Relationship Between Severity and Length of Exposure to COVID-19 Parameters and Resulting Government Responses and the Suicide Crisis Syndrome (SCS).

OBJECTIVE: The COVID-19 pandemic has had a globally devastating psychosocial impact. A detailed understanding of the mental health implications of this worldwide crisis is critical for successful mitigation of and preparation for future pandemics. Using a large international sample, we investigated in the present study the relationship between multiple COVID-19 parameters (both disease characteristics and government responses) and the incidence of the suicide crisis syndrome (SCS), an acute negative affect state associated with near-term suicidal behavior. METHODS: Data were collected from 5528 adults across 10 different countries in an anonymous web-based survey between June 2020 and January 2021. RESULTS: Individuals scoring above the SCS cut-off lived in countries with higher peak daily cases and deaths during the first wave of the pandemic. Additionally, the longer participants had been exposed to markers of pandemic severity (eg, lockdowns), the more likely they were to screen positive for the SCS. Findings reflected both country-to-country comparisons and individual variation within the pooled sample. CONCLUSION: Both the pandemic itself and the government interventions utilized to contain the spread appear to be associated with suicide risk. Public policy should include efforts to mitigate the mental health impact of current and future global disasters.

Next-generation sequencing of host genetics risk factors associated with COVID-19 severity and long-COVID in Colombian population.

Coronavirus disease 2019 (COVID-19) was considered a major public health burden worldwide. Multiple studies have shown that susceptibility to severe infections and the development of long-term symptoms is significantly influenced by viral and host factors. These findings have highlighted the potential of host genetic markers to identify high-risk individuals and develop target interventions to reduce morbimortality. Despite its importance, genetic host factors remain largely understudied in Latin-American populations. Using a case-control design and a custom next-generation sequencing (NGS) panel encompassing 81 genetic variants and 74 genes previously associated with COVID-19 severity and long-COVID, we analyzed 56 individuals with asymptomatic or mild COVID-19 and 56 severe and critical cases. In agreement with previous studies, our results support the association between several clinical variables, including male sex, obesity and common symptoms like cough and dyspnea, and severe COVID-19. Remarkably, thirteen genetic variants showed an association with COVID-19 severity. Among these variants, rs11385942 (p < 0.01; OR = 10.88; 95% CI = 1.36-86.51) located in the LZTFL1 gene, and rs35775079 (p = 0.02; OR = 8.53; 95% CI = 1.05-69.45) located in CCR3 showed the strongest associations. Various respiratory and systemic symptoms, along with the rs8178521 variant (p < 0.01; OR = 2.51; 95% CI = 1.27-4.94) in the IL10RB gene, were significantly associated with the presence of long-COVID. The results of the predictive model comparison showed that the mixed model, which incorporates genetic and non-genetic variables, outperforms clinical and genetic models. To our knowledge, this is the first study in Colombia and Latin-America proposing a predictive model for COVID-19 severity and long-COVID based on genomic analysis. Our study highlights the usefulness of genomic approaches to studying host genetic risk factors in specific populations. The methodology used allowed us to validate several genetic variants previously associated with COVID-19 severity and long-COVID. Finally, the integrated model illustrates the importance of considering genetic factors in precision medicine of infectious diseases.

Intelligent diagnosis of the severity of disease conditions in COVID-19 patients based on the LASSO method.

Purpose: The purpose of this study is to develop an intelligent diagnosis model based on the LASSO method to predict the severity of COVID-19 patients. Methods: The study uses the clinical data of 500 COVID-19 patients from a designated hospital in Guangzhou, China, and selects eight features, including age, sex, dyspnea, comorbidity, complication, lymphocytes (LYM), CRP, and lung injury score, as the most important predictors of COVID-19 severity. The study applies the LASSO method to perform feature selection and regularization, and compares the LASSO method with other machine learning methods, such as ridge regression, support vector machine, and random forest. Results: The study finds that the ridge regression model has the best performance among the four models, with an AUROC of 0.92 in the internal validation and 0.91 in the external validation. Conclusion: The study provides a simple, robust, and interpretable model for the intelligent diagnosis of COVID-19 severity, and a convenient and practical tool for the public and the health care workers to assess COVID-19 severity. However, the study also has some limitations and directions for future research, such as the need for more data from different sources and settings, and from prospective, longitudinal, multi-class classification models. The study hopes to contribute to the prevention and control of COVID-19, and to the improvement of the diagnosis and treatment of COVID-19 patients.

