Risk Factors For COVID-19 Research Articles

Spatiotemporal hierarchical Bayesian analysis to identify factors associated with COVID-19 in suburban areas in Colombia

IntroductionThe pandemic had a profound impact on the provision of health services in Cúcuta, Colombia where the neighbourhood-level risk of Covid-19 has not been investigated. Identifying the sociodemographic and environmental risk factors of Covid-19 in large cities is key to better estimate its morbidity risk and support health strategies targeting specific suburban areas. This study aims to identify the risk factors associated with the risk of Covid-19 in Cúcuta considering inter -spatial and temporal variations of the disease in the city's neighbourhoods between 2020 and 2022. MethodsAge-adjusted rate of Covid-19 were calculated in each Cúcuta neighbourhood and each quarter between 2020 and 2022. A hierarchical spatial Bayesian model was used to estimate the risk of Covid-19 adjusting for socioenvironmental factors per neighbourhood across the study period. Two spatiotemporal specifications were compared (a nonparametric temporal trend; with and without space-time interaction). The posterior mean of the spatial and spatiotemporal effects was used to map the Covid-19 risk. ResultsThere were 65,949 Covid-19 cases in the study period with a varying standardized Covid-19 rate that peaked in October–December 2020 and April–June 2021. Both models identified an association of the poverty and stringency indexes, education level and PM10 with Covid-19 although the best fit model with a space-time interaction estimated a strong association with the number of high-traffic roads only. The highest risk of Covid-19 was found in neighbourhoods in west, central, and east Cúcuta. ConclusionsThe number of high-traffic roads is the most important risk factor of Covid-19 infection in Cucuta. This indicator of mobility and connectivity overrules other socioenvironmental factors when Bayesian models include a space-time interaction. Bayesian spatial models are important tools to identify significant determinants of Covid-19 and identifying at-risk neighbourhoods in large cities. Further research is needed to establish causal links between these factors and Covid-19.

Smoking cessation among tuberculosis patients during the coronavirus disease-2019 pandemic.

Smoking has been recognized as a significant risk factor for COVID-19 and mortality. The World Health Organization (WHO) has recommended smoking cessation to reduce the impact of COVID-19. This study aimed to evaluate the smoking cessation rate of patients starting tuberculosis (TB) treatment at six months using motivational interviewing based on the WHO "five steps to quit" model. In addition, we assessed the knowledge about smoking and the barriers to smoking cessation. We conducted a retrospective cohort study. Outpatients aged >18 years, smokers, and those who are starting TB treatment in two outpatient TB clinics were invited to participate. Patients received information about the importance of smoking cessation, especially in TB patients, and standardized advice based on guidelines. This information was repeated during phone calls during the second and fourth months of treatment. During the study period, 111 patients were included. The primary outcome was the smoking cessation rate at the end of the sixth month of treatment, which was 26.8% (19/71). The barriers to smoking cessation described by the patients were anxiety/depression (47.4%), seeing someone smoking (38.5%), drug use (19.2%), and alcohol abuse (2.6%). The assessment of knowledge about smoking showed that patients had some information gaps. In conclusion, TB smokers who tried to quit smoking during the COVID-19 pandemic faced many challenges. Despite this, we demonstrated a reasonable smoking cessation rate with a nurse-conducted motivational interview.

