or pneumonia diagnosis, from referral hospitals in Kenya and Mali. We collected demographic, clinical characteristics of the patients, and nasopharyngeal and oropharyngeal specimens for SARS-CoV-2 testing using RT-PCR. A mixed-effects logistic regression model was fitted to identify factors associated with 30-day mortality among patients with SRI.

RESULTS

Between July 2022 and October 2023 9947 SRI patients were enrolled, of whom 9743 were included in this analysis and 1620 (16.6 %) died (Kenya: 1533/7822 [20.0 %]; Mali: 87/1921 [4.5 %]). Compared to patients aged 12-24 years, those aged >64 years were more likely to die (adjusted Odds Ratio [aOR] = 2.36; 95 % Confidence Interval [95 % CI] 1.72-3.24). Patients who were in coma (aOR = 3.45; 95 %CI 2.27-5.24) or Intensive Care Unit (aOR = 2.98; 95 %CI 2.06-4.31), or had HIV infection (aOR = 2.47; 95 %CI 2.11-2.90), liver disease (aOR = 2.42; 95 %CI 1.57-3.74), cancer (aOR = 2.09; 95 %CI 1.46-2.99) or SARS-CoV-2 infected (aOR = 1.24; 95 %CI 1.02-1.52) were at increased risk of death. Additionally, diarrhea, malaise/fatigue, difficulty in breathing, confusion, mechanical ventilation, vasopressor support, malnutrition and admission to High Dependency Unit had significant associations.

CONCLUSION

Mortality was heightened among SRI patients who were older, required critical care, had chronic conditions and infected with SARS-CoV-2 suggesting need for early identification of these conditions to improve possible treatment outcomes.

Association between excess mortality due to COVID-19, full vaccination coverage, smoking, hypertension, and gross domestic product per capita/purchasing power parity across 10 Southeast Asian Countries

Objectives

Mass vaccination and cardiometabolic disorders have been reported to influence COVID-19 prognosis and mortality burden. We applied a generalized linear mixed model (GLMM) to explore the associations between COVID-19 mortality, full vaccination coverage, and cardiometabolic health indicators in Southeast Asia (SEAR).

Methods

A region-wide ecological analysis of aggregate COVID-19 data from 10 SEAR countries (January 2020 to December 2022) was performed. The databases used were from the John Hopkins University Coronavirus Resource Center and the WHO Health Organization. Excess deaths associated with COVID-19 per 100,000 and case fatality rate were the outcome variables. A GLMM was performed to determine the predictors of COVID-19 mortality, and adjustments were made for sociodemographic variables. The statistical significance level was set at P <0.01 (double-sided).

Results

The adjusted GLMM analysis showed that the number of excess deaths due to COVID-19 per 100,000 was strongly and positively associated with age-standardized smoking (coefficient of determination [coeff.] = 9.18 [standard error (SE): 2.15]; P <0.001) and hypertension prevalence (coeff. = 25.98 [SE: 9.15]; P <0.01), whereas it was strongly and negatively associated with the full vaccination coverage rate (coeff. = -5.23 [SE: 1.54]; P <0.01) and gross domestic product per capita/purchasing power parity (coeff. = -102.01 [SE: 18.31]; P <0.001). The COVID-19 case fatality rate was positively associated with the age-standardized prevalence of hypertension (coeff. = 0.30 [SE: 0.16]; P <0.01) and negatively correlated with the full vaccination coverage rate (coeff. = -0.05 [SE: 0.01]; P <0.01) and gross domestic product per capita/purchasing power parity (coeff. = -1.09 (SE: 0.34); p<0.001). The associations observed in the multivariate analysis remained in the stratified analysis by quartile.

Conclusions

The study findings suggest that implementing effective public health interventions that would have increased vaccine uptake and improve cardiometabolic health on one hand and initiatives that enhance country-level economy on the other hand would have reduced COVID-19 mortality in the SEAR.