Effectiveness of Copeptin, MR-proADM and MR-proANP in Predicting Adverse Outcomes, Alone and in Combination with Traditional Severity Scores, a Secondary Analysis in COVID-19 Patients Requiring Intensive Care Admission.

Objective: To investigate whether copeptin, MR-proADM and MR-proANP, alone or integrated with the SOFA, MuLBSTA and SAPS II scores, are capable of early recognition of COVID-19 ICU patients at increased risk of adverse outcomes. Methods: For this predefined secondary analysis of a larger cohort previously described, all consecutive COVID-19 adult patients admitted between March and December 2020 to the ICU of a referral, university hospital in Northern Italy were screened, and clinical severity scores were calculated upon admission. A blood sample for copeptin, MR-proADM and MR-proANP was collected within 48 h (T1), on day 3 (T3) and 7 (T7). Outcomes considered were ICU and in-hospital mortality, bacterial superinfection, recourse to renal replacement therapy (RRT) or veno-venous extracorporeal membrane oxygenation, need for invasive mechanical ventilation (IMV) and pronation. Results: Sixty-eight patients were enrolled, and in-hospital mortality was 69.1%. ICU mortality was predicted by MR-proANP measured at T1 (HR 1.005, 95% CI 1.001-1.010, p = 0.049), although significance was lost if the analysis was adjusted for procalcitonin and steroid treatment (p = 0.056). Non-survivors showed higher MR-proADM levels than survivors at all time points, and an increase in the ratio between values at baseline and at T7 > 4.9% resulted in a more than four-fold greater risk of in-hospital mortality (HR 4.417, p < 0.001). Finally, when considering patients with any reduction in glomerular filtration, an early copeptin level > 23.4 pmol/L correlated with a more than five-fold higher risk of requiring RRT during hospitalization (HR 5.305, p = 0.044). Conclusion: Timely evaluation of MR-proADM, MR-proANP and copeptin, as well as changes in the former over time, might predict mortality and other adverse outcomes in ICU patients suffering from severe COVID-19.

Evaluating the potential mediating role of ADAMTS13 activity in the relationship between obesity and the severity of COVID-19: A retrospective cohort study.

Obesity and low enzyme A disintegrin and metalloproteinase with thrombospondin type-1 motif-13 (ADAMTS13) activity have been linked to poor coronavirus disease 2019 (COVID-19). Given that obesity may influence ADAMTS13 activity, it is feasible; however, it remains unclear whether ADAMTS13 activity acts as a mediator between obesity and COVID-19 outcomes. We investigated the link between body mass index (BMI) and COVID-19 outcomes, using ADAMTS13 activity as a mediator. ADAMTS13 activity was measured in 86 hospitalized COVID-19 patients. BMI, ADAMTS13 activity, and COVID-19 outcomes were assessed. Obese patients had a high odds ratio for low ADAMTS13 levels. When different levels of ADAMTS13 activity were considered, the severity of COVID-19 in obese patients was 4.5 times that in the normal BMI group. Furthermore, increased coagulopathy indicators correlated with low ADAMTS13 activity. Patients with elevated ALT and AST levels showed a 3 to 4-fold increase in the chances of low ADAMTS13 activity (OR:3.19, 95% CI:1.22-8.90, P = .021; OR:2.17, 95% CI:0.91-5.27, P = .082, respectively). When ADAMTS13 activity was considered, obese patients had greater COVID-19 severity and slower viral clearance than those with normal BMI. Low ADAMTS13 activity and impaired liver function are associated with poor COVID-19 outcomes. These findings encourage researchers to use molecular component identification to study the effects of obesity on the von Willebrand factor (VWF)/ADAMTS13 axis, COVID-19 pathogenesis, and outcomes.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Lung pneumonia severity scoring in chest X-ray images using transformers.