Could Anemia Impact the Severity of Infections? COVID-19 as an Example

Background The association between anemia and severity of infection as well as mortality rates among patients infected with COVID-19 has scarcely been studied. This is the first study UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate. Methods A retro-prospective chart review of hospitalized COVID-19 patients was conducted in a large COVID-19 referral hospital in UAE. The study included adult patients with confirmed COVID-19. Clinical and laboratory data, severity of the disease, ICU admissions, and mortality rates were analyzed and correlated to the presence of anemia among the patients. Results A total of 3092 patients were included. 362 patients (11.7%) were anemic and most of the cases were between asymptomatic and mild COVID-19 (77.4%, n=2393). Among patients with anemia, 30.1% (n=109) had moderate to severe COVID-19. Statistically, anemia was associated significantly with a higher risk for severe COVID-19 outcome compared to nonanemic patients (AOR:1.59, 95% CI:1.24-2.04, p<0.001). Intensive care unit (ICU) admission was almost 3 times higher among anemic patients compared to nonanemic (AOR:2.83,95% CI:1.89-4.25, p<0.001). In addition, the overall mortality rate of 2.8% (n=87) was 2.5-fold higher in anemic than nonanemic patients (OR:2.56, CI: 1.49-4.06, p<0.001). Moreover, older age (≥48-year-old) and male gender were independent predictors for severe illness (Age: OR=1.26, CI:1.07-1.51, p=0.006; Gender: OR:1.43,CI:1.15-1.78, p<0.001)) and ICU admission (Age: OR:2.08, CI:1.47-2.94, p<0.001; Gender: OR: 1.83, CI:1.12-3.00, p=0.008) whereas only age ≥48 years old contributed to higher mortality rate (OR:1.60, CI:1.04-2.46, p=0.034). Conclusion Anemia was a major risk factor for severe COVID-19, ICU admission and mortality among hospitalized COVID-19 patients. Thus, healthcare providers should be aware of monitoring the hematological parameters among hospitalized patients with COVID-19 and anemia to reduce the risk of disease complications and mortality. This association should also be considered in other infectious diseases.

Risk factors for COVID-19 associated pulmonary aspergillosis and outcomes in patients with acute respiratory failure in a respiratory sub-intensive care unit

BackgroundCOVID-19-associated pulmonary aspergillosis (CAPA) is burdened by high mortality. Data are lacking about non-ICU patients. Aims of this study were to: (i) assess the incidence and prevalence of CAPA in a respiratory sub-intensive care unit, (ii) evaluate its risk factors and (iii) impact on in-hospital mortality. Secondary aims were to: (i) assess factors associated to mortality, and (ii) evaluate significant features in hematological patients.Materials and methodsThis was a single-center, retrospective study of COVID-19 patients with acute respiratory failure. A cohort of CAPA patients was compared to a non-CAPA cohort. Among patients with CAPA, a cohort of hematological patients was further compared to another of non-hematological patients.ResultsThree hundred fifty patients were included in the study. Median P/F ratio at the admission to sub-intensive unit was 225 mmHg (IQR 155–314). 55 (15.7%) developed CAPA (incidence of 5.5%). Eighteen had probable CAPA (37.3%), 37 (67.3%) possible CAPA and none proven CAPA. Diagnosis of CAPA occurred at a median of 17 days (IQR 12–31) from SARS-CoV-2 infection. Independent risk factors for CAPA were hematological malignancy [OR 1.74 (95%CI 0.75–4.37), p = 0.0003], lymphocytopenia [OR 2.29 (95%CI 1.12–4.86), p = 0.02], and COPD [OR 2.74 (95%CI 1.19–5.08), p = 0.014]. Mortality rate was higher in CAPA cohort (61.8% vs 22.7%, p < 0.0001). CAPA resulted an independent risk factor for in-hospital mortality [OR 2.92 (95%CI 1.47–5.89), p = 0.0024]. Among CAPA patients, age > 65 years resulted a predictor of mortality [OR 5.09 (95% CI 1.20–26.92), p = 0.035]. No differences were observed in hematological cohort.ConclusionCAPA is a life-threatening condition with high mortality rates. It should be promptly suspected, especially in case of hematological malignancy, COPD and lymphocytopenia.