Impact of IL-6 rs1800795 and rs1800796 polymorphisms on clinical outcomes of COVID-19: a study on severity of disease in Turkish population

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is exacerbated by cytokine storms, leading to severe inflammation. Interleukin-6 (IL-6) plays a critical role in this process, and variations in its promoter may influence disease severity. This study aims to investigate the relationship between IL6 promoter polymorphisms rs1800795 (G > C) and rs1800796 (G > C) and the severity of COVID-19 in the Turkish population. A total of 332 participants were included: 84 control, 80 with mild COVID-19, and 168 with severe COVID-19. IL6 polymorphisms were genotyped using the restriction fragment length polymorphism (RFLP) method. The genotypes rs1800795 GC (OR = 3.00, 95% CI: 1.669-5.398, p < 0.000), CC (OR = 7.44, 95% CI: 2.899-19.131, p < 0.000), and rs1800796 GC (OR = 2.76, 95% CI: 1.603-4.761, p < 0.000), as well as the alleles rs1800795 C (OR = 3.01, p < 0.000) and rs1800796 C (OR = 1.97, p = 0.002), may be associated with the severity of COVID-19. According to the Jonckheere-Terpstra (J-T) test, the most significant trends that vary linearly with disease severity were observed for D-dimer [J-T = 15.896, Effect size = 0.68 (0.61 to 0.76), p < 0.000] and CRP [J-T = 15.389, Effect size = 0.66 (0.59 to 0.73), p < 0.000]. The distribution of clinical parameters across genotype combinations (rs1800796/rs1800795*) showed that GC/GC* and GC/CC* were linked to a higher risk of severe inflammation, clotting, and organ damage. Additionally, it has been determined that the G-C and C-C haplotypes may be associated with increased severity of COVID-19. The rs1800795 and rs1800796 polymorphisms are linked to COVID-19 severity and could help guide future treatment strategies.

Intensive Care Unit Memories and Trauma Triggers for Acute Respiratory Distress Syndrome Survivors Hospitalized During the COVID-19 Pandemic

BACKGROUND

Intensive care unit (ICU) admissions can be traumatic for critically ill, ventilated acute respiratory distress syndrome (ARDS) patients due to fear of death, an inability to verbally communicate, reliance on health care professionals, and invasive medical interventions. Adult ARDS patients hospitalized during the COVID-19 pandemic were strictly isolated and had limited to no visitation from loved ones, impacting their access to support systems.

OBJECTIVE

To explore the memories and sensory triggers for them (if applicable) of adult ARDS survivors hospitalized during the COVID-19 pandemic.

METHODS

This study used a phenomenological design with an interpretative descriptive approach. Semistructured interviews with open-ended questions were conducted with survivors. Thematic analysis of 16 ARDS survivors' responses to ICU memories and sensory triggers questions was completed to identify the most prevalent themes.

RESULTS

Major themes for vivid memories included (1) altered reality, (2) vivid nonsense dreams, (3) medical treatment/procedures, and (4) feeling lonely/isolated. Themes for triggers included (1) seeing doctors/nurses/hospitals and medical equipment or seeing/hearing media depictions of them, (2) hearing ringtones and beeping/alarms, (3) seeing/hearing helicopters, (4) smelling cleaning products, and (5) seeing/touching scars.

DISCUSSION/CONCLUSIONS

Fifteen of the 16 ARDS survivors reported traumatic vivid memories, often triggered by sensory stimuli they encountered in their everyday lives. It is important for acute care and outpatient nurses to understand the impact of an ICU admission on ARDS survivors' mental health, so they can adopt evidence-based interventions to prevent or limit these effects.

N-acetyl-cysteine in Intensive Care Unit Patients with Acute Respiratory Distress Syndrome due to COVID-19: A Retrospective Cohort Study

COVID-19-related acute respiratory distress syndrome (ARDS) is linked to mortality, primarily due to a cytokine storm, oxidative stress imbalance, and pro-thrombotic state.PurposeWe assessed the potential association between N-acetyl-cysteine (NAC) and clinical outcomes in critically ill subjects with COVID-19-related ARDS.Material and MethodsWe included subjects with confirmed COVID-19 who were admitted to our ICU between March 1, 2020, and January 31, 2021, due to ARDS and necessitating invasive mechanical ventilation (IMV). Subjects who received standard of care (SOC) were compared with subjects who additionally received NAC 600 mg bid orally.ResultsA total of 243 subjects were included in this study. The results indicate significantly improved survival rates in the NAC plus SOC group, both in the unadjusted analysis and after adjusting for confounding factors such as ARDS severity (HR 0.48, 95% CI 0.32-0.70).ConclusionsWe found that oral administration of NAC was associated with reduced mortality in critically ill patients with COVID-19 related ARDS.

Artificial intelligence in respiratory pandemics-ready for disease X? A scoping review

OBJECTIVES

This study aims to identify repeated previous shortcomings in medical imaging data collection, curation, and AI-based analysis during the early phase of respiratory pandemics. Based on the results, it seeks to highlight essential steps for improving future pandemic preparedness.

MATERIALS AND METHODS

We searched PubMed/MEDLINE, Scopus, and Cochrane Reviews for articles published from January 1, 2000, to December 31, 2021, using the terms "imaging" or "radiology" or "radiography" or "CT" or "x-ray" combined with "SARS," "MERS," "H1N1," or "COVID-19." WHO and CDC Databases were searched for case definitions.

RESULTS

Over the last 20 years, the world faced several international health emergencies caused by respiratory diseases such as SARS, MERS, H1N1, and COVID-19. During the same period, major technological advances enabled the analysis of vast amounts of imaging data and the continual development of artificial intelligence algorithms to support radiological diagnosis and prognosis. Timely availability of data proved critical, but so far, data collection attempts were initialized only as individual responses to each outbreak, leading to long delays and hampering unified guidelines and data-driven technology to support the management of pandemic outbreaks. Our findings highlight the multifaceted role of imaging in the early stages of SARS, MERS, H1N1, and COVID-19, and outline possible actions for advancing future pandemic preparedness.

CONCLUSIONS

Advancing international cooperation and action on these topics is essential to create a functional, effective, and rapid counteraction system to future respiratory pandemics exploiting state of the art imaging and artificial intelligence.

KEY POINTS

Question What has been the role of radiological data for diagnosis and prognosis in early respiratory pandemics and what challenges were present? Findings International cooperation is essential to developing an effective rapid response system for future respiratory pandemics using advanced imaging and artificial intelligence. Clinical relevance Strengthening global collaboration and leveraging cutting-edge imaging and artificial intelligence are crucial for developing rapid and effective response systems. This approach is essential for improving patient outcomes and managing future respiratory pandemics more effectively.

Health outcomes one year after Omicron infection among 12,789 adults: a community-based cross-sectional study

Background

Characterizing the paradigm and impact of long COVID is crucial for addressing this worldwide health challenge. This study aimed to investigate the prevalence of long COVID one year after primary Omicron infection and characterize differences in long-term health consequence between participants with persistent long COVID and those who fully recovered.

Methods

This a community-based cross-sectional study conducted from December 2023 to March 2024 at the China-Japan Friendship Hospital and 16 administrative districts in Beijing. 12,789 participants infected with Omicron between December 2022 and January 2023 were recruited through stratified multistage random sampling and included in the final analysis. Of them, 376 participants with persistent long COVID and 229 without long COVID were matched for further physical examinations. The primary outcome was the prevalence of long COVID one year after infection. Secondary outcomes included muscle strength, exercise capacity, health-related quality of life (HRQoL), mental health, work status, laboratory tests, and examinations.

Findings

Among 12,789 participants (media [IQR] age, 48.4 [37.3 to 61.4] years; 7817 females [61.1%]), 995 of them (7.8%) experienced long COVID within one year, with 651 (5.1%) having persistent symptoms. Fatigue (598/995 [60.1%]) and post-exertional malaise (367/995 [36.9%]) were the most common symptoms. Brain fog had the lowest resolution proportion as 4.2% within one year. The odds of long COVID increased with reinfections (odds ratios for one reinfection 2.592 [95% CI: 2.188 to 3.061]; two or more: 6.171 [3.227 to 11.557]; all p < 0.001). Participants with persistent long COVID had markedly lower muscle strength (upper-limb: 26.9 ± 12.4 vs. 29.1 ± 14.5 Kg; lower-limb: 40.0 [27.0 to 62.0] vs. 43.0 [28.0 to 59.0] s), worse exercise capacity and poorer HRQoL, and meaningful difference in laboratory tests results compared to those without long COVID. They also exhibited significantly higher proportions of abnormal lung function (FEV1 %pred<80%: 13.0% vs. 2.0%; DLco %pred<80%: 32.7% vs. 19.9%) and lung imaging abnormalities (23.5% vs. 13.6%).

Interpretation

The considerable health burden of long COVID and the progression of neurological symptoms following Omicron infection warrant close monitoring. Utilizing professional questionnaires and developing reliable diagnostic tools are necessary for improving diagnosis and treatment of long COVID.

Funding

This work was supported by Beijing Research Center for Respiratory Infectious Diseases (BJRID2024-012), Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2022-I2M-CoV19-005/CIFMS 2021-I2M-1-048), the National Natural Science Foundation of China (82241056/82200114/82200009), the New Cornerstone Science Foundation.

Early Identification of Severe COVID-19 Cases and the Need for ICU Care Based on Clinical and Laboratory Risk Factors

Background and objective Treatment in ICUs became extremely difficult due to the growing number of coronavirus disease 2019 (COVID-19) patients at the height of the pandemic. Consequently, prompt patient triage depends on the early categorization of severe cases in such scenarios. This study aimed to provide an evidence-based strategy to ensure the best use of resources by triaging patients based on objective risk factors. Methods This retrospective observational study comprised 500 inpatients (>age 18 years) who were hospitalized between March 20 and April 19, 2020, at the Khyber Teaching Hospital (KTH) and Hayatabad Medical Complex (HMC) in Peshawar, Pakistan. The clinical, laboratory, and radiological parameters were assessed. Real-time polymerase chain reaction (RT-PCR) findings were used to confirm the diagnosis of COVID-19. Results A total of 19 potential clinical and laboratory risk factors associated with ICU admissions were identified. At least one comorbidity among chronic lung disease, cardiovascular disease (CVD), and diabetes was the factor with the strongest association with ICU admission with a univariable odds ratio (OR) of over 27, followed by renal disease and other COVID-19 sequelae such as diarrhea, respiratory rate (>24 breaths/minute), and positive RT-PCR (vs. negative) with an univariable OR between 9 and 15. Furthermore, a multivariate logistic regression model was further developed with five risk factors, including comorbidity, presence of chronic lung disease, presence of diabetes, and RT-PCR (positive vs. negative), male sex (vs. female), and older age (65.0-80.5 years), suggesting a good fit of the model to the data shown by the area under the receiver operator characteristic curve (AUC) of 0.943 (95% CI: 0.917, 0.969). Additionally, a chest CT scan showed the typical COVID-19 pneumonia with pulmonary involvement of 30-40%, which was further evaluated by the COVID-19 Reporting and Data System (CO-RADS). The typical COVID-19 pneumonia was on a scale of four (15/25) or five (19/25) lung lesions. Conclusions Based on our findings, this approach could be used to screen the severe cases of COVID-19 patients and help them to be treated in ICUs on time while preventing others from unnecessarily using ICUs in the setting of limited medical resources, such as the outbreak of a pandemic.

A comprehensive overview on the crosstalk between microRNAs and viral pathogenesis and infection

Infections caused by viruses as the smallest infectious agents, pose a major threat to global public health. Viral infections utilize different host mechanisms to facilitate their own propagation and pathogenesis. MicroRNAs (miRNAs), as small noncoding RNA molecules, play important regulatory roles in different diseases, including viral infections. They can promote or inhibit viral infection and have a pro-viral or antiviral role. Also, viral infections can modulate the expression of host miRNAs. Furthermore, viruses from different families evade the host immune response by producing their own miRNAs called viral miRNAs (v-miRNAs). Understanding the replication cycle of viruses and their relation with host miRNAs and v-miRNAs can help to find new treatments against viral infections. In this review, we aim to outline the structure, genome, and replication cycle of various viruses including hepatitis B, hepatitis C, influenza A virus, coronavirus, human immunodeficiency virus, human papillomavirus, herpes simplex virus, Epstein-Barr virus, Dengue virus, Zika virus, and Ebola virus. We also discuss the role of different host miRNAs and v-miRNAs and their role in the pathogenesis of these viral infections.

Dynamics of diabetes prevalence, incidence and mortality in France: A nationwide study, 2013-2021

AIM

To estimate the time trends of treated diabetes incidence, prevalence and mortality in France from 2013 to 2019 and to compare with the Covid-19 pandemic period (2020-2021).

METHODS

Using the French National Health Data System, people with treated diabetes ≥ 45 years-old were identified based on their medications. Annual time trends over 2013-2019 were estimated using Poisson log-linear model controlled for age, year and region for prevalence (aPTT), incidence (aITT) and mortality (aMTT). Numbers of incident cases and deaths in 2020-2021 were estimated from these trends, and compared with those observed.

