Pre-existing respiratory diseases may influence coronavirus disease (COVID-19) susceptibility and severity. However, the molecular mechanisms underlying the airway epithelial response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection severity in patients with chronic respiratory diseases remain unelucidated. Using an in vitro model of differentiated primary bronchial epithelial cells, we aimed to investigate the molecular mechanisms of SARS-CoV-2 infection in pre-existing cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD). Our study revealed reduced susceptibility of CF and COPD airway epithelia to SARS-CoV-2, relative to that in healthy controls. Mechanistically, reduced transmembrane serine protease 2 (TMPRSS2) activity potentially contributed to this resistance of CF epithelium. Upregulated complement and inflammatory pathways in CF and COPD epithelia potentially primed the antiviral state prior to infection. Analysis of a COVID-19 patient cohort validated our findings, correlating specific inflammatory markers (IP-10, SERPINA1, and CFB) with COVID-19 severity. This study elucidates SARS-CoV-2 pathogenesis and identifies potential biomarkers for clinical monitoring.

Chronic obstructive pulmonary disease (COPD) ranks among the leading causes of global mortality, and COVID-19 has intensified its challenges. Beyond the evident physical effects, the long-term psychological effects of COVID-19 are not fully understood.

This study aims to unveil the long-term psychological trends and patterns in populations with COPD throughout the COVID-19 pandemic and beyond via large-scale Twitter mining.

A 2-stage deep learning framework was designed in this study. The first stage involved a data retrieval procedure to identify COPD and non-COPD users and to collect their daily tweets. In the second stage, a data mining procedure leveraged various deep learning algorithms to extract demographic characteristics, hashtags, topics, and sentiments from the collected tweets. Based on these data, multiple analytical methods, namely, odds ratio (OR), difference-in-difference, and emotion pattern methods, were used to examine the psychological effects.

A cohort of 15,347 COPD users was identified from the data that we collected in the Twitter database, comprising over 2.5 billion tweets, spanning from January 2020 to June 2023. The attentiveness toward COPD was significantly affected by gender, age, and occupation; it was lower in females (OR 0.91, 95% CI 0.87-0.94; P<.001) than in males, higher in adults aged 40 years and older (OR 7.23, 95% CI 6.95-7.52; P<.001) than in those younger than 40 years, and higher in individuals with lower socioeconomic status (OR 1.66, 95% CI 1.60-1.72; P<.001) than in those with higher socioeconomic status. Across the study duration, COPD users showed decreasing concerns for COVID-19 and increasing health-related concerns. After the middle phase of COVID-19 (July 2021), a distinct decrease in sentiments among COPD users contrasted sharply with the upward trend among non-COPD users. Notably, in the post-COVID era (June 2023), COPD users showed reduced levels of joy and trust and increased levels of fear compared to their levels of joy and trust in the middle phase of COVID-19. Moreover, males, older adults, and individuals with lower socioeconomic status showed heightened fear compared to their counterparts.

Our data analysis results suggest that populations with COPD experienced heightened mental stress in the post-COVID era. This underscores the importance of developing tailored interventions and support systems that account for diverse population characteristics.

Substance-use disorders (SUDs) represent a major public health concern. The increased prevalence of SUDs within the general population has led to more patients with SUD being admitted to intensive care units (ICUs) for an SUD-related condition or with SUD as a relevant comorbidity. Multiprofessional providers of critical care should be familiar with these disorders and their impact on critical illness. Management of critically ill patients with SUDs is complicated by both acute exposures leading to intoxication, the associated withdrawal syndrome(s), and the physiologic changes associated with chronic use that can cause, predispose patients to, and worsen the severity of other medical conditions. This article reviews the epidemiology of substance use in critically ill patients, discusses the identification and treatment of common intoxication and withdrawal syndromes, and provides evidence-based recommendations for the management of patients exposed to chronic use.

Chronic obstructive pulmonary disease (COPD) is a risk factor for severe COVID-19. However, mortality after COVID-19 recovery in this population remains unclear.

We retrospectively enrolled individuals with COPD from the Korean National Health Insurance database. We compared the mortality rate in individuals with COPD who recovered from COVID-19 between 8 October 2020 and 31 December 2021 (COVID-19 cohort, n=2499) with that in 1:1 propensity score-matched controls (n=2499). The study population was followed until either death or 30 September 2022, whichever came first.

The COVID-19 cohort had a 4.8% mortality rate vs 2.7% in matched controls during a median follow-up of 319 days (IQR, 293-422 days), including 14 days of recovery time. The COVID-19 cohort had a higher risk of death than matched controls (adjusted HR (aHR)=1.81, 95% CI=1.35 to 2.45). The risk of mortality was notably higher in individuals with severe COVID-19 (aHR=5.05, 95% CI=3.65 to 6.97), especially during the first 180 days of recovery (highest during the first 30 days (aHR=20.25, 95% CI=7.79 to 52.64)). Non-severe COVID-19 does not increase the risk of mortality compared with controls (aHR=0.85, 95% CI=0.57 to 1.28).

Individuals with COPD recovering from COVID-19 showed an increased risk of long-term mortality, particularly within the first 180 days post-recovery, especially those who experienced severe COVID-19.

The relationships between pectoralis muscle parameters and outcomes in patients with coronavirus disease 2019 (COVID-19) remain uncertain.

We systematically searched PubMed, Embase, Web of Science and the Cochrane Library from 1 January 2019 to 1 May 2024 to identify non-overlapping studies evaluating pectoralis muscle-associated index on chest CT scan with clinical outcome in COVID-19 patients. Random-effects and fixed-effects meta-analyses were performed, and heterogeneity between studies was quantified using the I2 statistic. The risk of study bias was assessed using the Newcastle-Ottawa scale. Funnel plots for detecting small-study effects.

A total of 9 studies with 4109 COVID-19 patients were included. The meta-analysis findings revealed a correlation between pectoralis muscle parameters and COVID-19 prognosis. Specifically, patients with higher pectoralis muscle density (PMD) exhibited a lower mortality risk, with an odds ratio (OR) of 0.95 (95% CI: 0.92-0.99). The rate of intubation was lower in COVID-19 patients with a high pectoralis muscle index (PMI) (OR =  0.96, 95% CI: 0.92-1.00).

In summary, a low PMD is associated with a marginally elevated risk of mortality, whereas a decreased PMI represents a risk factor for intubation in COVID-19 patients. These findings suggest that pectoralis muscle parameters on chest CT may be a useful prognostic tool for COVID-19 patients.

It is anticipated that Chronic Obstructive Pulmonary Disease (COPD) has greater risk in acquiring COVID-19 infection and poorer outcome. However, current worldwide data are conflicting.

This study primarily aims to compare the outcomes of COVID-19 patients with COPD and those without COPD in terms of length of hospital stay (LOS), recovery or mortality, treatment received, and predictors of mortality.

This is a retrospective cohort chart review of 1,017 admitted adult COVID-19 patients from July to December 2020. Age, gender, smoking status, current control and medications for COPD, COVID-19 severity, symptoms, treatment, and outcomes of the two study groups were compared.

Prevalence rate of COPD was 3.8%. COVID-19 patients with COPD were older (median age of 69 vs 54, p<0.001), male (87% vs 50%, p<0.001), hypertensive (72% vs 48%, p=0.004), and with tuberculosis (31% vs 11%, p=0.002). COVID-19 patients with COPD more commonly needed oxygen therapy, High Flow Nasal Cannula, Mechanical Ventilation, Tocilizumab, Convalescent Plasma Therapy and Dexamethasone, and had longer LOS. Significant risk factors for mortality are malignancy, investigational therapies, smoking, and older age. There was no difference in survival rates between the two groups.

COPD increases the risk for severe COVID-19 and lengthens LOS.

The Saudi Thoracic Society (STS) developed an updated evidence-based guideline for diagnosing and managing chronic obstructive pulmonary disease (COPD) in Saudi Arabia. This guideline aims to provide a comprehensive and unbiased review of current evidence for assessing, diagnosing, and treating COPD. While epidemiological data on COPD in Saudi Arabia are limited, the STS panel believes that the prevalence is increasing due to rising rates of tobacco smoking. The key objectives of the guidelines are to facilitate accurate diagnosis of COPD, identify the risk for COPD exacerbations, and provide recommendations for relieving and reducing COPD symptoms in stable patients and during exacerbations. A unique aspect of this guideline is its simplified, practical approach to classifying patients into three classes based on symptom severity using the COPD Assessment Test and the risk of exacerbations and hospitalizations. The guideline provides the reader with an executive summary of recommended COPD treatments based on the best available evidence and also addresses other major aspects of COPD management and comorbidities. This guideline is primarily intended for use by internists and general practitioners in Saudi Arabia.

Emphysema, a significant global health issue, involves abnormal lung enlargement and wall destruction, affecting 9% to 12% of people worldwide. In the United States (US), 2 million people live with emphysema, with numbers expected to rise. Data on mortality trends and disparities associated with demographic factors is limited, underscoring our study's focus on analyzing these patterns in US adults. This study examined death certificates from the CDC WONDER database for individuals aged 25 and older who died with emphysema (J43) between 1999 and 2020. Age-adjusted mortality rates (AAMRs) and annual percent change were calculated by year, gender, age group, race/ethnicity, geographic region, and urbanization status. Between 1999 and 2020, there were 484,095 reported deaths among emphysema patients. The overall AAMR decreased from 18.5 to 7.2 per 100,000 population, with an annual decrease of 8% from 2008 to 2015, followed by a slight recent increase. Analyzing by age groups, older adults had the highest AAMR of 42. Men had significantly higher AAMRs than women (13.4 vs 7.8). By race, non-Hispanic (NH) White patients had the highest AAMRs (11.3), followed by NH American Indian or Alaska Native (8.2), NH Black (7.7), Hispanic (3.9), and NH Asian or Pacific Islander patients (3.1). Nonmetropolitan areas had higher AAMRs compared to metropolitan areas (11.7 vs 9.8). Emphysema mortality has decreased overall but recently increased slightly. Higher rates are seen among older adults, men, NH White patients, and nonmetropolitan residents. Policies are needed to continue reducing these death rates and to address these disparities.

Preserved ratio impaired spirometry (PRISm) represents a population with spirometry results that do not meet standardized COPD obstruction criteria, yet present with high respiratory symptom burden and might benefit from respiratory management and treatment. We aimed to determine prevalence of PRISm in US primary care patients diagnosed with COPD, describe their demographic, clinical, and CT scan characteristics.

An observational registry study utilizing the US APEX COPD registry, composed of patients diagnosed with COPD aged 35+ years. Demographic and clinical data were collected from EHRs and complemented by questionnaires. Multivariable logistic regression was performed to assess whether PRISm predicts lung function decline.

Prevalence of PRISm within a primary care population clinically diagnosed with COPD was 23.6% (678/2866, 95% CI 22.0-25.1). Those with PRISm were more likely female (55.9% vs 46.9%), younger (66.3±11.1 vs 69.2±10.3 years), with a greater mean BMI (33.5±9.2 vs 27.8±7.2 kg/m2), more often African American or Hispanic (37.2% vs 26.3%), and with fewer current smokers (33.1% vs 36.8%) when compared to those meeting COPD spirometry criteria (all p<0.05). Compared to COPD GOLD 0 patients, individuals with PRISm had greater BMI (33.5±9.2 vs 30.6±7.8), and were more likely current smokers (33.1% vs 23.4%), both p<0.05. Patients with PRISm had similar respiratory symptoms (chronic bronchitis, CAT, and mMRC) to overall COPD patients, but more frequently than GOLD 0 COPD patients (p<0.01). Emphysema was more commonly reported in CT scans from patients with PRISm 70.3% (260/369, 95% CI 65.8-75.3) than those with GOLD 0 COPD 64.1% (218/340, 95% CI 58.8-69.2) (p<0.05). PRISm status was not predictive of lung function decline.

One in four primary care patients with clinically diagnosed COPD in a large US registry fulfil the spirometric definition of PRISm rather than COPD, but suffers from emphysema in CT and significant respiratory symptoms.

Background: Understanding the interactions between age and comorbidities is crucial for assessing COVID-19 mortality, particularly in patients with cardiac and pulmonary conditions. This study investigates the relationship between comorbidities and mortality outcomes in a cohort of hospitalized COVID-19 patients, emphasizing the interplay of age, cardiac, and pulmonary conditions. Methods: We analyzed a cohort of 3005 patients hospitalized with COVID-19 between 2020 and 2022. Key variables included age, comorbidities (diabetes, cardiac, pulmonary, and neoplasms), and clinical outcomes. Chi-square tests and logistic regression models were used to assess the association between comorbidities and mortality. Stratified analyses by age, diabetes, and pulmonary conditions were conducted to explore interaction effects. Additionally, interaction terms were included in multivariable logistic regression models to evaluate the combined impact of age, comorbidities, and mortality. Results: Cardiac conditions such as hypertension, ischemic cardiopathy, and myocardial infarction showed significant protective effects against mortality in younger patients and in those without pulmonary conditions (p < 0.001). However, these protective effects were diminished in older patients and those with pulmonary comorbidities. Age was found to be a significant modifier of the relationship between cardiac conditions and mortality, with a stronger protective effect observed in patients under the median age (p < 0.001). Pulmonary comorbidities significantly increased the risk of mortality, particularly when co-occurring with cardiac conditions (p < 0.001). Diabetes did not significantly modify the relationship between cardiac conditions and mortality. Conclusions: The findings highlight the complex interactions between age, cardiac conditions, and pulmonary conditions in predicting COVID-19 mortality. Younger patients with cardiac comorbidities show a protective effect against mortality, while pulmonary conditions increase mortality risk, especially in older patients. These insights suggest that individualized risk assessments incorporating age and comorbidities are essential for managing COVID-19 outcomes.

Sleep disorders often coexist with personality and psychological issues, alongside nocturnal hypoxia. This study investigates the potential mediating role of nocturnal hypoxia between personality traits and psychological symptoms in individuals with sleep disorders.

A cohort comprising 171 participants reporting sleep disturbances was recruited from Dalian Seventh People's Hospital. Psychological symptoms were assessed using the Symptom Checklist-90-R (SCL-90-R), while personality traits were evaluated using the Eysenck Personality Questionnaire (EPQ). Nocturnal hypoxia status was determined through overnight polysomnography.

Mediation analysis, conducted using SPSS 23.0, demonstrated that the cumulative time of nocturnal peripheral oxygen saturation (SpO2) < 85% (T85) partially mediated the relationship between neuroticism and various psychological symptoms, including somatization (c=0.207, c'=0.164, a*b=0.043, proportion of mediation 20.8%), interpersonal sensitivity (c=0.360, c'=0.326, a*b=0.034, proportion of mediation 9.6%), depression (c=0.277, c'=0.234, a*b=0.042, proportion of mediation 15.3%), anxiety (c=0.240, c'=0.199, a*b=0.041, proportion of mediation 16.9%), hostility (c=0.241, c'=0.205, a*b=0.036, proportion of mediation 14.9%), phobic anxiety (c=0.271, c'=0.241, a*b=0.030, proportion of mediation 11.1%), and psychoticism (c=0.298, c'=0.266, a*b=0.032, proportion of mediation 10.8%).

These findings underscore the potential mediating role of nocturnal hypoxia in the association between neuroticism personality traits and psychological symptoms among individuals with sleep disorders. Our research holds considerable significance in advancing the quest for personalized treatments targeting psychological symptoms in individuals with sleep disorders.

To understand changes in purchasing behaviors and use of tobacco products such as e-cigarettes and cigarettes among different tobacco user groups during the COVID-19 pandemic using a mixed methods approach.