Coordination chemistry suggests that independently observed benefits of metformin and Zn2+ against COVID-19 are not independent

Independent trials indicate that either oral Zn2+ or metformin can separately improve COVID-19 outcomes by approximately 40%. Coordination chemistry predicts a mechanistic relationship and therapeutic synergy. Zn2+ deficit is a known risk factor for both COVID-19 and non-infectious inflammation. Most dietary Zn2+ is not absorbed. Metformin is a naked ligand that presumably increases intestinal Zn2+ bioavailability and active absorption by cation transporters known to transport metformin. Intracellular Zn2+ provides a natural buffer of many protease reactions; the variable “set point” is determined by Zn2+ regulation or availability. A Zn2+-interactive protease network is suggested here. The two viral cysteine proteases are therapeutic targets against COVID-19. Viral and many host proteases are submaximally inhibited by exchangeable cell Zn2+. Inhibition of cysteine proteases can improve COVID-19 outcomes and non-infectious inflammation. Metformin reportedly enhances the natural moderating effect of Zn2+ on bioassayed proteome degradation. Firstly, the dissociable metformin–Zn2+ complex could be actively transported by intestinal cation transporters; thereby creating artificial pathways of absorption and increased body Zn2+ content. Secondly, metformin Zn2+ coordination can create a non-natural protease inhibitor independent of cell Zn2+ content. Moderation of peptidolytic reactions by either or both mechanisms could slow (a) viral multiplication (b) viral invasion and (c) the pathogenic host inflammatory response. These combined actions could allow development of acquired immunity to clear the infection before life-threatening inflammation. Nirmatrelvir (Paxlovid®) opposes COVID-19 by selective inhibition the viral main protease by a Zn2+-independent mechanism. Pending safety evaluation, predictable synergistic benefits of metformin and Zn2+, and perhaps metformin/Zn2+/Paxlovid® co-administration should be investigated.

Clinical Characteristics of COVID-19 Patients and Risk Factors for Shortness of Breath: A Cross-Sectional Study in Bangladesh

Background: Exploring the clinical characteristics, and risk factors for severe complications among COVID-19-positive patients has been helpful in identifying the most vulnerable communities to which public healthpractitioners should pay special attention. This study aimed to evaluate the clinical characteristics of COVID-19 patients, and risk factors for shortness of breath among COVID-19-positive patients in Chattogram, Bangladesh.Materials and Methods: Data were collected using a structured and facilitator-administered questionnaire among the COVID-19-positive patients (N = 408). Multivariate logistic regression analysis was performed to explore the predictors of outcome variables. Data were analyzed using IBM SPSS version 24.0.Results: It was revealed that at least one comorbidity was found among about half of the study participants,while the most prevalent symptoms of COVID-19 patients consisted of fever, cough, loss of taste, loss of smell, fatigue, and sore pain. In addition, Azithromycin is a more common treatment in our country. The multivariate logistic regression displays the COVID-19 patients aged more than 50 years (AOR = 2.05, 95% CI: 1.13-3.71) and respondents with cardiovascular disease (AOR = 4.60, 95% CI: 1.51-8.58) and the second wave of the coronapandemic (AOR = 1.78, 95% CI: 1.06-2.99) were reported as a risk factor for having shortness of breath among the virus-infected people.Conclusion: The findings explored an empirical and practical basis for exploring the risk factors for severecomplications of COVID-19 patients. Furthermore, evidence from this study might play a key role in providingpolicymakers with research-based evidence in their continuous effort to prevent the COVID-19 pandemic.

Mental Health Concerns During COVID-19: An Observational Study Among a Predominantly Black Community in New York City.

