Prognostic significance of lung diffusion capacity and spirometric parameters in relation to hemodynamic status in heart transplant candidates

Introduction: Investigations have described a correlation between the severity of heart failure and the severity of pulmonary function abnormalities. In this study, we investigated the association of resting spirometric parameters, lung diffusion for carbon monoxide (DLCO), and the transfer coefficient (KCO) with hemodynamic variables and outcomes in a cohort of heart transplant candidates. Material and methods: Between January 2018 and January 2020, a total of 100 patients with advanced heart failure who were scheduled for right heart catheterization (RHC) as a pre-transplant evaluation measure were enrolled. Spirometry and DLCO were performed in all patients within 24 hours of their RHC. All selected patients were followed for a median (IQR) time of 6 (2–12) months. The end points of interest were heart failure-related mortality and a combined event involving HF-related mortality, heart transplantation (HTX), and need for the placement of a left ventricular assist device (LVAD).Results: Among 846 patients scheduled for RHC, a total of 100 patients (25% female) with a mean (SD) age of 38.5 (12.8) were enrolled. There was a significant correlation between FEV1/FVC and CVP (r = –0.22, p = 0.02), PCWP (r = –0.4, p < 0.001), mPAP (r = –0.45, p < 0.001), and PVR (r = –0.32, p = 0.001). The cardiac output correlated with DLCO (r = 0.3, p = 0.008). Spirometry parameters, DLCO parameters, and hemodynamic parameters did not correlate with the combined event. Among the several variables, only PVR had an independent association with the combined event.Conclusion: Both mechanical and gas diffusion parameters of the lung were not associated with outcomes in the homogeneous group of heart transplant candidates

Changes in heart rate variability (HRV) in patients with severe and moderate obstructive sleep apnea before and after acute CPAP therapy during nocturnal polysomnography

Introduction: Obstructive sleep apnea is an important risk factor for cardiovascular disease. Noninvasive positive pressure ventilation is the standard treatment of this disease, and it can reduce mortality in patients. Dysfunction of the autonomic system is one of the reasons for an increased risk of cardiovascular disease in these patients. The purpose of the present study was to investigate the effect of positive airway pressure (PAP) therapy on heart rate variability (HRV) indices. Methods: The study population was comprised of 55 patients, who underwent nocturnal polysomnography for the diagnosis of obstructive sleep apnea and PAP titration on the same night. The levels of continuous positive airway pressure (CPAP) and bilevel positive airway pressure were adjusted to relieve obstructive sleep apnea, hypopnea, and desaturation. The patients’ heart changes and cardiac characteristics were recorded before and after the start of routine CPAP therapy. Finally, the cases’ sleep and polysomnography tests were analyzed and interpreted in collaboration with a sleep specialist and their cardiac changes with the aid of a cardiologist before and after treatment with CPAP. Results: The participants were 55 patients at a mean age of 57.04±12.9 years. There were 34 (61.8%) male and 21 (38.2%) female cases. PAP therapy on the same night resulted in a decreased standard deviation of the N-N interval index (p=0.036) and a low-frequency index (p=0.021), as well as increased high-frequency index (p<0.001) and low frequency / high frequency ratios (p=0.008). Conclusion: Our findings indicate a relative improvement in the activity of the autonomic system in patients with obstructive sleep apnea after 1 night of PAP therapy. Overwhelming evidence suggests that improvement in the sympathetic balance can reduce the risk of cardiovascular disease in patients

Prognostic Significance of Lung Diffusion Capacity and Spirometric Parameters in Relation to Hemodynamic Status in Heart Transplant Candidates

Introduction: Investigations have described a correlation between the severity of heart failure and the severity of pulmonary function abnormalities. In this study, we investigated the association of resting spirometric parameters, lung diffusion for carbon monoxide (DLCO), and the transfer coefficient (KCO) with hemodynamic variables and outcomes in a cohort of heart transplant candidates. Material and methods: Between January 2018 and January 2020, a total of 100 patients with advanced heart failure who were scheduled for right heart catheterization (RHC) as a pre-transplant evaluation measure were enrolled. Spirometry and DLCO were performed in all patients within 24 h of their RHC. All selected patients were followed for a median (IQR) time of 6 (2–12) months. The end points of interest were heart failure-related mortality and a combined event involving HF-related mortality, heart transplantation (HTX), and need for the placement of a left ventricular assist device (LVAD). Results: Among 846 patients scheduled for RHC, a total of 100 patients (25% female) with a mean (SD) age of 38.5 (12.8) were enrolled. There was a significant correlation between FEV1/FVC and CVP (ρ = –0.22, p = 0.02), PCWP (ρ = –0.4, p &lt; 0.001), mPAP (ρ = –0.45, p &lt; 0.001), and PVR (ρ = –0.32, p = 0.001). The cardiac output correlated with DLCO (ρ = 0.3, p = 0.008). Spirometry parameters, DLCO parameters, and hemodynamic parameters did not correlate with the combined event. Among the several variables, only PVR had an independent association with the combined event. Conclusion: Both mechanical and gas diffusion parameters of the lung were not associated with outcomes in the homogeneous group of heart transplant candidates

Comparative Network Analysis of Patients with Non-Small Cell Lung Cancer and Smokers for Representing Potential Therapeutic Targets

Abstract Cigarette smoking is the leading cause of lung cancer worldwide. In this study, we evaluated the serum autoantibody (AAb) repertoires of non-small cell lung cancer (NSCLC) patients and smokers (SM), leading to the identification of overactivated pathways and hubs involved in the pathogenesis of NSCLC. Surface- and solution-phase biopanning were performed on immunoglobulin G purified from the sera of NSCLC and SM groups. In total, 20 NSCLC- and 12 SM-specific peptides were detected, which were used to generate NSCLC and SM protein datasets. NSCLC- and SM-related proteins were visualized using STRING and Gephi, and their modules were analyzed using Enrichr. By integrating the overrepresented pathways such as pathways in cancer, epithelial growth factor receptor, c-Met, interleukin-4 (IL-4) and IL-6 signaling pathways, along with a set of proteins (e.g. phospholipase D (PLD), IL-4 receptor, IL-17 receptor, laminins, collagens, and mucins) into the PLD pathway and inflammatory cytokines network as the most critical events in both groups, two super networks were made to elucidate new aspects of NSCLC pathogenesis and to determine the influence of cigarette smoking on tumour formation. Taken together, assessment of the AAb repertoires using a systems biology approach can delineate the hidden events involved in various disorders

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundEstimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.Methods22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.FindingsGlobal all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.InterpretationGlobal adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic