Risk of temperature, humidity and concentrations of air pollutants on the hospitalization of AECOPD

Time series analysis of the interaction between ambient temperature and air pollution on hospitalizations for AECOPD in Ganzhou, China

This study aimed to investigate the univariate and bivariate effects of ambient temperature and air pollutants on 57,251 inpatients with AECOPD (Acute Exacerbation of Chronic Obstructive Pulmonary Disease) in Ganzhou from January 1, 2016, to December 31, 2019. We categorized the daily mean temperature and air pollutant variables based on the exposure-response curve of the Distributed Lag Non-Linear Model. Poisson regression model was used for interaction and stratification analysis. The Relative Excess Risk due to Interaction (RERI) with 95% confidence intervals (95% CI) between daily mean temperature (Tmean) and air pollutants including NO2, PM2.5, and PM10 were - 0.428 (95% CI - 0.637, - 0.218), -- 0.227 (95% CI - 0.293, - 0.161), and - 0.119 (95% CI - 0.159, - 0.079). Further stratification analysis showed the relative risk (RR) (95% CI) of high NO2 (> 33 μg/m3) at low Tmean (≤ 28 °C) was 1.119 (95% CI 1.096, 1.142). Low temperatures with high PM10 in men and high PM2.5 in women were associated with a higher risk of AECOPD hospitalization. The results indicate a higher risk of hospitalization for AECOPD when there is with high concentrations of air pollution at low temperatures.

Effects of ambient temperature and humidity on COPD mortality in Ganzhou city, China

This study used the time series data of Ganzhou city to explore the individual and interaction effects of temperature and humidity on COPD death, and identify vulnerable subgroups of the population. We collected daily COPD mortality and meteorological data in Ganzhou from 2016 to 2019. The nonlinear distribution lag model was used to examine the associations and interaction between daily mean temperature and humidity and COPD mortality. For the total population, male and 65 years old or above, the relative risk (RR) for COPD mortality could be significant at extremely low temperature (3.3 ℃), reaching 1.799 (95% confidence interval [CI]: 1.216, 2.662), 1.894 (95% CI: 1.164, 3.084) and 1.779 (95% CI:1.185, 2.670). Also, at extremely low humidity (47.8%), the risk reached 1.888 (95% CI: 1.217, 2.930), 1.837 (95% CI: 1.066, 3.165) and 2.166 (95% CI: 1.375, 3.414). The cumulative COPD death risk for females was 3.524 (95% CI: 1.340, 9.267) at high temperature (30.7 ℃), 1.953(95% CI: 1.036, 3.683) at low humidity (47.8%) and 1.726 (95% CI: 1.048, 2.845) at high humidity (96.7%). For the total COPD deaths and subgroups, the interaction effects between daily temperature and humidity were not significant (p > 0.05). Both extremely low temperature and low humidity increased the risk of COPD death in Ganzhou city, especially for males and people over 65 years old. Females were more sensitive to extremely high temperature and humidity. Patients with COPD should pay attention to self-protection under extreme temperature and humidity weather conditions.

Prediction of air pollutant concentrations based on the long short-term memory neural network

In recent years, environmental problems caused by air pollutants have received increasing attention. Effective prediction of air pollutant concentrations is an important way to protect the public from harm. Recently, due to extreme climate and social development, the forest fire frequency has increased. During the biomass combustion process caused by forest fires, the content of particulate matter (PM) in the atmosphere increases significantly. However, most existing air pollutant concentration prediction methods do not consider the considerable impact of forest fires, and effective long-term prediction models have not been established to provide early warnings for harmful gases. Therefore, in this paper, we collected a daily air quality data set (aerodynamic diameter smaller than 2.5 µm, PM2.5) for Heilongjiang Province, China, from 2017 to 2023 and A novel Long Short-Term Memory (LSTM) model was proposed to effectively predict the situation of air pollutants. The model could automatically extract information of the effective time step from the historical data set and combine forest fire disturbance and climate data as auxiliary data to improve the model prediction ability. Moreover, we created artificial neural network (ANN) and permissive regression (support vector machine, SVR) models for comparative experiments. The results showed that the precision accuracy of the developed LSTM model is higher. Unlike the other models, the LSTM neural network model could effectively predict the concentration of air pollutants in long-term series. Regarding long-term observation missions (7 days), the proposed model performed well and stably, with R2 reaching over 88%.