RESULTS

Over 2013-2019, incidence and mortality declined significantly in men, aITT=-0.61 % (-0.95;-0.26); aMTT=-0.52 % (-0.81;-0.22), leading to a stable prevalence, aPTT=0.18 % (-0.03;0.40). In women, the fall in incidence was more marked, aITT=-1.45 % (-1.95;-0.95), mortality was stable, aMTT=-0.19 % (-0.54;0.15), leading to a significant decrease in prevalence, aPTT=-0.31 % (-0.60;-0.02). Compared with people not treated for diabetes, the relative risk of mortality increased significantly in men over the 2013-2019 period, from 1.38 (1.37;1.39) to 1.42 (1.41;1.43), while the risk remained stable in women, from 1.45 (1.44;1.46) to 1.46 (1.45;1.47). In 2020, there were 7,458 and 4,404 additional deaths and 3,550 and 4,919 new cases in respectively men and women. In 2021, there were 11,576 and 6,371 additional deaths and 30,057 and 26,169 new cases in respectively men and women.

CONCLUSION

This study reports a favorable dynamic of diabetes over 2013-2019 followed by a sharp increase in incidence and mortality in 2020 and 2021. Continued monitoring is necessary to identify long-term trend and potential indirect effect of the pandemic.

Vitamin D and its analogs in immune system regulation

Vitamin D was discovered as the cure for nutritional rickets, a disease of bone growth arising from inadequate intestinal calcium absorption, and for much of the 20th century, it was studied for its critical role in calcium homeostasis. However, we now recognize that the vitamin D receptor and vitamin D metabolic enzymes are expressed in numerous tissues unrelated to calcium homeostasis. Notably, vitamin D signaling can induce cellular differentiation and cell cycle arrest. Moreover, the vitamin D receptor and the enzyme CYP27B1, which produces the hormonal form of vitamin D, 1,25-dihydroxyvitamin D (1,25D), are expressed throughout the immune system. In addition, CYP27B1 expression in immune cells is regulated by physiological inputs independent of those controlling its expression in calcium homeostatic tissues. These observations have driven the development of 1,25D-like secosteroidal analogs and nonsecosteroidal analogs to separate the effects of vitamin D on cell differentiation and function from its calcemic activities. Notably, some of these analogs have had considerable success in the clinic in the treatment of inflammatory and immune-related disorders. In this review, we described in detail the mechanisms of vitamin D signaling and the physiological signals controlling 1,25D synthesis and catabolism, with a focus on the immune system. We also surveyed the effects of 1,25D and its analogs on the regulation of immune system function and their implications for human immune-related disorders. Finally, we described the potential of vitamin D analogs as anticancer therapeutics, in particular, their use as adjuncts to cancer immunotherapy. SIGNIFICANCE STATEMENT: Vitamin D signaling is active in both the innate and adaptive arms of the immune system. Numerous vitamin D analogs, developed primarily to minimize the dose-limiting hypercalcemia of the active form of vitamin D, have been used widely in preclinical and clinical studies of immune system regulation. This review presents a description of the mechanisms of action of vitamin D signaling, an overview of analog development, and an in-depth discussion of the immunoregulatory roles of vitamin D analogs.

Comparing Care Pathways Between COVID-19 Pandemic Waves Using Electronic Health Records: A Process Mining Case Study

The COVID-19 pandemic caused rapid shifts in the workflow of many health services, but evidence of how this affected multidisciplinary care settings is limited. In this data study, we propose a process mining approach that utilises timestamped data from electronic health records to compare care provider patterns across pandemic waves. To investigate healthcare patterns during the pandemic, we collected routine events from Scottish hospital episodes in adults with COVID-19 status, generating treatment logs based on care provider input. Conformance checking metrics were used to select the Inductive Miner infrequent (IMi) algorithm for downstream analysis. Visual diagrams from the discovered Petri Nets indicated interactions on provider- and activity-level data subsets. Measures of "cross-log conformance checking" and graph edit distance (GED) further quantified variation in care complexity in adverse subgroups. Our baseline cohort included 1153 patients with COVID-19 linked to 55,212 relevant care provider events. At the conformance checking stage, the IMi model achieved good log fitness (LF ¯ = 0.95 ) and generalisation ( G ¯ = 0.89 ), but limited precision (PR ¯ = 0.27 ) across all granularity levels. More structured care procedures were present in Wave 1, compared to limited multidisciplinary involvement in Wave 2. Care activities differed in patients with extended stay ( G E D = 348 , PR ¯ = 0.231 vs G E D = 197 , PR ¯ = 0.429 in shorter stays). We demonstrated that process mining can be incorporated to investigate differential complexity in patients with COVID-19 and derive fine-grained evidence on shifts in healthcare practice. Future process-driven studies could use clinical oversight to understand operational adherence and driving factors behind service changes during pressured periods.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41666-024-00181-6.