To create robust and adaptable methods for lung pneumonia diagnosis and the assessment of its severity using chest X-rays (CXR), access to well-curated, extensive datasets is crucial. Many current severity quantification approaches require resource-intensive training for optimal results. Healthcare practitioners require efficient computational tools to swiftly identify COVID-19 cases and predict the severity of the condition. In this research, we introduce a novel image augmentation scheme as well as a neural network model founded on Vision Transformers (ViT) with a small number of trainable parameters for quantifying COVID-19 severity and other lung diseases. Our method, named Vision Transformer Regressor Infection Prediction (ViTReg-IP), leverages a ViT architecture and a regression head. To assess the model's adaptability, we evaluate its performance on diverse chest radiograph datasets from various open sources. We conduct a comparative analysis against several competing deep learning methods. Our results achieved a minimum Mean Absolute Error (MAE) of 0.569 and 0.512 and a maximum Pearson Correlation Coefficient (PC) of 0.923 and 0.855 for the geographic extent score and the lung opacity score, respectively, when the CXRs from the RALO dataset were used in training. The experimental results reveal that our model delivers exceptional performance in severity quantification while maintaining robust generalizability, all with relatively modest computational requirements. The source codes used in our work are publicly available at https://github.com/bouthainas/ViTReg-IP .

Can the ADO Index Be Used as a Predictor of Mortality from COVID-19 in Patients with COPD?

Background: Several studies have shown that the risk of mortality due to COVID-19 is high in patients with COPD. However, evidence on factors predicting mortality is limited. Research Question: Are there any useful markers to predict mortality in COVID-19 patients with COPD?. Study Design and Methods: A total of 689 patients were included in this study from the COPET study, a national multicenter observational study investigating COPD phenotypes consisting of patients who were followed up with a spirometry-confirmed COPD diagnosis. Patients were also retrospectively examined in terms of COVID-19 and their outcomes. Results: Among the study patients, 105 were diagnosed with PCR-positive COVID-19, and 19 of them died. Body mass index (p= 0.01) and ADO (age, dyspnoea, airflow obstruction) index (p= 0.01) were higher, whereas predicted FEV1 (p< 0.001) and eosinophil count (p= 0.003) were lower in patients who died of COVID-19. Each 0.755 unit increase in the ADO index increased the risk of death by 2.12 times, and each 0.007 unit increase in the eosinophil count decreased the risk of death by 1.007 times. The optimum cut-off ADO score of 3.5 was diagnostic with 94% sensitivity and 40% specificity in predicting mortality. Interpretation: Our study suggested that the ADO index recorded in the stable period in patients with COPD makes a modest contribution to the prediction of mortality due to COVID-19. Further studies are needed to validate the use of the ADO index in estimating mortality in both COVID-19 and other viral respiratory infections in patients with COPD.

Correction: Body mass index and severity/fatality from coronavirus disease 2019: A nationwide epidemiological study in Korea.

[This corrects the article DOI: 10.1371/journal.pone.0253640.].

Biomarkers and sepsis severity as predictors of mechanical ventilation and mortality in COVID-19.

Introduction: Patients with septic shock face an elevated risk of mortality compared to those with sepsis. Several biomarkers, including lactate dehydrogenase, albumin, and lactate/albumin (L/A), have been associated with increased mortality in COVID-19 patients. This study aims to assess the relationship between sepsis, septic shock, and mortality, as well as the need for mechanical ventilation in COVID-19 patients. Demographic, sepsis severity factors, and biomarkers are examined. Methods: A retrospective case series from June 2020 to March 2021 included 490 patients diagnosed with sepsis or septic shock secondary to SARS-CoV-2 pneumonia. Time-to-event analyses were conducted for mechanical ventilation and mortality. Statistical significance was set at p ≤ .0038. Serum lactate, albumin, lactate/albumin ratio, C-reactive protein, platelet levels, and three sepsis severity scales, (CCI, SOFA, APACHE IV) were assessed. Results: Sepsis was identified in 352 patients (71.8%), while 138 had septic shock. Patients with septic shock were more likely to require invasive ventilator support. Factors associated with a higher risk of intubation included higher APACHE IV scores, elevated serum albumin levels, and increased L/A ratio. L/A ratio and serum lactate levels demonstrated the best diagnostic accuracy for mechanical ventilation (AUC, 0.964 and 0.946, respectively), mortality (AUC, 0.926 and 0.887, respectively). Discussion: Increased C-reactive protein, combined with increased serum lactate and a high lactate/albumin ratio, may assist clinicians in identifying COVID-19 patients at risk of mechanical ventilation and mortality upon admission. Optimal cut-off values for lactate (1.45-1.65 mmol/L) and L/A ratio (0.413) can aid in prioritizing medical care for at risk COVID-19 patients.

Charlson comorbidity index and the severity of community-acquired pneumonia caused by SARS-CoV-2: A retrospective analysis.