Effect of Ambient Temperature on Hospital Admissions for Respiratory Disease in Suburban Rural Villages of a Semi-Arid Region in Northwest China

OBJECTIVE

This study evaluated the effects of extreme temperatures on hospital admissions for respiratory diseases (RDs) in a semi-arid region in the Northwest of China.

METHODS

Distributed lag nonlinear model was constructed, and stratified analysis by gender and age was performed.

RESULTS

The exposure-response curve between temperature and RD hospital admissions was almost W-shaped. Either extremely cold temperatures or moderately cold temperatures presented a short-term acute harmful effect, and the relative risks were higher among males (1.976, 95% confidence interval [CI]: 1.773-2.203; 1.242, 95% CI: 1.203-1.282) and the elderly (2.363, 95% CI: 1.724-3.240; 1.267, 95% CI: 1.154-1.390). Both extreme and moderately hot temperatures had higher risks among females (2.040, 95% CI: 1.815-2.292; 1.328, 95% CI: 1.276-1.381).

CONCLUSIONS

The relationship between air temperature and RD hospital admissions was nonlinear. Vulnerable populations varied according to extreme temperature conditions.

Effect of particulate matter (PM2.5 and PM10) on health indicators: climate change scenarios in a Brazilian metropolis

Recife is recognized as the 16th most vulnerable city to climate change in the world. In addition, the city has levels of air pollutants above the new limits proposed by the World Health Organization (WHO) in 2021. In this sense, the present study had two main objectives: (1) To evaluate the health (and economic) benefits related to the reduction in mean annual concentrations of PM₁₀ and PM_2.5 considering the new limits recommended by the WHO: 15 µg/m³ (PM₁₀) and 5 µg/m³ (PM_2.5) and (2) To simulate the behavior of these pollutants in scenarios with increased temperature (2 and 4 °C) using machine learning. The averages of PM_2.5 and PM₁₀ were above the limits recommended by the WHO. The scenario simulating the reduction in these pollutants below the new WHO limits would avoid more than 130 deaths and 84 hospital admissions for respiratory or cardiovascular problems. This represents a gain of 15.2 months in life expectancy and a cost of almost 160 million dollars. Regarding the simulated temperature increase, the most conservative (+ 2 °C) and most drastic (+ 4 °C) scenarios predict an increase of approximately 6.5 and 15%, respectively, in the concentrations of PM_2.5 and PM₁₀, with a progressive increase in deaths attributed to air pollution. The study shows that the increase in temperature will have impacts on air particulate matter and health outcomes. Climate change mitigation and pollution control policies must be implemented for meeting new WHO air quality standards which may have health benefits.

Associations between air pollutants and hospital admissions for chronic obstructive pulmonary disease in Jinan: potential benefits from air quality improvements

Evidence between air pollution and chronic obstructive pulmonary disease (COPD) is inconsistent and limited in China. In this study, we aim to examine the associations between air pollutants and hospital admissions for COPD, hoping to provide practical advice for prevention and control of COPD. Hospital admissions for COPD were collected from a Grade-A tertiary hospital in Jinan from 2014 to 2020. A generalized additive model (GAM) was used to examine the associations between air pollutants and hospital admissions for COPD. Stratified analysis was also conducted for gender, age (20-74 and ≥75 years), and season (warm and cold). The avoidable number of COPD hospital admissions was calculated when air pollutants were controlled under national and WHO standards. Over the study period, a total of 4,012 hospital admissions for COPD were recorded. The daily hospital admissions of COPD increased by 2.36% (95%CI: 0.13-4.65%) and 2.39% (95%CI: 0.19-4.65%) for per 10 μg/m³ increase of NO₂ and SO₂ concentrations at lag2, respectively. There was no statistically significant difference in health effects caused by increased concentrations of PM_2.5, PM₁₀, CO, and O₃. The health effects of increased SO₂ concentration were stronger in women, the ≥75 years old people and the cold season. About 2 (95%CI: 0-3), 64 (95%CI: 4-132) and 86 (95%CI: 6-177) COPD admissions would be avoided when the SO₂ concentration was controlled below the NAAQS-II (150 μg/m³), NAAQS-I (50 μg/m³), and WHO's AQG2021 standard (40 μg/m³), respectively. These findings suggest that short-term exposure to NO₂ and SO₂ was associated with increased risks of daily COPD admissions, especially for females and the elderly. The control of SO₂ and NO₂ under the national and WHO standards could avoid more COPD admissions and obtain greater health benefits.

Association between ambient PM2.5 and outpatient visits of children's respiratory diseases in a megacity in Central China

Objective

To explore the relationship between ambient PM_2.5 level and outpatient visits of children with respiratory diseases in a megacity, Zhengzhou, in central China.

Methods

We collected daily outpatient visit data, air pollutant data, and meteorological data at the monitoring points of Zhengzhou from the time period 2018 to 2020 and used Spearman's rank correlation to analyze the correlation between children's respiratory outpatient visits and air pollutants and meteorological factors. Generalized additive models were used to analyze the association between PM_2.5 exposures and children's respiratory outpatient visits. A stratified analysis was further carried out for the seasons.

Results

From 2018 to 2020, the total number of outpatients with children's respiratory diseases was 79,1107, and the annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃-8h in Zhengzhou were respectively 59.48 μg/m³, 111.12 μg/m³, 11.10 μg/m³, 47.77 μg/m³, 0.90 mg/m³ and 108.81 μg/m³. The single-pollutant model showed that the risk of outpatient visits for children with respiratory disease increased by 0.341% (95%CI: 0.274-0.407%), 0.532% (95%CI: 0.455-0.609%) and 0.233% (95%CI: 0.177-0.289%) for every 10 μg/m³ increase in PM_2.5 with a 3-day lag, 1-day lag, and 1-day lag respectively for the whole year, heating period, and non-heating period. The multi-pollutant model showed that the risk of PM_2.5 on children's respiratory disease visits was robust. The excess risk of PM_2.5 on children's respiratory disease visits increased by 0.220% (95%CI: 0.147-0.294%) when SO₂ was adjusted. However, the PM_2.5 effects were stronger during the heating period than during the non-heating period.

Conclusion

The short-term exposure to PM_2.5 was significantly associated with outpatient visits for children's respiratory diseases. It is therefore necessary to strengthen the control of air pollution so as to protect children's health.

The Effects of Ambient Temperature on Lumbar Disc Herniation: A Retrospective Study

Purpose

This article was designed to provide critical evidence into the relationship between ambient temperature and intensity of back pain in people with lumbar disc herniation (LDH).

Methods

Data concerning patient's age, gender, diagnostic logout, admission time, discharge time, residence area, and work area (residence area and work area were used to ensure research area) from 2017 to 2019 were obtained from the Neck-Shoulder and Lumbocrural Pain Hospital in Jinan, China. A total of 1,450 hospitalization records were collected in total. The distributed lag non-linear model (DLNM) was used to evaluate the relationship between lag–response and exposure to ambient temperature. Stratification was based on age and gender. Days 1, 5, 20, and 28 prior to admission were denoted as lags 0, 5, 20, and 28, respectively.

Results

An average daily temperature of 15–23°C reduced the risk of hospitalization the most in men. Conversely, temperatures <10°C drastically increased hospitalization in men, particularly in lags 0–5 and lags 20–28. Men aged between 40 and 50 years old showed less effect in pain sensation during ambient temperature.

Conclusion

High or low ambient temperature can increase the hospitalization risk of LDH, and sometimes, the temperature effect is delayed.

Air Pollution’s Impact on Cardiac Remodeling in an Experimental Model of Chagas Cardiomyopathy

Background

Chagas disease is characterized by intense myocardial fibrosis stimulated by the exacerbated production of inflammatory cytokines, oxidative stress, and apoptosis. Air pollution is a serious public health problem and also follows this same path. Therefore, air pollution might amplify the inflammatory response of Chagas disease and increase myocardial fibrosis.

Methods

We studied groups of Trypanosoma cruzi infected Sirius hamsters (Chagas=CH and Chagas exposed to pollution=CH+P) and 2 control groups (control healthy animals=CT and control exposed to pollution=CT+P). We evaluated acute phase (60 days post infection) and chronic phase (10 months). Echocardiograms were performed to assess left ventricular systolic and diastolic diameter, in addition to ejection fraction. Interstitial collagen was measured by morphometry in picrosirius red staining tissue. The evaluation of inflammation was performed by gene and protein expression of cytokines IL10, IFN-γ, and TNF; oxidative stress was quantified by gene expression of NOX1, MnSOD, and iNOS and by analysis of reactive oxygen species; and apoptosis was performed by gene expression of BCL2 and Capsase3, in addition to TUNEL analysis.

Results

Chagas groups had increased collagen deposition mainly in the acute phase, but air pollution did not increase this deposition. Also, Chagas groups had lower ejection fraction in the acute phase (p = 0.002) and again air pollution did not worsen ventricular function or dilation. The analysis of the inflammation and oxidative stress pathways were also not amplified by air pollution. Apoptosis analysis showed increased expression of BCL2 and Caspase3 genes in chagasic groups in the acute phase, with a marginal p of 0.054 in BCL2 expression among infected groups, and TUNEL technique showed amplified of apoptotic cells by pollution among infected groups.

Conclusions

A possible modulation of the apoptotic pathway was observed, inferring interference from air pollution in this pathway. However, it was not enough to promote a greater collagen deposition, or worsening ventricular function or dilation caused by air pollution in this model of Chagas cardiomyopathy.

Association between air pollution and hospital admissions for chronic respiratory disease in people aged over 65 years: a time series analysis in Ningbo, China, 2015-2017

PURPOSE

To provide essential information of environmental triggers leading to CRD.

METHODS

We investigated the short-term effects of ambient air pollutants on CRD-related hospitalizations in people aged ≥ 65 years in Ningbo. Data on 23,610 cases of CRD requiring hospitalization were collected from January 2015 to August 2017. After adjusting for temporal trends, seasonality, meteorological conditions, day of week (DOW), and public holidays, we used generalized additive Poisson distribution models to calculate the excess risks (ERs) and 95% confidence intervals (95% CIs) of CRD related hospitalizations.

RESULTS

Our results showed that fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) were associated with CRD-related hospitalizations in people aged ≥ 65 years. We observed that each 10 μg/m³ increase (except for each 0.1 mg/m³ increase in CO) in the concentration of air pollutants, the percentage of CRD-related hospitalizations due to PM_2.5, PM₁₀, and SO₂ exposure at lag 07, NO₂ exposure at lag 03, and CO exposure at lag 0 increased by 2.13% (95% CI: 0.55%, 3.74%), 1.76% (95% CI: 0.70%, 2.83%), 8.24% (95% CI: 0.92%, 16.09%), 2.16% (95% CI: 0.26%, 4.05%), and 1.19% (95% CI: 0.26%, 2.12%), respectively. In addition, we found stronger effects of particulate matter in 75-84 years age group, on warmer days, and in asthmatics.

CONCLUSION

In conclusion, air pollution may have adverse effects on CRD-related hospitalizations among people aged ≥ 65 years in Ningbo. Therefore, public health measures should be taken to improve air quality.

Effect of high-level fine particulate matter and its interaction with meteorological factors on AECOPD in Shijiazhuang, China

Epidemiological evidence of the effect of high-level air pollution and its interaction with meteorological factors on the risk of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is limited. Daily data on AECOPD cases, air pollutants and meteorological factors were collected from 2015 to 2018 in Shijiazhuang. A distributed lag non-linear model (DLNM) was used to explore the lag and cumulative effect of PM_2.5 on the risk of AECOPD. The effect of the interaction between PM_2.5 and meteorological factors on AECOPD was estimated by a generalized additive model (GAM) and a stratification model. A total of 4766 patients with AECOPD were enrolled. After controlling for confounders, each 10 μg/m³ increase in PM_2.5 led to a 5.8% increase in the risk of AECOPD on day lag 0. The cumulative effect of PM_2.5 on AECOPD risk showed an increasing trend after 3 days. Similar results were observed in both smoking and non-smoking patients. There was an interaction between PM_2.5 and meteorological factors, and the risk of AECOPD was higher in cold and lower humidity conditions than in other conditions. High-level PM_2.5 exposure is positively associated with the risk of AECOPD onset, and the effect of PM_2.5 can be modified by the temperature and relative humidity. Public health guidelines should pay close attention to AECOPD risk under the condition of high-level PM_2.5 with low temperature or low humidity.

Role of air pollutants in airway epithelial barrier dysfunction in asthma and COPD

Chronic exposure to environmental pollutants is a major contributor to the development and progression of obstructive airway diseases, including asthma and COPD. Understanding the mechanisms underlying the development of obstructive lung diseases upon exposure to inhaled pollutants will lead to novel insights into the pathogenesis, prevention and treatment of these diseases. The respiratory epithelial lining forms a robust physicochemical barrier protecting the body from inhaled toxic particles and pathogens. Inhalation of airborne particles and gases may impair airway epithelial barrier function and subsequently lead to exaggerated inflammatory responses and airway remodelling, which are key features of asthma and COPD. In addition, air pollutant-induced airway epithelial barrier dysfunction may increase susceptibility to respiratory infections, thereby increasing the risk of exacerbations and thus triggering further inflammation. In this review, we discuss the molecular and immunological mechanisms involved in physical barrier disruption induced by major airborne pollutants and outline their implications in the pathogenesis of asthma and COPD. We further discuss the link between these pollutants and changes in the lung microbiome as a potential factor for aggravating airway diseases. Understanding these mechanisms may lead to identification of novel targets for therapeutic intervention to restore airway epithelial integrity in asthma and COPD.

Exposure to air pollution induces airway epithelial barrier dysfunction through several mechanisms including increased oxidative stress, exaggerated cytokine responses and impaired host defence, which contributes to development of asthma and COPD. https://bit.ly/3DHL1CA

Air Pollution Exposure as a Relevant Risk Factor for Chronic Obstructive Pulmonary Disease Exacerbations in Male and Female Patients

Chronic obstructive pulmonary disease (COPD) is a multifactorial lung inflammatory disease that affects 174 million people worldwide, with a recently reported increased incidence in female patients. Patients with COPD are especially vulnerable to the detrimental effects of environmental exposures, especially from air particulate and gaseous pollutants; exposure to air pollution severely influences COPD outcomes, resulting in acute exacerbations, hospitalisations, and death. Here, a literature review of the recent work addressing air pollution-induced acute exacerbations of COPD (AECOPD) was conducted in order to determine whether sex was considered as a biological variable in these studies, and whether air pollution exposure affected patients with COPD in a sex-specific manner. It was found that, while the majority of studies enrolled both male and female patients, only a few reported results were disaggregated by sex. Most studies had a higher enrolment of male patients, only four compared AECOPD outcomes between sexes, and only one study identified sex differences in AECOPD, with females displaying higher rates. Overall, this analysis of the literature confirmed that air pollution exposure is a trigger for AECOPD hospitalisations and revealed a significant gap in the knowledge of sex-specific effects of air pollutants on COPD outcomes, highlighting the need for more studies to consider sex as a biological variable.