A quantitative online survey was conducted in October-November 2020 using a national probability sample of US adults (N = 1,460) comprising exclusive cigarette smokers (n = 1,080), dual users of both cigarettes and e-cigarettes (n = 143), and exclusive e-cigarette users (n = 237). Simultaneously, ten online focus groups were conducted with 61 adults in the Atlanta, GA area including exclusive smokers (n = 16), current E-cigarette users (n = 22), and transitioning (recently quit or currently quitting) smokers and/or E-cigarette users (n = 23).

From the survey, dual users vs. exclusive smokers had higher odds of buying cheaper cigarette brands (adjusted odds ratio (aOR) 2.50, 95% confidence interval (CI) = 1.49, 4.20), buying cigarettes online (aOR = 2.79; 95% CI = 1.02, 7.69), buying from Indian Reservations (aOR = 3.99; 95% CI = 2.07, 7.69), buying fewer cigarettes than normal (aOR = 4.01; 95% CI = 2.42, 6.65) and buying other tobacco products (aOR = 4.44; 95% CI = 2.24, 8.79). From the focus groups, participants perceived reduced accessibility, fear of contracting COVID-19, rising prices, and convenience to influence their purchasing behaviors and tobacco use.

Exclusive and dual users differed in their tobacco purchasing behaviors during the COVID-19 pandemic, such that dual users were more likely to change their purchasing behaviors (e.g., buying other tobacco products) than exclusive users. Educational campaigns and public health workers may promote interventions targeting dual users either to switch to reduced-risk products or quit smoking, particularly during stressful societal situations such as the COVID-19 pandemic.

The findings inform public health educators and policymakers to develop policies and interventions carefully tailored for tobacco user groups targeting the perceived factors influencing purchasing behaviors during challenging situations affecting tobacco product availability.

The presence of chronic obstructive pulmonary disease (COPD) and COVID-19 infection is a detrimental combination for patients and can cause negative clinical consequences. The investigation aimed to compare sociodemographic and clinical parameters of COPD individuals hospitalized for exacerbations before and at the end of the COVID-19 pandemic. An observational cross-sectional study including 222 patients with COPD was conducted in two stages: a survey and assessment of clinical and laboratory data of patients hospitalized from September 2022 to March 2023 (n=98) and processing of the medical histories of patients with COPD who received hospital treatment in 2017 and 2018 (n=124). A comparative analysis of patients who received inpatient treatment for COPD showed that the frequency of patients with Global Initiative for Chronic Obstructive Lung Disease (GOLD) I was half as high after the COVID-19 pandemic, whereas the individuals with GOLD IV were more frequent during the same period (p<0.05). Multiple regression analysis proved the effects of smoking status and previous COVID-19 infection on the health status of patients with COPD according to COPD Assessment Test data (p<0.05). There was an increase in the frequency of comorbid pathologies in the post-COVID period: hypertension, coronary heart disease, gastrointestinal diseases, anemia (p<0.05), and other diseases. This study highlights the significant influence of the COVID-19 infection on people with COPD, which manifested as impaired lung function and an increased incidence of comorbidities.

On December 7, 2022, China switched from dynamic zeroing strategy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reopening. A nationwide SARS-CoV-2 epidemic emerged rapidly. The effect of smoking on SARS-CoV-2 infection remains unclear. We aimed to retrospectively investigate the relationship between smoking and coronavirus disease 2019 (COVID-19) using a community-based cohort of smokers and non-smokers. We included participants from a pre-pandemic cohort with a prolonged follow-up period. Data on smoking status, body mass index, and history of other diseases were collected from health examination and consultation clinic records. Cox regression analysis was used to identify the relationship between groups and SARS-CoV-2 infection over time. We analysed 218 male patients with varied smoking statuses (46.3% current or ex-smokers; average age 68.63 ± 9.81 years). Two peaks in the epidemic were observed following the December 2022 outbreak. At the end of the second peak, non-smokers, current smokers, and ex-smokers had primary infection rates increase to 88.0%, 65.1%, and 81.0%, respectively, with a significant difference between the groups. Current smoking significantly protected against SARS-CoV-2 infection (HR 0.625, 95% CI 0.402-0.970, p = 0.036). Further analyses showed that the prevalence of pneumonia in the unvaccinated, older, diabetic, and non-smoking groups was significantly higher than that in the other groups (p < 0.05). Our study suggests a potential association between smoking and a reduced risk of SARS-CoV-2 infection and pneumonia. This indicates that nicotine and ACE2 play important roles in preventing COVID-19 and its progression. We suggest smokers use nicotine replacement therapy during hospitalization for COVID-19.

Previous studies have shown that patients with pre-existing chronic obstructive pulmonary diseases (COPD) were more likely to be infected with coronavirus disease (COVID-19) and lead to more severe lung lesions. However, few studies have explored the severity and prognosis of COVID-19 patients with different phenotypes of COPD.

The aim of this study is to investigate the value of the deep learning and radiomics features for the severity evaluation and the nucleic acid turning-negative time prediction in COVID-19 patients with COPD including two phenotypes of chronic bronchitis predominant patients and emphysema predominant patients.

A total of 281 patients were retrospectively collected from Hohhot First Hospital between October 2022 and January 2023. They were divided to three groups: COVID-19 group of 95 patients, COVID-19 with emphysema group of 94 patients, COVID-19 with chronic bronchitis group of 92 patients. All patients underwent chest computed tomography (CT) scans and recorded clinical data. The U-net model was pretrained to segment the pulmonary involvement area on CT images and the severity of pneumonia were evaluated by the percentage of pulmonary involvement volume to lung volume. The 107 radiomics features were extracted by pyradiomics package. The Spearman method was employed to analyze the correlation of the data and visualize it through a heatmap. Then we establish a deep learning model (model 1) and a fusion model (model 2) combined deep learning with radiomics features to predict nucleic acid turning-negative time.

COVID-19 patients with emphysema was lowest in the lymphocyte count compared to COVID-19 patients and COVID-19 companied with chronic bronchitis, and they have the most extensive range of pulmonary inflammation. The lymphocyte count was significantly correlated with pulmonary involvement and the time for nucleic acid turning negative (r=-0.145, P < 0.05). Importantly, our results demonstrated that model 2 achieved an accuracy of 80.9% in predicting nucleic acid turning-negative time.

The pre-existing emphysema phenotype of COPD severely aggravated the pulmonary involvement of COVID-19 patients. Deep learning and radiomics features may provide more information to accurately predict the nucleic acid turning-negative time, which is expected to play an important role in clinical practice.

In this study, we aimed to explore the impact of exacerbation history on future exacerbation and mortality with different inhaled drugs in chronic obstructive pulmonary disease (COPD) patients based on a Global Initiative Chronic Obstructive Lung Disease (GOLD) A and B classifications.

This observational study was based on the cohort study Real World Research of Diagnosis and Treatment of COPD (RealDTC). We collected data from COPD patients in China from 1 July 2017 to 31 December 2022. Patients were followed up until December 2023 or death. Further, we separated GOLD A and B patients into GOLD A0 and B0, who had no exacerbation during the previous year, and GOLD A1 and B1, who had only one exacerbation during the previous year. Study outcomes included moderate-to-severe exacerbation, hospitalisation, frequent exacerbation in the first year and all-cause mortality during total follow-up.

Of the 8318 eligible patients, GOLD E group of patients suffered from a greater risk of exacerbation in the first year and death than patients in the GOLD A and B groups. GOLD A1 group had a higher risk of moderate-to-severe exacerbation (hazard ratio (HR) = 2.087; 95% confidence interval (CI) = 1.419-3.068), hospitalisation (HR = 1.704; 95% CI = 1.010-2.705) and frequent exacerbation (HR = 1.983; 95% CI = 1.046-3.709) compared to GOLD A0. GOLD B1 group had a risk of moderate-to-severe exacerbation (HR = 1.321; 95% CI = 1.105-1.679) and mortality (HR = 1.362; 95% CI = 1.026-1.963) that exceeded the risk in GOLD B0 group. The treatment outcome of different inhaled drugs had no statistical differences in GOLD A0 group. In GOLD A1 group, only inhaled corticosteroids (ICS), in addition to long-acting β-2 agonist (LABA) and long-acting muscarinic antagonist (LAMA), reduced the risk of moderate-to-severe exacerbation in the first year compared to only LAMA. As for the GOLD B0 group, LABA and LAMA decreased the odds of moderate-to-severe exacerbation, hospitalisation, frequent exacerbation and mortality compared to only LAMA. ICS, LABA, and LAMA in GOLD B0 also down-regulated the risk of frequent exacerbation, compared to only LAMA. In addition, GOLD B1 patients treated with LABA and LAMA or ICS, LABA, and LAMA had a lower risk of moderate-to-severe exacerbation and hospitalisation. Meanwhile, ICS, LABA, and LAMA also reduced the risk of frequent exacerbation and mortality, compared to only LAMA in the multivariate Cox analysis.

Compared to the GOLD A or B group without exacerbation history, GOLD A patients with exacerbation history had a higher risk of future exacerbation, and GOLD B patients with exacerbation history had a higher risk of future exacerbation and mortality and benefited more from triple inhaler therapy.

When the coronavirus case was originally reported in Wuhan, China, in December 2019, it quickly spread throughout the world and became a global public health problem. Evidence of the admission and outcomes of coronavirus disease among patients with chronic obstructive pulmonary disease (COPD) has not been reported in Africa. Consequently, this research protocol uses a systematic review and meta-analysis of the admission and outcomes of COVID-19 in patients with COPD in Africa. All observational studies published in the English language and reporting on the prevalence, admission and outcomes of COVID-19 among patients with COPD in Africa will be included. A search strategy will be implemented using electronic databases and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol recommendations. The findings of this review will be reported to health program designers, decision-makers and healthcare providers.

Objectives Long-term consequences of COVID-19 in the post-pandemic era are still being investigated. Despite the growing data on COVID-19, there remains a lack of information regarding predictors of poor outcomes among chronic obstructive pulmonary disease (COPD) patients with COVID-19.  Methods A single-center prospective cohort study was conducted with a total of 172 adult COPD patients with COVID-19 pneumonia included. Univariable and multivariable analyses were conducted to define independent factors associated with ICU admission, need for mechanical ventilation, or all-cause mortality in 30 days following COVID-19 pneumonia. receiver operating characteristic (ROC) analyses evaluated the diagnostic performance of the independent predictors. Results Out of all the patients, 73 (42.4%) experienced poor outcomes. Lower forced expiratory volume in the first second (FEV1) (OR= 0.949, p= 0.004), higher radiological severity score (OR= 1.15, p= 0.004), and lower respiratory rate oxygenation (ROX) index (OR= 0.867, p<0.001) were independently associated with poor outcomes. ROX index was found a better predictor of poor outcome than oxygen saturation (SaO2)/fraction of inspired oxygen (FiO2) and partial pressure of oxygen (PaO2)/FiO2 ratio (area under the curve (AUC)=0.80 vs. 0.73, p=0.01; AUC= 0. 80 vs. 0.63 p=0.001). A significant decline in FEV1 values compared to baseline values was observed (55.9 ±12.9 vs. 62.1±10.0; p<0.001). Conclusion Lower baseline FEV1, higher COVID-19 radiological severity score, and lower ROX index are strongly associated with poor outcomes in COPD patients with COVID-19.

Older age and comorbidities are associated with adverse outcomes in patients with coronavirus disease 2019 (COVID-19); however, comprehensive identification of mortality risk factors can further guide disease management. We aimed to analyze predictors of in-hospital mortality in hospitalized COVID-19 patients.

This retrospective cohort study included 400 COVID-19 patients admitted between March and December 2020. Demographics, vital signs, medical history, presenting symptoms, laboratory findings, treatments, and outcomes were extracted from the patient's electronic medical records. Patients were stratified into survivor (n = 300) and nonsurvivor (n = 100) groups. Univariate and multivariate logistic regressions were used to analyze associations between variables and mortality.

Nonsurvivors were older (mean age 65 vs 45 years) and had more hypertension (60% vs 33%), diabetes (40% vs 20%), chronic obstructive pulmonary disease (20% vs 5%), and chronic kidney disease (15% vs 3%). Shorter symptom onset to admission (7 vs 4 days), lower oxygen saturation (92% vs 96%), lymphopenia, and elevated inflammatory and coagulation markers were also associated with mortality (all P < 0.001). Mechanical ventilation (60% vs 3%) and therapeutic anticoagulation were more common in nonsurvivors (all P < 0.001). Age over 75 years (adjusted odds ratio 5.2), chronic medical conditions, elevated D-dimer, and mechanical ventilation had the strongest independent associations with mortality (P < 0.001).

Older age, comorbidities such as chronic pulmonary and renal disease, disease severity parameters such as dysregulated inflammatory and coagulation markers, and the need for aggressive interventions predict increased mortality risk in hospitalized COVID-19 patients.

Rationale: Existing work suggests that patients with chronic obstructive pulmonary disease (pwCOPD) presented less frequently to the emergency department and were less likely to be hospitalized during the coronavirus disease (COVID-19) pandemic, but it is unclear if this was due to improved health and disease management or to increased barriers and/or avoidance of health care. Objectives: The objective of this study was to determine the impact of the pandemic on inpatient and outpatient healthcare use, disease incidence, and mortality rates in pwCOPD. Methods: A retrospective population-based analysis using linked administrative datasets from Alberta, Canada 18 months before and after March 12, 2020 was conducted to measure hospitalization, emergency department and outpatient visits, and COPD outpatient exacerbations during these time periods. Mortality data were also analyzed before versus after the pandemic, taking confirmed COVID-19 infection within 30 days into account. Subgroup analysis based on COPD exacerbation risk stratification was undertaken to determine if healthcare use differed based on exacerbation risk. Finally, sex-based analysis of healthcare use during the pandemic was also completed. Results: Hospitalization or emergency department visits and outpatient treatment for acute exacerbations of COPD dropped, whereas total outpatient COPD visits, including both virtual and in person, increased during the pandemic for pwCOPD. The mortality rate increased even after adjusting for COVID-19-associated deaths. Sex-based subgroup analysis showed a greater drop in acute care use for females, but the rise in mortality was seen for both sexes, with men experiencing a greater rate of mortality than women. Conclusions: Overall, pwCOPD accessed acute care resources less during the pandemic, which may have contributed to a rise in non-COVID-19 all-cause mortality.

Handgrip strength (HGS) is a non-invasive and reliable biomarker of overall health, physical function, mobility, and mortality. This study aimed to investigate the possible relationship between HGS and mortality in older adult patients hospitalized with COVID-19 in the intensive care unit (ICU) by Alpha (B.1.1.7) and Delta (B.1.617.2) variants. This retrospective cohort study was conducted on 472 COVID-19 patients (222 female and 250 male) aged 60-85 years admitted to the ICU. Demographic data, underlying comorbidities, COVID-19-related symptoms, as well as laboratory and computed tomography (CT) findings were obtained from the patient's medical records. Using a JAMAR® hydraulic dynamometer, the average grip strength value (kg) after three measurements on the dominant side was recorded for subsequent analysis. Low grip strength (LGS) was defined as an arbitrary cut-off of two standard deviations below the gender-specific peak mean value of normative HGS in Iranian healthy population, i.e. < 26 kg in males and < 14 kg in females. The findings showed lower mean grip strength and high frequency of LGS in the non-survivors patients versus survivors group and in the Delta (B.1.617.2) variant vs. Alpha (B.1.1.7) variant, respectively (both p < 0.01). The binary logistic regression analysis showed that chronic obstructive pulmonary disease (COPD) (adjusted odds ratio [OR] 5.125, 95% CI 1.425-25.330), LGS (OR 4.805, 95% CI 1.624-10.776), SaO2 (OR - 3.501, 95% CI 2.452-1.268), C-reactive protein (CRP) level (OR 2.625, 95% CI 1.256-7.356), and age (OR 1.118, 95% CI 1.045-1.092) were found to be independent predictors for mortality of patients with Alpha (B.1.1.7) variant (all p < 0.05). However, only four independent predictors including COPD (OR 6.728, 95% CI 1.683-28.635), LGS (OR 5.405, 95% CI 1.461-11.768), SaO2 (OR - 4.120, 95% CI 2.924-1.428), and CRP level (OR 1.893, 95% CI 1.127-8.692) can be predicted the mortality of patients with Delta (B.1.617.2) variant (p < 0.05). Along with the well-known and common risk factors (i.e. COPD, CRP, and SaO2), handgrip strength can be a quick and low-cost prognostic tool in predicting chances of mortality in older adults who are afflicted with COVID-19 variants.