This study examined the prevalence of mental health concerns and its association with COVID-19, selected social determinants of health, and psychosocial risk factors in a predominantly racial/ethnic minoritized neighborhood in New York City. Adult Harlem residents (N = 393) completed an online cross-sectional survey from April to September 2021. The Patient Health Questionnaire (PHQ-4) and the Post-Traumatic Stress Disorder (PC-PTSD) were used to evaluate mental health concerns. Poisson regression with robust variance quantified the associations of interests via prevalence ratios (PR) and 95% confidence intervals (CI). Two-thirds (66.4%) of theresidents reported experiencing mental health concerns, including PTSD (25.7%), depression (41.2%), and anxiety (48.1%). Residents with low-income housing status (PR = 1.16; 95% CI 1.01, 1.34), alcohol misuse (PR = 1.68; 95% CI 1.40, 2.01), food insecurity (PR = 1.23; 95% CI 1.07, 1.42), exposure to interpersonal violence (PR = 1.33; 95% CI 1.08, 2.65), and experience of discrimination (PR = 1.53, 95% CI 1.23-1.92) were more likely to report mental health concerns. Better community perception of the police (PR = 0.97, 95% CI 0.95, 0.99) was associated with fewer mental health concerns. No associations were observed for employment insecurity, housing insecurity, or household COVID-19 positivity with mental health concerns. This study showed a high prevalence of mental health concerns in a low-income racial/ethnic minoritized community, where COVID-19 and social risk factors compounded these concerns. Harlem residents face mental health risks including increased financial precarity, interpersonal violence, and discrimination exposure. Interventions are needed to address these concurrent mental health and psychosocial risk factors, particularly in racial/ethnic minoritized residents.

The risk of COVID-19 in Cushing's disease is independently related to disease activity (hypercortisolism) and obesity.

To evaluate the cumulative incidence, risk factors, and outcomes of COVID-19 in patients with Cushing's disease (CD). In all, 60 patients with CD following up in our outpatient clinic answered via phone interview a questionnaire about the occurrence of COVID-19 infection documented by RT-PCR (including the diagnosis date and clinical outcome) and vaccination status. Clinical and biochemical data on disease activity (hypercortisolism) and comorbidities (obesity, diabetes mellitus, and hypertension) were obtained from the patients' electronic medical records. Risk ratios (RRs) of risk factors were obtained using univariate and multivariate analyses. The cumulative incidence of COVID-19 in patients with CD during the observation period was 31.7%, which was higher than that in the general reference population (9.5%). The cumulative incidence of COVID-19 was significantly higher in patients with hypercortisolism (57% versus 17% in those without hypercortisolism, p = 0.012) and obesity (54% versus 9% in those without obesity, p < 0.001) but not in patients with hypertension or diabetes mellitus. On multivariate analysis, hypercortisolism and obesity were each independent risk factors for COVID-19 (RR 2.18, 95% CI 1.06-4.46, p = 0.033 and RR 5.19, 95% CI 1.61-16.74, p = 0.006, respectively). The incidence of COVID-19 in patients with CD was associated with hypercortisolism, as expected, and obesity, a novel and unexpected finding. Thus, correction of hypercortisolism and obesity should be implemented in patients with CD during the current and future COVID-19 outbreaks.

COVID-19 Susceptibility among ABO/RH Blood Groups in Tamil Nadu Population: A Retrospective Case–Control Study

Background: COVID-19 is a world pandemic with clinical manifestation from mild subclinical infection to severe illness. Literature suggests an evident correlation between the ABO blood group, Rhesus blood group, and COVID-19 in the recent past. The role of blood group in disease susceptibility and severity of COVID-19 varies in different geographical locations, as ABO blood group distribution varies among the human population with the impact of migration. Although various research have been done globally, scientific evidence with respect to the south Indian population remains limited, emphasizing the need for the present study to analyze the association of COVID-19 and blood groups in Tamil Nadu. Aim: The aim of this study was to analyze the potential susceptibility of COVID-19 among the blood groups (ABO and Rh type) in Tamil Nadu population. Materials and Methods: This was a noninterventional retrospective case–control study, with 500 patients who tested positive for COVID-19 being taken as the “cases,” while another 500 who tested negative were taken as the “controls.” The medical records, including the blood group and Rh factor, were collected from the government-recognized testing centers (Government Medical Hospital and Primary Health Centers, Tiruvallur, and Frontier Lifeline Hospital, Chennai) in Tamil Nadu, who came for COVID-19 screening by reverse transcriptase–polymerase chain reaction. The data were analyzed to associate its correlation with different blood groups. Results: Blood Group A showed significantly higher distribution among the cases (P = 0.030), and blood Groups O and B were significant among the controls (P = 0.026 and P = 0.000, respectively). Blood Group AB did not show any significant differences between the groups (P = 0.374). The odds ratio for AB, A, O, and B Groups for Rh (positive and negative) were shown to be 0.659, 0.591, 0.472, and 0.262, respectively, suggesting increased susceptibility toward Rh positive factor. Conclusion: In our study, blood Group A was found to be the most susceptible and blood Group O to be the least susceptible to COVID-19 in the Tamil Nadu population. In addition, the Rh positive factor showed more inclination toward COVID susceptibility than the Rh negative factor. ABO blood group may be considered a potential nonmodifiable and secondary risk factor for COVID-19 contributing to the disease pathobiology at immunological, biochemical, and physiological levels. Still, the intensity of their role and their exact mechanism in its association requires further exploration to validate the current findings.

Testing Positive for Covid-19, Signs and Symptoms, Treatment, and Covid-19-Related Anxiety: A Case of Factory Workers

Objective: This paper investigated the incidence of COVID-19 contraction, signs and symptoms, treatment, pandemic-related anxiety, and related factors in factory workers.&#x0D; Methods: This was a descriptive study conducted in a factory operating in the textile industry. No sampling was performed. The sample consisted of 287 volunteers. Data were collected using a sociodemographic characteristics questionnaire and the Coronavirus Anxiety Scale Short Form.&#x0D; Results: Less than half the participants tested positive for COVID-19 (41.1%). They were treated at home (68.6%) or in a hospital (19.5%). The most common symptoms were fatigue, joint pain, change in the sense of taste, and headache. The mean duration of home and hospital treatment was 7.00±0.00 and 12.49±6.14, respectively. Participants had a mean anxiety scale score of 7.65±3.71. Less than half the&#x0D; participants (31%) had high COVID-19 anxiety levels. The incidence of COVID-19 infection and anxiety was higher in participants who were on medication for chronic illnesses. Age and BMI were correlated with hospitalization for COVID-19.&#x0D; Conclusions: The incidence of COVID-19 infection is high among factory workers. Therefore, authorities should consider them a priority group for vaccination and provide them with training on COVID-19 risk factors and preventive measures.

Spatial analysis of COVID-19 risk factors: a case study in Bangladesh

Spatial analysis of COVID-19 risk factors: a case study in Bangladesh

Prevalence and characters of post-acute COVID-19 syndrome in healthcare workers in Kashan/Iran 2023: a cross-sectional study

BackgroundPost-acute COVID-19 syndrome that is called long COVID-19 consists of the symptoms that last more than 12 weeks with no other explanation. The present study aimed to determine the prevalence, frequency of symptoms, and risk factors of long COVID-19 in the healthcare workers (HCWs) of a selected hospital in Kashan/Iran in 2023.MethodsA total of 350 HCWs with a history of COVID-19 infection were randomly recruited to the study from February to May 2023. Participants completed a questionnaire including demographic characteristics, information related to COVID-19 infection, underlying diseases, and a checklist of long COVID-19 symptoms. Mann‒Whitney U test, chi-square test, T‒tests, and binary logistic regression were used for data analysis by SPSS 16.ResultsThe results showed that 75.7% of HCWs experienced symptoms of long COVID-19. The most common symptoms were fatigue (53.1%), cough (43.1%) and muscle weakness (37.1%). In bivariate analysis job title, body mass index (BMI), frequency and number of symptoms of COVID-19 infection, preexisting disease, tobacco use, age, and years of experience showed a significant statistical association with long COVID-19. In binary logistic regression the number of symptoms during COVID-19 infection, nursing occupation, use of corticosteroids, and symptoms of dyspnea and loss of taste could explain the occurrence of long COVID-19.ConclusionThe long COVID-19 is a prevalent condition among HCWs especially nurses. Symptoms of long COVID-19 such as fatigue and cough can persists over time. This chronic condition has significant associations with different clinical risk factors.

Risk Factors for COVID-19 and Respiratory Tract Infections during the Coronavirus Pandemic.

(1) Background: Some individuals are more susceptible to developing respiratory tract infections (RTIs) or coronavirus disease (COVID-19) than others. The aim of this work was to identify risk factors for symptomatic RTIs including COVID-19 and symptomatic COVID-19 during the coronavirus pandemic by using infection incidence, participant baseline, and regional COVID-19 burden data. (2) Methods: Data from a prospective study of 1000 frontline healthcare workers randomized to Bacillus Calmette-Guérin vaccination or placebo, and followed for one year, was analyzed. Parametric time-to-event analysis was performed to identify the risk factors associated with (a) non-specific symptomatic respiratory tract infections including COVID-19 (RTIs+COVID-19) and (b) symptomatic RTIs confirmed as COVID-19 using a polymerase chain reaction or antigen test (COVID-19). (3) Results: Job description of doctor or nurse (median hazard ratio [HR] 1.541 and 95% confidence interval [CI] 1.299-1.822), the reported COVID-19 burden (median HR 1.361 and 95% CI 1.260-1.469 for 1.4 COVID-19 cases per 10,000 capita), or a BMI > 30 kg/m2 (median HR 1.238 and 95% CI 1.132-1.336 for BMI of 35.4 kg/m2) increased the probability of RTIs+COVID-19, while positive SARS-CoV-2 serology at enrollment (median HR 0.583 and 95% CI 0.449-0.764) had the opposite effect. The reported COVID-19 burden (median HR 2.372 and 95% CI 2.116-2.662 for 1.4 COVID-19 cases per 10,000 capita) and a job description of doctor or nurse (median HR 1.679 and 95% CI 1.253-2.256) increased the probability of developing COVID-19, while smoking (median HR 0.428 and 95% CI 0.284-0.648) and positive SARS-CoV-2 serology at enrollment (median HR 0.076 and 95% CI 0.026-0.212) decreased it. (4) Conclusions: Nurses and doctors with obesity had the highest probability of developing RTIs including COVID-19. Non-smoking nurses and doctors had the highest probability of developing COVID-19 specifically. The reported COVID-19 burden increased the event probability, while positive SARS-CoV-2 IgG serology at enrollment decreased the probability of RTIs including COVID-19, and COVID-19 specifically.

Tele-Urology in the Era of COVID-19: an Experience of the Reconstructive Urology Department in Iran.

The outbreak of coronavirus has put additional pressure on the health care systems of many countries; but telemedicine can be an important way to deal with it, especially for people whose health has been affected by the virus. The present study aims to investigate the Implementation of a Tele-urology Program for Reconstructive Urologic Referrals: Initial Results and Patient Satisfaction. All patients with a history of a urethral reconstructive surgery during last year was entered to our study and two nurses collected data of demographic and past medical history of patients by existed. Telephone visits:Fellowship of reconstructive urology was connected to patients during a phone call and filled the USS-PROM and COVID-19 questionnaires. Face to face visits: All patients were asked to answer the questionnaire about recent exposure and infection by corona virus, recent travel and other risk factors of COVID-19. Mean of USSPROM scale was calculated as 1.65 (+2.91) with a range of 0-15. Based on categorization for USSPROM scale, 74 patients (94.8%) had mild symptoms while 4 patients (5.1%) had moderate symptoms and needed further medical attention. Four patients with moderate USSPROM score were required to cystoscopic evaluation, which one patient with moderate USSPROM score had severe stricture and candidate for redo urethroplasty. Two other patients need for urethral stricture dilatation. Cost was calculated based on taxi-service fee. Accordingly, the average (+SD) cost for in-person visits to the physician was estimated as 4.80 + 4.32 million Rials. In terms of distance, the average distance for receiving medical services according to the patient`s residence area was 373.2 +348.79 kilometres.In terms of the patient`s opinion regarding virtual examination, inappropriateness of virtual visits for physical examination, and patient`s inability to explain the problem correctly, patient`s condition at the time of the virtual visit were the main challenges reported by the respondent. Considering that the present COVID-19 emergency will likely last for months, telehealth could be the safest way to deliver urological care for a large percentage of the patients, such as those who are more at risk of unfavorable outcomes of COVID-19.

Cognitive flexibility, mental health status, and sleep quality in adults with psychosocial vulnerability: The moderating role of risk factors for COVID-19

PurposeThis study is aimed to investigate the direct and indirect effects of cognitive flexibility on mental health status and sleep quality with regard to the mediating role of risk factors for COVID-19 based on Structural Equation Modeling (SEM) in adults with psychosocial vulnerability. MethodsThe participants of this study were 500 individuals that were selected by an availability sampling method within a cross-sectional study. A demographic questionnaire, the Cognitive Flexibility Inventory (CFI), the Risk Factor Checklist for COVID-19 (RFCCOVID), the Pittsburgh Sleep Quality Index (PSQI), and the Symptom Checklist (SCL-25) were used for data collection. ResultsThe SEM showed that cognitive flexibility plus risk factors for COVID-19 explain 11.8% of mental health status and 25.6% of sleep quality variations in adults. ConclusionThis conceptual model for the direct and indirect role of cognitive flexibility with the moderating influence of risk factors for COVID-19 on psychopathological and sleep problems is valuable for psychotherapeutic interventions and prevention programs in adults.

The protective effect of tumor necrosis factor-alpha inhibitors in COVID-19 in patients with inflammatory rheumatic diseases compared to the general population-A comparison of two German registries.

To investigate, whether inflammatory rheumatic diseases (IRD) inpatients are at higher risk to develop a severe course of SARS-CoV-2 infections compared to the general population, data from the German COVID-19 registry for IRD patients and data from the Lean European Survey on SARS-CoV-2 (LEOSS) infected patients covering inpatients from the general population with SARS-CoV-2 infections were compared. 4310 (LEOSS registry) and 1139 cases (IRD registry) were collected in general. Data were matched for age and gender. From both registries, 732 matched inpatients (LEOSS registry: n = 366 and IRD registry: n = 366) were included for analyses in total. Regarding the COVID-19 associated lethality, no significant difference between both registries was observed. Age > 65°years, chronic obstructive pulmonary disease, diabetes mellitus, rheumatoid arthritis, spondyloarthritis and the use of rituximab were associated with more severe courses of COVID-19. Female gender and the use of tumor necrosis factor-alpha inhibitors (TNF-I) were associated with a better outcome of COVID-19. Inflammatory rheumatic diseases (IRD) patients have the same risk factors for severe COVID-19 regarding comorbidities compared to the general population without any immune-mediated disease or immunomodulation. The use of rituximab was associated with an increased risk for severe COVID-19. On the other hand, the use of TNF-I was associated with less severe COVID-19 compared to the general population, which might indicate a protective effect of TNF-I against severe COVID-19 disease.

Machine Learning-Based Approach for Identifying Research Gaps: COVID-19 as a Case Study.

Research gaps refer to unanswered questions in the existing body of knowledge, either due to a lack of studies or inconclusive results. Research gaps are essential starting points and motivation in scientific research. Traditional methods for identifying research gaps, such as literature reviews and expert opinions, can be time consuming, labor intensive, and prone to bias. They may also fall short when dealing with rapidly evolving or time-sensitive subjects. Thus, innovative scalable approaches are needed to identify research gaps, systematically assess the literature, and prioritize areas for further study in the topic of interest. In this paper, we propose a machine learning-based approach for identifying research gaps through the analysis of scientific literature. We used the COVID-19 pandemic as a case study. We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. Our approach is based on the BERTopic topic modeling technique, which leverages transformers and class-based term frequency-inverse document frequency to create dense clusters allowing for easily interpretable topics. Our BERTopic-based approach involves 3 stages: embedding documents, clustering documents (dimension reduction and clustering), and representing topics (generating candidates and maximizing candidate relevance). After applying the study selection criteria, we included 33,206 abstracts in the analysis of this study. The final list of research gaps identified 21 different areas, which were grouped into 6 principal topics. These topics were: "virus of COVID-19," "risk factors of COVID-19," "prevention of COVID-19," "treatment of COVID-19," "health care delivery during COVID-19," "and impact of COVID-19." The most prominent topic, observed in over half of the analyzed studies, was "the impact of COVID-19." The proposed machine learning-based approach has the potential to identify research gaps in scientific literature. This study is not intended to replace individual literature research within a selected topic. Instead, it can serve as a guide to formulate precise literature search queries in specific areas associated with research questions that previous publications have earmarked for future exploration. Future research should leverage an up-to-date list of studies that are retrieved from the most common databases in the target area. When feasible, full texts or, at minimum, discussion sections should be analyzed rather than limiting their analysis to abstracts. Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.