BACKGROUND: The Charlson comorbidity index (CCI) has been considered as a valid and reliable tool for predicting poor clinical outcomes and mortality in patients with coronavirus disease 2019 (COVID-19). However, its relationship with the severity of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has not been thoroughly explored. OBJECTIVES: The aim of the present study was to identify the impact of the comorbidity burden, quantitatively assessed by applying CCI, on the severity of inpatient community-acquired pneumonia (CAP) caused by SARS-CoV-2. MATERIAL AND METHODS: The study was conducted using the medical records of 208 patients with CAP who had an epidemiological history of a plausible SARS-CoV-2 infection, with positive polymerase chain reaction (PCR) confirmation no later than 1 month before being admitted for inpatient treatment. The CCI was calculated using a custom computer program. The statistical analysis of data was carried out using Statistica, v. 7.0. RESULTS: Our study found a significant correlation between the comorbidity burden and the severity of CAP caused by SARS-CoV-2. Specifically, we observed a low CCI score in the majority of patients in the pneumonia risk class II and III groups, and a high CCI score ≥3 in the majority of patients in the pneumonia risk class IV group. Moreover, a direct correlation between CCI and age was established. The comorbidities most commonly associated with CAP caused by SARS-CoV-2 were congestive heart failure, moderate to severe liver diseases and diabetes mellitus (DM) with chronic complications. CONCLUSIONS: The use of CCI to evaluate comorbid pathology in hospitalized patients with CAP caused by SARS-CoV-2 can assist the medical staff in developing timely preventive and therapeutic strategies, leading to improved patient prognosis.

The Long Coronavirus Disease (COVID) Symptom and Severity Score: Development, Validation, and Application.

OBJECTIVES: The primary focus of this research is the proposition of a methodological framework for the clinical application of the long coronavirus disease (COVID) Symptom and Severity Score (LC-SSS). This tool is not just a self-reported assessment instrument developed and validated but serves as a standardized, quantifiable means to monitor the diverse and persistent symptoms frequently observed in individuals suffering from long COVID. METHODS: A three-stage process was used to develop, validate, and establish scoring standards for the LC-SSS. Validation measures included correlations with other patient-reported measures, confirmatory factor analysis, Cronbach's α for internal consistency, and test-retest reliability. Scoring standards were determined using K-means clustering, with comparative assessments made against Hierarchical clustering and the Gaussian Mixture Model (GMM). RESULTS: The LC-SSS showed correlations with EQ-5D-5L (rs = -0.55), EQ-VAS (rs = -0.368), PHQ-9 (rs = 0.538), BAI (rs = 0.689), and ISI (rs = 0.516), confirming its construct validity. Structural validity was good with a CFI of 0.969, with Cronbach's α of 0.93 indicating excellent internal consistency. Test-retest reliability was also satisfactory (ICC = 0.732). K-means clustering identified three distinct severity categories in individuals living with long COVID, providing a basis for personalized treatment strategies. CONCLUSIONS: The LC-SSS provides a robust and valid tool for assessing long COVID. The severity categories established via K-means clustering demonstrate significant variation in symptom severity, informing personalized treatment and improving care quality for long COVID patients.

Beyond prevention: Unveiling the benefits of triple vaccination on COVID-19 severity and resource utilization in solid organ transplant recipients.

OBJECTIVE: Despite the widespread reduction in COVID-19-related morbidity and mortality attributed to vaccination in the general population, vaccine efficacy in solid organ transplant recipients (SOTR) remains under-characterized. This study aimed to investigate clinically relevant outcomes on double and triple-vaccinated versus unvaccinated SOTR with COVID-19. STUDY DESIGN AND SETTING: A retrospective propensity score-matched cohort study was performed utilizing data from the US Collaborative Network Database within TriNetX (n = 117,905,631). We recruited vaccinated and unvaccinated (matched controls) SOTR with COVID-19 over two time periods to control for vaccine availability: December 2020 to October 2022 (bi-dose, double-dose vaccine effectiveness) and December 2020 to April 2023 (tri-dose, triple-dose vaccine effectiveness). A total of 42 factors associated with COVID-19 disease severity were controlled for including age, obesity, diabetes, and hypertension. We monitored 30-day outcomes including acute respiratory failure, intubation, and death following a diagnosis of COVID-19. RESULTS: Subjects were categorized into two cohorts based on the two time periods: bi-dose cohort (vaccinated, n = 462; unvaccinated, n = 20,998); tri-dose cohort (vaccinated, n = 517; unvaccinated, n = 23,061).Compared to unvaccinated SOTR, 30-day mortality was significantly lower for vaccinated subjects in both cohorts: tri-dose (2.0% vs 7.5%, HR = 0.22 [95% CI: 0.11, 0.46]); bi-dose (3.7% vs 8.2%, HR = 0.43 [95% CI: 0.24, 0.76]). Hospital admission rates were similar between bi-dose vaccinated and unvaccinated subjects (33.1% vs 28.6%, HR = 1.2 [95% CI: 0.95, 1.52]). In contrast, tri-dose vaccinated subjects had a significantly lower likelihood of hospital admission (29.4% vs 36.6%, HR = 0.74 [95% CI: 0.6, 0.91]). Intubation rates were significantly lower for triple-vaccinated- (2.3% vs 5.2%, p < 0.05), but not double-vaccinated subjects (3.0% vs 5.2%, p > 0.05). CONCLUSION: In solid organ transplant recipients with COVID-19, triple vaccination, but not double vaccination, against SARS-CoV-2 was associated with significantly less hospital resource utilization, decreased disease severity, and fewer short-term complications. These real-world data from extensively matched controls support the protective effects of COVID-19 vaccination with boosters in this vulnerable population.

Use of serum KL-6 and chest radiographic severity grade to predict 28-day mortality in COVID-19 patients with pneumonia: a retrospective cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has had a global social and economic impact. An easy assessment procedure to handily identify the mortality risk of inpatients is urgently needed in clinical practice. Therefore, the aim of this study was to develop a simple nomogram model to categorize patients who might have a poor short-term outcome. METHODS: A retrospective cohort study of 189 COVID-19 patients was performed at Shanghai Ren Ji Hospital from December 12, 2022 to February 28, 2023. Chest radiography and biomarkers, including KL-6 were assessed. Risk factors of 28-day mortality were selected by a Cox regression model. A nomogram was developed based on selected variables by SMOTE strategy. The predictive performance of the derived nomogram was evaluated by calibration curve. RESULTS: In total, 173 patients were enrolled in this study. The 28-day mortality event occurred in 41 inpatients (23.7%). Serum KL-6 and radiological severity grade (RSG) were selected as the final risk factors. A nomogram model was developed based on KL-6 and RSG. The calibration curve suggested that the nomogram model might have potential clinical value. The AUCs for serum KL-6, RSG, and the combined score in the development group and validation group were 0.885 (95% CI: 0.804-0.952), 0.818 (95% CI: 0.711-0.899), 0.868 (95% CI: 0.776-0.942) and 0.932 (95% CI: 0.862-0.997), respectively. CONCLUSIONS: Our results suggested that the nomogram based on KL-6 and RSG might be a potential method for evaluating 28-day mortality in COVID-19 patients. A high combined score might indicate a poor outcome in COVID-19 patients with pneumonia.

Greater Disease Severity and Worse Clinical Outcomes in Patients Hospitalised with COVID-19 in Africa.

Background: COVID-19 cardiovascular research from Africa is limited. This study describes cardiovascular risk factors, manifestations, and outcomes of patients hospitalised with COVID-19 in the African region, with an overarching goal to investigate whether important differences exist between African and other populations, which may inform health policies. Methods: A multinational prospective cohort study was conducted on adults hospitalised with confirmed COVID-19, consecutively admitted to 40 hospitals across 23 countries, 6 of which were African countries. Of the 5,313 participants enrolled globally, 948 were from African sites (n = 9). Data on demographics, pre-existing conditions, clinical outcomes in hospital (major adverse cardiovascular events (MACE), renal failure, neurological events, pulmonary outcomes, and death), 30-day vitality status and re-hospitalization were assessed, comparing African to non-African participants. Results: Access to specialist care at African sites was significantly lower than the global average (71% vs. 95%), as were ICU admissions (19.4% vs. 34.0%) and COVID-19 vaccination rates (0.6% vs. 7.4%). The African cohort was slightly younger than the non-African cohort (55.0 vs. 57.5 years), with higher rates of hypertension (48.8% vs. 46.9%), HIV (5.9% vs. 0.3%), and Tuberculosis (3.6% vs. 0.3%). In African sites, a higher proportion of patients suffered cardiac arrest (7.5% vs. 5.1%) and acute kidney injury (12.7% vs. 7.2%), with acute kidney injury (AKI) appearing to be one of the strongest predictors of MACE and death in African populations compared to other populations. The overall mortality rate was significantly higher among African participants (18.2% vs. 14.2%). Conclusions: Overall, hospitalised African patients with COVID-19 had a higher mortality despite a lower mean age, contradicting literature that had previously reported a lower mortality attributed to COVID-19 in Africa. African sites had lower COVID-19 vaccination rates and higher AKI rates, which were positively associated with increased mortality. In conclusion, African patients were hospitalized with more severe COVID-19 cases and had poorer outcomes.