Smoking behaviors, physical activities, and pulmonary diseases have been revealed to be associated with COVID-19 severity through observational research. The possible causative effect remains undetermined. To investigate this, we thus carried out a Mendelian randomization (MR) analysis. We chose genetic variants from genome-wide association studies that are strongly linked to 5 exposures related to smoking, 1 exposure related to drinking, 3 levels of physical activity, and 3 pulmonary diseases. The COVID-19 Host Genetics Initiative provided summary-level data for severe COVID-19 (13,769 cases and 1,072,442 noncases), hospitalized COVID-19 (32,519 cases and 2,062,805 noncases), and COVID-19 susceptibility (122,616 cases and 2,475,240 noncases). Univariate and multivariate MR analyses were carried out. Significant associations were found between severe COVID-19 and cigarette smoking per day (OR = 1.357, 95% CI: 1.087-1.694), lifetime smoking index (OR = 2.277, 95% CI: 1.602-3.325), and interstitial lung disease (OR = 1.23, 95% CI: 1.112-1.362), hospitalized COVID-19 and lifetime smoking index (OR = 2.199, 95% CI: 1.738-2.781), smoking initiation (OR = 1.419, 95% CI: 1.230-1.637), and interstitial lung disease (OR = 1.146, 95% CI: 1.082-1.214), as well as COVID-19 susceptibility and lifetime smoking index (OR = 1.39, 95% CI: 1.252-1.543), smoking initiation (OR = 1.235, 95% CI: 1.163-1.311), and duration of vigorous activity per day (OR = 0.733, 95% CI: 0.574-0.935). Duration of vigorous activity per day was suggestively inversely linked to hospitalized COVID-19 (OR = 0.434, 95% CI: 0.221-0.853) and severe COVID-19 (OR = 0.323, 95% CI: 0.123-0.850). The association for lifetime smoking index remained consistent with severe COVID-19, hospitalized COVID-19, and COVID-19 susceptibility in multivariable MR analysis. Genetic liability to lifetime smoking index mediated the interstitial lung disease effects on severe COVID-19 risk (21.0%) and hospitalized COVID-19 risk (14.4%). This study identified several smoking behaviors, duration of vigorous activity per day, and interstitial lung disease that may be causally related to COVID-19 severity.

Our study aimed to describe the group of severe COVID-19 patients at an institutional level, and determine factors associated with different outcomes.

A retrospective chart review of patients admitted with severe acute hypoxic respiratory failure due to COVID-19 infection. Based on outcomes, we categorized 3 groups of severe COVID-19: (1) Favorable outcome: progressive care unit admission and discharge (2) Intermediate outcome: ICU care (3) Poor outcome: in-hospital mortality.

Eighty-nine patients met our inclusion criteria; 42.7% were female. The average age was 59.7 (standard deviation (SD):13.7). Most of the population were Caucasian (95.5%) and non-Hispanic (91.0%). Age, sex, race, and ethnicity were similar between outcome groups. Medicare and Medicaid patients accounted for 62.9%. The average BMI was 33.5 (SD:8.2). Moderate comorbidity was observed, with an average Charlson Comorbidity index (CCI) of 3.8 (SD:2.6). There were no differences in the average CCI between groups(p = 0.291). Many patients (67.4%) had hypertension, diabetes (42.7%) and chronic lung disease (32.6%). A statistical difference was found when chronic lung disease was evaluated; p = 0.002. The prevalence of chronic lung disease was 19.6%, 27.8%, and 40% in the favorable, intermediate, and poor outcome groups, respectively. Smoking history was associated with poor outcomes (p = 0.04). Only 7.9% were fully vaccinated. Almost half (46.1%) were intubated and mechanically ventilated. Patients spent an average of 12.1 days ventilated (SD:8.5), with an average of 6.0 days from admission to ventilation (SD:5.1). The intermediate group had a shorter average interval from admission to ventilator (77.2 hours, SD:67.6), than the poor group (212.8 hours, SD:126.8); (p = 0.001). The presence of bacterial pneumonia was greatest in the intermediate group (72.2%), compared to the favorable group (17.4%), and the poor group (56%); this was significant (p<0.0001). In-hospital mortality was seen in 28.1%.

Most patients were male, obese, had moderate-level comorbidity, a history of tobacco abuse, and government-funded insurance. Nearly 50% required mechanical ventilation, and about 28% died during hospitalization. Bacterial pneumonia was most prevalent in intubated groups. Patients who were intubated with a good outcome were intubated earlier during their hospital course, with an average difference of 135.6 hours. A history of cigarette smoking and chronic lung disease were associated with poor outcomes.

Numerous studies have stated that comorbidities are risk factors for coronavirus disease 2019 (COVID-19) mortality, but few have considered the severity or stage of these comorbidities. The aim of this study was to determine the association between the severity of comorbidity, age, and number of COVID-19 vaccinations with COVID-19 mortality. This case-control study was conducted from July 2021 until December 2022 at the Dr. Soetomo General Academic Hospital, Surabaya, Indonesia. The patients were divided into non-survived patients (case group) and survived patients (control group). The inclusion criteria for cases were adult patients hospitalized with confirmed COVID-19, based on reverse transcriptase-polymerase chain reaction (RT-PCR) testing of nasopharyngeal swabs. Using total sampling, 1,046 confirmed COVID-19 patients, which consisted of 450 (43%) non-survived patients and 596 (57%) survived patients, were included. The most common comorbidity was diabetes mellitus (DM) (82.7%), chronic kidney disease (CKD) (43%), hypertension (25.7%), and obesity (23.6%). Our multivariate analysis indicated that older age (aOR: 1.03; 95%CI: 1.02-1.04, p<0.001), male sex (aOR: 1.29; 95%CI: 1.11- 2.00, p=0.007), severe COVID-19 at first admission (aOR: 3.13; 95%CI: 2.08-4.73, p<0.001), having pneumonia (aOR: 1.99; 95%CI: 1.21-3.33, p=0.005), poorly controlled DM with HbA1c≥9% (aOR: 2.90; 95%CI: 1.72-4.89, p<0.001), severe obesity with body mass index (BMI)≥30 (OR: 2.90; 95%CI: 1.72-4.89, p<0.001), hypertension stage 2 (aOR: 1.99; 95%CI: 1.12-3.53, p=0.019) or stage 3 (aOR: 6.59; 95%CI: 2.39-18.17, p<0.001), CKD stage 3 (aOR: 2.50; 95%CI: 1.36-4.59, p=0.003), stage 4 (aOR: 5.47; 95%CI: 2.18-13.69, p<0.001) or stage 5 (aOR: 1.71; 95%CI: 1.04-2.81, p=0.036), and having chronic lung disease (aOR: 3.08; 95%CI: 1.22-7.77, p=0.017) significantly increased the risk of COVID-19 mortality. In contrast, COVID-19 vaccination reduced the risk of COVID-19-associated death. This study highlights that more severe comorbidities, advanced age, and incomplete vaccination were associated with COVID-19 mortality.

Knee osteoarthritis (OA) is a prevalent degenerative disease affecting synovial joints, predominantly the knee, leading to various complications, including mental health conditions like depression and anxiety. This systematic review aimed to determine the prevalence of depression and anxiety in knee OA patients.

A comprehensive literature search was conducted in various databases till September 15, 2023. Studies focusing on the prevalence of mental health issues in patients with knee OA were included, excluding narrative reviews, protocols, unpublished reports, editorials, case reports, abstracts, and commentaries. All statistical analyses were performed in R version 4.2.3.