Symptomology following COVID-19 among adults in Alberta, Canada: an observational survey study

ObjectiveFatigue, headache, problems sleeping and numerous other symptoms have been reported to be associated with long COVID. However, many of these symptoms coincide with symptoms reported by the general population,...

Characteristics and outcomes of a hospitalized cohort with reduced mortality from COVID-19, White Mountain apache tribal lands, April 1 – July 31, 2020

BackgroundWidespread transmission of COVID-19 continues to threaten public health, particularly of rural, American Indian communities. Although COVID-19 risk factors for severe disease and clinical characteristics are well described in the general population, there has been little shared on hospitalized American Indian populations.MethodsIn this observational study, we performed chart extractions on all persons hospitalized with COVID-19 from April 1 through July 31, 2020 among an exclusively American Indian population living on or near Tribal lands in eastern Arizona. We provide descriptive statistics for the cohort stratified by presentation, comparing those who self-presented or were referred by an outreach program. Exploratory analyses were performed to identify risk factors for morbidity and mortality.ResultsDuring the observation period, 2262 persons were diagnosed with COVID-19 and 490 (22%) were hospitalized. Hospitalized persons had a median age of 54 years; 92% had at least one comorbidity, 72% had greater than one comorbidity, and 60% had a BMI of > 30. Most persons required supplemental oxygen (83%), but the majority (62%) only required nasal cannula and only 11% were intubated. The case fatality rates were 1.7% for the population, 7.1% among hospitalizations, and 9.3% among hospitalized patients 50 years and older. All rates that are significantly lower than those reported nationally during the same period.ConclusionsWe observed a cohort of American Indian patients hospitalized secondary to COVID-19 with greater number of comorbidities compared to the general population but with lower mortality rates. We posit that the primary driver of mortality reduction for this population and the hospitalized cohort was a community-based referral program that led to disproportionately lower fatality rates among the oldest persons.

Risk factors for severe COVID-19 in patients with rheumatic diseases

The aim – to study risk factors for severe COVID-19 in patients with rheumatic diseases (RD).Patients and methods. The study included medical histories of 464 patients with RD who were admitted at the V.A. Nasonova Research Institute of Rheumatology from September 27, 2021 to April 26, 2023Results. Age over 60 years, hypertension, obesity, lung disease, chronic kidney disease, coronary heart disease, diabetes mellitus, acute cerebrovascular accident or a history of pulmonary tuberculosis increase the risk of hospitalization in patients with RD with COVID-19 by 3–5 times. In addition, with an increase in the number of concomitant diseases, an increase in the risk of hospitalization was noted by 2–6 times. Taking glucocorticoids, including at a dose of ≥10 mg per day for prednisolone, mycophenolate mofetil and rituximab, leads to an increase risk of hospitalization by 1.5–4.5 times, while patients taking hydroxychloroquine or tumor necrosis factor α inhibitors was more often required outpatient treatment.Conclusions. It has been established that older age, the presence of comorbid pathology and the use of glucocorticoids, including at a dose of ≥10 mg per day for prednisolone, mycophenolate mofetil and rituximab, are risk factors for severe COVID-19.