COVID-19 in Asia: Transmission factors, re-opening policies, and vaccination simulation

This work aims to provide insights on the COVID-19 pandemic in three prime aspects. First, we attempted to understand the association between the COVID-19 transmission rate, environmental factors (air pollution, weather, mobility), and socio-political parameters (Government Stringency Index, GSI). Second, we evaluated the efficiency of various strategies, including radical opening, intermittent lockdown, phase lift, and contact tracing, to exit the COVID-19 pandemic and get back to pre-pandemic conditions using a stochastic individual-based epidemiology model. Third, we used a deep learning approach and simulated the vaccination rate and the time for reaching herd immunity. The analysis was done based on the collected data from eight countries in Asia, including Iran, Turkey, India, Saudi Arabia, United Arab Emirates, the Philippines, South Korea, and Russia (as a transcontinental country). Our findings in the first part highlighted a noninfluential impact from the weather-driven parameters and short-term exposure to pollutants on the transmission rate; however, long-term exposure could potentially increase the risk of COVID-19 mortality rates (based on 1998-2017 p.m.2.5 data). Mobility was highly correlated with the COVID-19 transmission and based on our causal analysis reducing mobility could curb the COVID-19 transmission rate with a 6-day lag time (on average). Secondly, among all the tested policies for exiting the COVID-19 pandemic, the contact tracing was the most efficient if executed correctly. With a 2-day delay in tracing the virus hosts, a 60% successful host tracing, and a 70% contact reduction with the hosts, a pandemic will end in a year without overburdening a healthcare system with 6000 hospital beds capacity per million. Lastly, our vaccine simulations showed that the target date for achieving herd immunity significantly varied among the countries and could be delayed to October-november 2022 in countries like India and Iran (based on 60% immunized population and assuming no intermediate factors affecting the vaccination rate).

The relationship between ambient temperature and acute respiratory and cardiovascular diseases in Shenyang, China

The purpose of this study was to analyze the acute effect of ambient temperature on hospitalization due to acute exacerbation of chronic obstructive pulmonary disease (AECOPD), stroke, and myocardial infarction (MI) in Shenyang, China. We used the distributed delayed nonlinear model to evaluate the impact of ambient temperature on respiratory and cardiovascular diseases. The study population was divided into four groups: < 65 group and ≥ 65 age groups, female and male groups. The < 65 age group of AECOPD patients was more likely to be affected by high ambient temperature, while the ≥ 65 age group of AECOPD patients was more sensitive to low ambient temperature. The hospitalization risk of MI admission increased in the ≥ 65 age group at 1-8 days delay under low ambient temperature conditions.

What Are the Effects of Meteorological Factors on Exacerbations of Chronic Obstructive Pulmonary Disease?

Chronic obstructive pulmonary disease (COPD) is one of the greatest global public health challenges. Acute exacerbations of COPD lead to the accelerated deterioration of lung function, reduced quality of life, a higher number of hospitalizations, and increased mortality. The factor causing the exacerbation is usually an infectious agent, but the impact of environmental factors is being studied more thoroughly. Among them, meteorological factors are the least examined. Multiple studies have shown that lower temperatures during the cold season, as well as sudden temperature changes regardless of the season, have the most significant negative effect on patients with COPD. However, higher temperatures, especially during summer heatwaves, can also cause COPD exacerbation and it is expected that this will be an even more important health problem in the future considering climate changes. The effects of other meteorological factors on acute exacerbation of COPD, such as atmospheric pressure, solar radiation, rainfall, wind speed, and humidity are far less investigated and opposing results have been obtained in different studies. Thus, there is a need for further research in this area that would result in clinical recommendations and public health interventions that could decrease the global burden of COPD.

Associations between ambient air pollution and hospitalizations for acute exacerbation of chronic obstructive pulmonary disease in Jinhua, 2019

Most cities in China are experiencing severe air pollution due to rapid economic development and accelerated industrialization. Exposure to various air pollutants has been related to acute exacerbations of chronic obstructive pulmonary disease (AECOPD). However, less is known about the spatial association between air pollution and AECOPD hospitalizations in the Yangtze River delta (YRD) economic and industrial region. Jinhua city is located in the YRD region of East China, in the middle of Zhejiang province. For the first time, 1563 AECOPD hospitalization cases in Jinhua during 2019 were enrolled in our analysis. The spatial distribution of six pollutants (SO₂, CO, PM10, PM2.5, O₃, NO₂) and the population temporal-spatial specific air pollutant exposure levels were estimated using the ordinary Kriging model through geographic information system (GIS). Global Moran's I was used to explore the spatial association between ambient air pollutants and AECOPD hospitalizations. The Z-scores of residential SO₂, CO, PM10, PM2.5, O₃, and NO₂ levels were 31.88, 42.95, 45.90, 32.29, 52.18, and 34.59, respectively. The concentrations of six monitored pollutants and AECOPD hospitalizations showed statistically significant spatial clustering. A generalized linear model (GLM) using a Poisson distribution with the log-link function was used to construct a core model. After adjusting for potential confounders in the model, residential SO₂, NO₂ and O₃ concentrations were significantly associated with increased AECOPD hospitalizations.

Understanding the relationships between environmental factors and exacerbations of COPD

INTRODUCTION

Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with a significant health burden both for patients and healthcare systems. Exposure to various environmental factors increases the risk of exacerbations.

AREAS COVERED

We searched PubMed and assessed literature published within the last 10 years to include epidemiological evidence on the relationships between air pollution, temperature and COPD exacerbation risk as well as the implications of extreme weather events on exacerbations.

EXPERT OPINION

Ongoing climate change is expected to increase air pollution levels, global temperature and the frequency and severity of extreme weather events, all of which are associated with COPD exacerbations. Further research is needed using patient-focused methodological approaches to better understand and quantify these relationships, so that effective mitigation strategies that decrease the risk of exacerbations can be developed.

[Lung sounds can be used as an indicator for assessing severity of chronic obstructive pulmonary disease at the initial diagnosis]

OBJECTIVE

To assess the value of pulmonary auscultation for evaluating the severity of chronic obstructive pulmonary disease (COPD) at the initial diagnosis.

METHODS

The patients with newly diagnosed COPD in our hospital between May, 2016 and May, 2019 were enrolled in this study. According to the findings of pulmonary auscultation, the lung sounds were classified into 5 groups: normal breathing sounds, weakened breathing sounds, weakened breathing sounds with wheezing, obviously weakened breathing sounds, and obviously weakened breathing sounds with wheezing. The pulmonary function of the patients was graded according to GOLD guidelines, and the differential diagnosis of COPD from asthmatic asthma COPD overlap (ACO) was made based on the GOLD guidelines and the European Respiratory Criteria.

RESULTS

A total of 1046 newly diagnosed COPD patients were enrolled, including 949 male and 97 female patients with a mean age of 62.6± 8.71. According to the GOLD criteria, 88.1% of the patients were identified to have moderate or above COPD, 50.0% to have severe or above COPD; a further diagnosis of ACO was made in 347 (33.2%) of the patients. ANOVA analysis showed significant differences in disease course, FEV1, FEV1%, FEV1/FVC, FVC, FVC% and mMRC among the 5 auscultation groups (P < 0.001), but FENO did not differ significantly among them (P=0.097). The percentage of patients with wheezing in auscultation was significantly greater in ACO group than in COPD group (P < 0.001). Spearman correlation analysis showed that lung sounds was significantly correlated with disease severity, FEV1, FEV1%, FVC and FVC% of the patients (P < 0.001); Multiple linear regression analysis showed that a longer disease course, a history of smoking and lung sounds were all associated with poorer lung functions and a greater disease severity.

CONCLUSIONS

Lung sounds can be used as an indicator for assessing the severity of COPD at the initial diagnosis.