This review included a total of 14 studies involving middle-aged to elderly adult patients with knee OA, with ages ranging from 45 to 75 years. Among these, 13 studies involving 3390 adult patients with an average age of 59.75 years reported a pooled prevalence of depression of 30% (95% confidence interval: 18-43), demonstrating a substantial heterogeneity (I 2=98%). Additionally, anxiety was identified with a combined prevalence of 27% (95% confidence interval: 24-30) based on three studies that included 1407 older adult patients with an average age of 62.1 years. These studies displayed minimal heterogeneity (I 2=7%).

The findings show a significant prevalence of depression among adult patients with knee OA and anxiety among older adults with knee OA, emphasizing the need for integrated healthcare approaches that address both orthopedic and mental health conditions. More comprehensive research is essential to deepen our understanding of the connection between mental illnesses and knee OA and to develop effective preventive and treatment strategies.

Evidence for the impact of smoking on coronavirus disease 2019 (COVID-19) is contradictory, and there is little research on vaping. Here we provide greater clarity on mechanisms perturbed by tobacco cigarette, electronic cigarette and nicotine exposures that may impact the risks of infection and/or disease severity.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the Ovid and Web of Science databases were searched. Study design and exposure-induced gene expression changes were extracted. Each study was quality assessed and higher confidence scores were assigned to genes consistently changed across multiple studies following the same exposure. These genes were used to explore pathways significantly altered following exposure.

125 studies provided data on 480 genes altered by exposure to tobacco cigarettes, e-cigarettes, nicotine or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Genes involved in both SARS-CoV-2 viral-entry and inflammation were changed following exposure. Pathway analysis revealed that many of those genes with high confidence scores are involved in common cellular processes relating to hyperinflammatory immune responses.

Exposure to tobacco cigarettes, e-cigarettes or nicotine may therefore impact initial host-pathogen interactions and disease severity. Smokers and vapers of e-cigarettes with nicotine could potentially be at increased risk of SARS-CoV-2 infection, associated cytokine storm, and acute respiratory distress syndrome. However, further research is required, particularly on e-cigarettes, to determine the biological mechanisms involved in perturbation of viral-entry genes and host-pathogen interactions and subsequent responses within the respiratory tract. This will improve our physiological understanding of the impact of smoking and vaping on COVID-19, informing public health advice and providing improved guidance for management of SARS-CoV-2 and other respiratory viruses.

Cigarette smoking is associated with COVID-19 prevalence and severity, but the mechanistic basis for how smoking alters SARS-CoV-2 pathogenesis is unknown. A potential explanation is that smoking alters the expression of the SARS-CoV-2 cellular receptor and point of entry, angiotensin converting enzyme-2 (ACE-2), and its cofactors including transmembrane protease serine 2 (TMPRSS2). We investigated the impact of cigarette smoking on the expression of ACE-2, TMPRSS2, and other known cofactors of SARS-CoV-2 infection and the resultant effects on infection severity in vitro. Cigarette smoke extract (CSE) exposure increased ACE-2 and TMPRSS2 mRNA expression compared to air control in ferret airway cells, Calu-3 cells, and primary human bronchial epithelial (HBE) cells derived from normal and COPD donors. CSE-exposed ferret airway cells inoculated with SARS-CoV-2 had a significantly higher intracellular viral load versus vehicle-exposed cells. Likewise, CSE-exposure increased both SARS-CoV-2 intracellular viral load and viral replication in both normal and COPD HBE cells over vehicle control. Apoptosis was increased in CSE-exposed, SARS-CoV-2-infected HBE cells. Knockdown of ACE-2 via an antisense oligonucleotide (ASO) reduced SARS-CoV-2 viral load and infection in CSE-exposed ferret airway cells that was augmented by co-administration of camostat mesylate to block TMPRSS2 activity. Smoking increases SARS-CoV-2 infection via upregulation of ACE2 and TMPRSS2.

Humoral immunity in COVID-19 includes antibodies (Abs) targeting spike (S) and nucleocapsid (N) SARS-CoV-2 proteins. Antibody levels are known to correlate with disease severity, but titers are poorly reported in mild or asymptomatic cases. Here, we analyzed the titers of IgA and IgG against SARS-CoV-2 proteins in samples from 200 unvaccinated Hospital Workers (HWs) with mild COVID-19 at two time points after infection. We analyzed the relationship between Ab titers and patient characteristics, clinical features, and evolution over time. Significant differences in IgG and IgA titers against N, S1 and S2 proteins were found when samples were segregated according to time T1 after infection, seroprevalence at T1, sex and age of HWs and symptoms at infection. We found that IgM + samples had higher titers of IgG against N antigen and IgA against S1 and S2 antigens than IgM - samples. There were significant correlations between anti-S1 and S2 Abs. Interestingly, IgM + patients with dyspnea had lower titers of IgG and IgA against N, S1 and S2 than those without dyspnea. Comparing T1 and T2, we found that IgA against N, S1 and S2 but only IgG against certain Ag decreased significantly. In conclusion, an association was established between Ab titers and the development of infection symptoms.

The emergence of coronavirus disease 2019 (COVID-19) as a global health emergency necessitates continued investigation of the disease progression. This study investigated the relationship between eosinophilia and the severity of COVID-19 in chronic obstructive pulmonary disease (COPD) patients.

This cross-sectional study was conducted on 73 COPD patients infected by COVID-19 in Afzalipour Hospital, Iran. Peripheral blood samples were collected for hematological parameter testing, including eosinophil percentage, using Giemsa staining. Eosinophilia was defined as≥ 2% and non-eosinophilia as< 2%. The severity of pulmonary involvement was determined based on chest CT severity score (CT-SS) (based on the degree of involvement of the lung lobes, 0%: 0 points, 1-25%: 1 point, 26-50%: 2 points, 51-75%: 3 points, and 76-100%: 4 points). The CT-SS was the sum of the scores of the five lobes (range 0-20).

The average age of patients was 67.90±13.71 years, and most were male (54.8%). Non-eosinophilic COPD patients were associated with more severe COVID-19 (P= 0.01) and lower oxygen saturation (P= 0.001). In addition, the study revealed a significant difference in the chest CT severity score (CT-SS) between non-eosinophilic (9.76±0.7) and eosinophilic COPD patients (6.26±0.63) (P< 0.001). Although non-eosinophilic COPD patients had a higher mortality rate, this difference was not statistically significant (P= 0.16).

Our study demonstrated that reduced peripheral blood eosinophil levels in COPD patients with COVID-19 correlate with unfavorable outcomes. Understanding this association can help us identify high-risk COPD patients and take appropriate management strategies to improve their prognosis.

To develop a mortality risk score for COVID-19 patients admitted to intensive care units (ICU), and to compare it with other existing scores.

This retrospective observational study included consecutive adult patients with laboratory-confirmed COVID-19 admitted to ICUs of 18 hospitals from nine Brazilian cities, from September 2021 to July 2022. Potential predictors were selected based on the literature review. Generalized Additive Models were used to examine outcomes and predictors. LASSO regression was used to derive the mortality score.

From 558 patients, median age was 69 years (IQR 58-78), 56.3 % were men, 19.7 % required mechanical ventilation (MV), and 44.8 % died. The final model comprised six variables: age, pO2/FiO2, respiratory function (respiratory rate or if in MV), chronic obstructive pulmonary disease, and obesity. The AB2CO had an AUROC of 0.781 (95 % CI 0.744 to 0.819), good overall performance (Brier score = 0.191) and an excellent calibration (slope = 1.063, intercept = 0.015, p-value = 0.834). The model was compared with other scores and displayed better discrimination ability than the majority of them.

The AB2CO score is a fast and easy tool to be used upon ICU admission.