The relationship between quality of sleep and physical activity with level of symptom severity post-COVID-19 among HIV/AIDS patients.

OBJECTIVE: The COVID-19 pandemic led to many implications for patients after recovering from the disease, including HIV patients. The long symptoms such as breathlessness, fatigue, and sleep deprivation are common complaints for patients post-COVID-19. In this study, we investigate the correlation between sleep quality and physical activity and severity post-COVID-19 among patients at the hospital in Jakarta. PATIENTS AND METHODS: A cross-sectional study was conducted among 120 post-COVID patients recruited from a public hospital in Jakarta. All participants were aged over 20 years old, diagnosed with HIV/AIDS, and infected by COVID-19 within the last month. Eligibility included primary insomnia for at least 3 months and acute pain and high fever. Outcomes included sleep quality (the Pittsburgh Sleep Quality Index (PSQI), physical activity (the Global Physical Activity Questionnaire (GPAQ), and severity post-COVID-19 (severe post-COVID). Univariate analysis measured demographics, such as age, gender, etc. RESULTS: Among all study participants, 75.8% of patients had poor sleep quality and 60% of respondents 60% moderate physical activity. We found that sleep quality was not significantly associated with severe COVID-19 symptoms (p = 0.409). Physical activity was significantly associated with severe COVID-19 symptoms (p = 0.007). In the multivariate analysis, only physical activity (p = 0.011) and oxygen saturation (p = 0.000) were found to be independently related to the severity of the post-COVID-19 symptoms. CONCLUSIONS: Physical activity was associated with the severity of the COVID-19 symptoms (p = 0.007). However, sleep quality was not associated with the severity of COVID-19 (p = 0.409). Physical activity may be one of the factors that prevent further severe COVID-19 symptoms. Therefore, physical activity should be considered as an effective factor to reduce the impact of COVID-19 and should be included in health care and prevention strategies.

Impact of vaccination on COVID-19 severity during the second wave in Brunei Darussalam, 2021.

Objective: Coronavirus disease (COVID-19) vaccinations have been shown to prevent infection with efficacies ranging from 50% to 95%. This study assesses the impact of vaccination on the clinical severity of COVID-19 during the second wave in Brunei Darussalam in 2021, which was due to the Delta variant. Methods: Patients included in this study were randomly selected from those who were admitted with COVID-19 to the National Isolation Centre between 7 August and 6 October 2021. Cases were categorized as asymptomatic, mild (symptomatic without pneumonia), moderate (pneumonia), severe (needing supplemental oxygen therapy) or critical (needing mechanical ventilation) but for statistical analysis purposes were dichotomized into asymptomatic/mild or moderate/severe/critical cases. Univariate and multivariable analyses were conducted to identify risk factors associated with moderate/severe/critical disease. Propensity score-matched analysis was also performed to evaluate the impact of vaccination on disease severity. Results: The study cohort of 788 cases (mean age: 42.1 ± 14.6 years; 400 males) comprised 471 (59.8%) asymptomatic/mild and 317 (40.2%) moderate/severe/critical cases. Multivariable logistic regression analysis showed older age group (≥ 45 years), diabetes mellitus, overweight/obesity and vaccination status to be associated with increased severity of disease. In propensity score-matched analysis, the relative risk of developing moderate/severe/critical COVID-19 for fully vaccinated (two doses) and partially vaccinated (one dose) cases was 0.33 (95% confidence interval [CI]: 0.16-0.69) and 0.62 (95% CI: 0.46-0.82), respectively, compared with a control group of non-vaccinated cases. The corresponding relative risk reduction (RRR) values were 66.5% and 38.4%, respectively. Vaccination was also protective against moderate/severe/critical disease in a subgroup of overweight/obese patients (RRR: 37.2%, P = 0.007). Discussion: Among those who contracted COVID-19, older age, having diabetes, being overweight/obese and being unvaccinated were significant risk factors for moderate/severe/critical disease. Vaccination, even partial, was protective against moderate/severe/critical disease.

Severity of gambling behaviors: exploring associations with venues, legality, and substance use.

INTRODUCTION: The COVID-19 pandemic has been linked to an increase in gambling behaviors, potentially leading to Gambling Disorder (GD) and adverse health and social consequences. Problematic gambling has received little research attention over the years in Israeli society and the issue of gambling is not high on the list of priorities of Israeli policymakers. The present study examined gambling behavior in Israel on a continuum of severity and its association with venues where the gambling occurs, legality, attitude toward the legalization of casinos and poker, and substance use. METHODS: The study questionnaires were distributed to approximately 15,000 Jewish-Israeli adults via internet panel. From 3,088 Israeli adults who answered the questionnaire, 1,251 (40.5%) reported gambling in the last year and were included in the analyses. RESULTS: Based on the Problem Gambling Severity Index, 60% of participants were classified as non-problem gamblers, 25% as at low-risk for a gambling problem, 11% as at moderate risk, and 4% as having a gambling problem. Most online gambling was practiced by non-problem gamblers (40%) and most illegal gambling was by low-risk gamblers (34%). The more severe the gambling behavior was on the continuum, the more it was associated with illegal substance use and positive attitudes toward legalized casinos in Israel. Logistic regression showed the odds of developing moderate and problem gambling were 3.8 times higher for online gamblers (OR = 3.8; CI 2.6-5.4; p < 0.000) and 3.3 times higher for illegal gamblers (OR = 3.3; CI 2.2-4.9; p < 0.000). CONCLUSION: Though more research attention should be paid to gambling behaviors, harm reduction gambling interventions should be made available to all categories on the continuum of severity of gambling behaviors. The present study provides evidence-based information to promote health policies that aim to prevent and reduce harm for Israeli gamblers.

Evaluating the Association of Body Mass Index with COVID-19 Severity and Mortality using Japanese Administrative Claims Data.

INTRODUCTION: Obesity is a risk factor for aggravation of and mortality from coronavirus disease 2019 (COVID-19). We aimed to investigate the relationship between COVID-19 and Body Mass Index (BMI) in the Japanese population. METHODS: We used administrative claims data from an advanced treatment hospital in Japan and extracted data from patients hospitalized for COVID-19. The exposure variable was BMI measured at the time of admission, and the study outcomes were progression to critical illness and death. Analyses were performed for each age group. RESULTS: Overall, 58,944 patients met the inclusion criteria. The risk of critical illness increased monotonically with higher BMI. In contrast, the relationship between BMI and mortality follows a J-shaped curve; being underweight and obese are risk factors for mortality. When stratified by age, similar trends were observed for both critical illness and mortality. CONCLUSION: A higher BMI is a risk factor for the progression of COVID-19 severity, whereas both lower and higher BMIs are risk factors for mortality in the Japanese population.

COVID-19 severity in patients with chronic lymphocytic leukemia treated with venetoclax: a single-center observational cohort study.

Patients with chronic lymphocytic leukemia (CLL) are at high risk of developing severe COVID-19. The present study was undertaken to elucidate COVID-19 related morbidity and mortality in CLL patients treated with venetoclax. We present a single-center study of 108 patients with small lymphocytic lymphoma or CLL treated with venetoclax. Primary outcome was 30-day COVID-19 mortality. Secondary outcomes included COVID-19 severity and hospitalization rate. Forty-eight (44%) patients had PCR-verified SARS-COV-2 between March 2020 and January 2023. Thirty-six patients (75%) presented with asymptomatic/mild COVID-19 and 12 (25%) with severe/critical disease. The hospitalization rate was 46% with a 30-day mortality rate of only 4% and severe comorbidities as the primary cause of death. COVID-19 severity and mortality were similar before and during the Omicron era. High CIRS-scores (P < 0.02) and thrombocytopenia (P < 0.01) were more frequent in patients with severe/critical disease. In real-world data, most venetoclax treated patients presented with mild COVID-19. Hospitalization and mortality rates were low compared to data of general CLL populations. Our data indicate that venetoclax was a safe treatment option for CLL patients during the pandemic.