Background: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease worldwide. Obesity has been proven to increase the susceptibility of an individual to infections, but the relationship between obesity and COVID-19 is still unclear. This study aimed to conduct a systematic review and meta-analysis of the prevalence of obesity and its effects in patients with COVID-19. Methods: Web of Science, PubMed and Embase were searched for English language studies up to May 22, 2020. We used a random or fixed-effects model to calculate pooled prevalence rates and odds ratio (OR) with 95% confidence intervals (CI). Results: Twelve studies with a total of 14 364 patients met the inclusion criteria. The pooled prevalence of obesity in patients with COVID-19 was 32.0% (95% CI, 26%-38%, P < .001). The prevalence of obesity in ICU COVID-19 patients were 37.0% (95% CI, 29%-46%, P < .001). Comparing between obese and non-obese patients, the meta-analysis showed that obesity was an important risk factor associated with COVID-19 patients needed for ICU care (OR: 1.36, 95% CI 1.22-1.52, P < .001). Conclusion: Obesity was highly prevalent (32.0%) in patients with COVID-19, especially in ICU patients (37.0%), and was an important risk factor for COVID-19 patients needed for ICU care.

Cigarette smoking remains one of the leading causes of preventable death worldwide. A worldwide study by the World Health Organization concluded that more than 8 million people die every year from smoking, tobacco consumption, and secondhand smoke. The most effective tobacco cessation programs require personalized human intervention combined with costly pharmaceutical supplementation, making them unaffordable or inaccessible to most tobacco users. Thus, digital interventions offer a promising alternative to these traditional methods. However, the leading smartphone apps available in the market today have either not been studied in a clinical setting or are unable to match the smoking cessation success rates of their expensive offline counterparts. We would like to understand whether QuitSure, a novel smoking cessation app built by Rapidkart Online Private Limited, is able to bridge this efficacy gap and deliver affordable and effective smoking cessation at scale.

Our objective was to do an initial exploration into the engagement, efficacy, and safety of QuitSure based on the self-reported experiences of its users. Outcomes measured were program completion, the effect of program completion on smoking behavior, including self-reported cessation outcomes, and negative health events from using the app.

All QuitSure registered users who created their accounts on the QuitSure app between April 1, 2021, and February 28, 2022, were sent an anonymized web-based survey. The survey results were added to their engagement data on the app to evaluate the feasibility and efficacy of the app as a smoking cessation intervention. The data were analyzed using descriptive statistics (frequencies and percentages) and the χ2 test of independence.

In total, 1299 users who had completed the QuitSure program submitted the survey and satisfied the inclusion criteria of the study. Of these, 1286 participants had completed the program more than 30 days before filling out the survey, and 1040 (80.1%, 95% CI 79.1%-82.6%) of them had maintained prolonged abstinence for at least 30 days after program completion. A majority of participants (770/891, 86.4%) who were still maintaining abstinence at the time of submitting the survey did not experience any severe nicotine withdrawal symptoms, while 41.9% (373/891) experienced no mild withdrawal symptoms either. Smoking quantity prior to completing the program significantly affected quit rates (P<.001), with heavy smokers (>20 cigarettes per day) having a lower 30-day prolonged abstinence rate (relative risk=0.91; 95% CI 90.0%-96.2%) compared to lighter smokers. No additional adverse events outside of known nicotine withdrawal symptoms were reported.

The nature of web-based surveys and cohort selection allows for extensive unknown biases. However, the efficacy rates of survey respondents who completed the program were high and provide a case for further investigation in the form of randomized controlled trials on the QuitSure tobacco cessation program.

The goals of this study were to develop a model that predicts the risk of 30-d all-cause readmission in hospitalized Medicaid patients diagnosed with COPD and to create a predictive model in a retrospective study of a population cohort.

We analyzed 2016-2019 Medicaid claims data from 7 United States states. A COPD admission was one in which either the admission diagnosis or the first or second clinical (discharge) diagnosis bore an International Classification of Diseases, Tenth Revision code for COPD. A readmission was an admission for any condition (not necessarily COPD) that occurred within 30 d of a COPD discharge. We estimated a mixed-effects logistic model to predict 30-d readmission from patient demographic data, comorbidities, past health care utilization, and features of the index hospitalization. We evaluated model fit graphically and measured predictive accuracy by the area under the receiver operating characteristic (ROC) curve.

Among 12,283 COPD hospitalizations contributed by 9,437 subjects, 2,534 (20.6%) were 30-d readmissions. The final model included demographics, comorbidities, claims history, admission and discharge variables, length of stay, and seasons of admission and discharge. The observed versus predicted plot showed reasonable fit, and the estimated area under the ROC curve of 0.702 was robust in sensitivity analyses.

Our model identified with acceptable accuracy hospitalized Medicaid patients with a diagnosis of COPD who are at high risk of readmission. One can use the model to develop post-discharge management interventions for reducing readmissions, for adjusting comparisons of readmission rates between sites/providers or over time, and to guide a patient-centered approach to patient care.

Background and objectives There are multiple factors and comorbid conditions that can impact the outcomes of COVID-19. This study aimed to assess how patients with certain comorbidities and risk factors were affected by COVID-19. Methodology This retrospective study involved 578 inpatients who presented to the emergency room (ER) due to COVID-19 infection, diagnosed with COVID-19 between 2020 and 2021. This research takes note of COVID-19 severity, particularly in individuals with comorbidities such as chronic obstructive pulmonary disease (COPD), diabetes mellitus (DM), chronic kidney disease (CKD), coronary artery disease (CAD), and hypertension. Results A two-sample t-test found that age was a significant factor affecting hospital length of stay (LOS) and mortality. An ANOVA analysis of race, DM, and CAD showed a significant effect on LOS (p-values = 0.005, 0.01, and 0.01, respectively) but not on mortality and intubation. White patients had an increased LOS compared to other ethnicities. CKD and hypertension significantly affect mortality and LOS. However, COPD did significantly influence all three variables: mortality, intubation, and LOS (p-values = 0.005, 0.013, and 0.01, respectively). A multiple ANOVA test showed that COPD, hypertension, and CKD had a significant effect on mortality, intubation, and LOS (p-values = 0.014, 0.004, and 0.01, respectively). DM showed weaker significance on mortality, intubation, and LOS (p-value = 0.108). Conclusions Patients with all three comorbid conditions (COPD, hypertension, and CKD) had increased length of stay, intubation, and mortality; thus, appropriate measures including close observation and early intervention may be necessary to prevent mortality in these patients.

The COVID-19 pandemic had a profound and pervasive impact on the health of chronic care patients and disrupted care systems worldwide. Our research aimed to assess the impact of the pandemic on chronic care provision and provide recommendations for improving care provision, based on patient experiences.

Qualitative semi-structured interviews were held among patients with chronic obstructive pulmonary disease (COPD) or heart failure.

Using stratified sampling, 23 patients with COPD, heart failure, or both were recruited to participate in semi-structured interviews. In the summer of 2021, online interviews were conducted.

An iterative process was adopted to analyze the data. Going back and forth through the data and our analytical structure, we first coded the data, and subsequently developed categories, themes, and aggregate dimensions. The data were synthesized in a data structure and a data table, which were analyzed using an interpretative approach.

We found 3 dimensions through which care might be improved: (1) proactive and adaptive health care organization and use of innovative technologies, (2) assistance in maintaining patient resilience and coping strategies, and (3) health care built on outreaching and person-centered care enabling identification of individual patient needs. Experiences of impaired accessibility to care, altered and unmet care demands and patient needs, and the negative impact of national containment strategies on patient resilience support the need for improvement in these dimensions.

The in-depth insight gained on the impact of the pandemic on chronic care provision was used to propose recommendations for improving care, supported by not only the what and how but also the why developments require additional efforts made by policymakers and change agents, augmented by structural use and development of innovations. Health care organizations should be enabled to rapidly respond to changing internal and external environments, develop and implement innovations, and match care to patient needs.

Solid organ transplant (SOT) recipients with COVID-19 have a higher risk of mortality than those without COVID-19. However, it is unclear how SOT patient outcomes compare to the general population without SOT who contract COVID-19.

We used the National Inpatient Sample from January to December 2020 to investigate inpatient outcomes seen in SOT recipients after contracting COVID-19 compared to nontransplant patients. We identified our study sample using ICD-10 CM and excluded those <18 years of age and those with dual organ transplants. Inpatient outcomes were compared in SOT and non-SOT COVID cohorts, and we further evaluated predictors of mortality in the SOT with COVID population.

Out of the 1,416,445 COVID-19 admissions included in the study, 8315 (0.59%) were single SOT recipients. Our analysis that adjusted for multiple baseline characteristics and comorbidities demonstrated that COVID-19 in SOT patients was associated with higher rates of acute kidney injury (adjusted odds ratio [aOR] 2.34, 95% confidence interval [CI] 1.81-3.02, P < 0.01), lower rates of acute respiratory distress syndrome (aOR 0.68, 95% CI 0.54-0.85, P < 0.01), and similar rates of cardiac arrest, pulmonary embolism, circulatory shock, cerebrovascular events, and in-hospital mortality. Age >65 was associated with mortality in SOT patients.

In this nationally representative sample, SOT patients presenting with COVID-19 experienced similar rates of mortality compared to those without SOT. SOT patients were more likely to develop acute kidney injury. Further research is needed to understand the complex relationship between transplant patient outcomes and COVID-19.

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common cause of hospital admissions. Coronavirus disease 2019 (COVID-19) has large impact on patients with pulmonary diseases. The purpose of the study is to evaluate the impact of COVID-19 on patients with AECOPD.

Retrospective study with two cohorts, the first period included patients with AECOPD before COVID-19 pandemic; the second period included patients with AECOPD since the beginning of COVID-19 pandemic. The length of stay (LOS), number of patients requiring mechanical ventilation, and allcause mortality were calculated.

There was a total of 55 (44.72%) patients in the pre-COVID period compared to 68 (55.28%) patients in the COVID period. In the pre-COVID period: 14 (19.44%) had hypertension, 26(36.11%) had diabetes, 27(37.50%) had ischemic heart disease, 3(4.17%) had myocardial infarction; in the COVID period: 20 (29.41%) had hypertension, 24(35.29%) had diabetes, 27(39.71%) had ischemic heart disease, 1(1.47) had myocardial infarction. The LOS was shorter in pre-COVID period compared to COVID period, 6.51(SD 5.02) days vs 8.91(SD7.88) days with P-value of 0.042 respectively. The total number of patients needing mechanical ventilation in pre-COVID period was similar to the COVID period with P-value of 0.555. All-cause mortality number was 2 (3.64%) in the pre-COVID period compared to 6 (8.82%) in COVID period with P-value of 0.217.

Study results revealed significant difference in length of stay for patients with AECOPD, patient in COVID period had increased LOS compared to pre-COVID period. There was no significant difference in the other parameters.

To determine the prevalence of COVID-19 and the characteristics of infected patients, as well as the prevalence of mental disorders associated with the infection and the associated risk factors. Secondary: to know the prevalence of the long COVID syndrome and the characteristics of this cohort.

Incidence study of mental disorder in patients diagnosed with COVID-19 and case-control study of long COVID syndrome in the subsample of patients diagnosed with COVID-19 without a history of mental disorder. SITE: Primary care setting in Lleida.

The 46,258 patients diagnosed of COVID-19 without a history of mental disorder were followed for 2 years.

The dependent variable was the mental disorder in the period 03/11/2020 to 03/11/2022; and the independent variables were clinical and social variables. Its association with mental disorder was analyzed by calculating the adjusted hazard ratio using a logistic regression model.

The average age of 46,258 patients at the beginning of the study was 43±17.9 years. 47% were women. The mental disorder rate for all period was 3.46% (59.20% anxiety). A predictive score was elaborated. The long COVID syndrome was more common in older women, without toxic habits, with obesity and associated comorbidity.

COVID-19 has had an impact on the mental health of patients. Knowing the risk factors for developing these mental disorders and the long COVID syndrome would allow the clinician to be able to identify patients at risk in order to establish preventive measures and avoid their appearance.

Amidst the COVID-19 pandemic, vaccination has been a crucial strategy for mitigating transmission and disease severity. However, vaccine-effectiveness may be influenced by various factors, including booster vaccination, as well as personal factors such as age, sex, BMI, smoking, and comorbidities. To investigate the potential effects of these factors on SARS-CoV-2 infection and disease severity, we analyzed data from the third round of the Cologne Corona Surveillance (CoCoS) project, a large cross-sectional survey.

The study was conducted mid-February to mid-March 2022 in Cologne, Germany. A random sample of 10,000 residents aged 18 years and older were invited to participate in an online survey. Information on participants' demographics (age, sex), SARS-CoV-2 infections, vaccination status, smoking, and preexisting medical conditions were collected. The outcomes of the study were: (1) the occurrence of SARS-CoV-2 infection despite vaccination (breakthrough infection) and (2) the occurrence of moderate-to-severe disease as a result of a breakthrough infection. Cox proportional-hazards regression was used to investigate possible associations between the presence/absence of booster vaccination, personal factors and the occurrence of SARS-CoV-2 infection. Associations with moderate-to-severe infection were analyzed using the Fine and Gray subdistribution hazard model.

A sample of 2,991 residents responded to the questionnaire. A total of 2,623 primary immunized participants were included in the analysis of breakthrough infection and 2,618 in the analysis of SARS-CoV-2 infection severity after exclusions due to incomplete data. The multivariable results show that booster vaccination (HR = 0.613, 95%CI 0.415-0.823) and older age (HR = 0.974, 95%CI 0.966-0.981) were associated with a reduced hazard of breakthrough infection. Regarding the severity of breakthrough infection, older age was associated with a lower risk of moderate-to-severe breakthrough infection (HR = 0.962, 95%CI0.949-0.977). Female sex (HR = 2.570, 95%CI1.435-4.603), smoking (HR = 1.965, 95%CI1.147-3.367) and the presence of chronic lung disease (HR = 2.826, 95%CI1.465-5.450) were associated with an increased hazard of moderate-to-severe breakthrough infection.

The results provide a first indication of which factors may be associated with SARS-CoV-2 breakthrough infection and moderate-to-severe course of infection despite vaccination. However, the retrospective nature of the study and risk of bias in the reporting of breakthrough infection severity limit the strength of the results.

DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046, Registered on 25 February 2021.

Patients with chronic obstructive pulmonary disease (COPD) who are hospitalized are more likely to die from their illness and have increased likelihood of re-admission than those who are not. Subsequent re-admissions further increase the burden on healthcare systems. This study compared inpatient admission rates and time-to-first COPD-related inpatient admission among Medicare beneficiaries with COPD indexed on umeclidinium/vilanterol (UMEC/VI) versus tiotropium (TIO).

This retrospective study used the All-Payer Claims Database to investigate hospital admission and re-admission outcomes in Medicare beneficiaries with COPD with an initial pharmacy claim for UMEC/VI or TIO from 1 January 2015 to 28 February 2020. Inpatient admissions, baseline, and follow-up variables were assessed in patients indexed on UMEC/VI and TIO after propensity score matching (PSM), with time-to-first on-treatment COPD-related inpatient admission as the primary endpoint. Re-admissions were assessed among patients with a COPD-related inpatient admission in the 30- and 90-days post-discharge.

Post-PSM, 7152 patients indexed on UMEC/VI and 7069 on TIO were eligible for admissions analysis. The mean (standard deviation [SD]) time-to-first COPD-related inpatient admission was 46.71 (87.99) days for patients indexed on UMEC/VI and 44.96 (85.90) days for those on TIO (p=0.06). The mean (SD) number of inpatient admissions per patient was 1.24 (2.92) for patients indexed on UMEC/VI and 1.26 (3.05) for those on TIO (p=0.49). Proportion of patients undergoing re-admissions was similar between treatments over both 30 and 90 days, excluding a significantly lower proportion of patients indexed on UMEC/VI than those indexed on TIO for COPD-related re-admissions for hospital stays of 4-7 days and 7-14 days, and all-cause re-admissions for stays of 4-7 days.

Patients with COPD using Medicare in the US and receiving UMEC/VI or TIO reported similar time-to-first inpatient admission and similar proportion of re-admissions.