Impacts of COPD Exacerbation History on Mortality and Severe Cardiovascular Events among Patients with COPD in China: A Retrospective Cohort Study

Impacts of COPD Exacerbation History on Mortality and Severe Cardiovascular Events among Patients with COPD in China: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impacts of COPD Exacerbation History on Mortality and Severe Cardiovascular Events among Patients with COPD in China: A Retrospective Cohort Study Dongni Hou, Zhike Liu, Xinli Li, Peng Shen, Wenhao Li, Meng Zhang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4678295/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Jul, 2025 Read the published version in Respiratory Research → Version 1 posted 10 You are reading this latest preprint version Abstract Background Chronic Obstructive Pulmonary Disease (COPD) exacerbations are associated with increased mortality and cardiovascular events. However, there is limited evidence on the relationship between COPD exacerbations and mortality and cardiovascular outcomes in China. Methods This retrospective cohort study included Chinese COPD patients aged ≥ 40 years from the Yinzhou regional electronic health records database. Patients were screened for eligibility between 1 Jan 2014 and 1 Mar 2022, with the index date being the first identified COPD diagnosis within this timeframe. Patient characteristics and frequency and severity of COPD exacerbations were collected during the 24-month baseline period prior to the index date. Outcomes included all-cause mortality and severe cardiovascular events. The incidence of death and first severe cardiovascular event was reported overall, and by baseline exacerbation history. Cox proportional hazards models were employed to identify the association between baseline COPD exacerbation history and all-cause death. Results A total of 14,713 COPD patients were included, with a median follow-up duration of 41.3 months. During the follow-up period, 20.1% of patients died, with a crude incidence rate of 5.17 (95% CI: 4.98, 5.36) per 100 person-years. 20.1% of patients experienced severe cardiovascular events. The incidence of severe cardiovascular events increased with higher frequency and severity of baseline COPD exacerbations. Patients with history of severe COPD exacerbations exhibited an increased risk (adjusted HR: 1.26, 95%CI: 1.14, 1.38) of all-cause death compared with patients with no exacerbations. Conclusions The burden of all-cause death and severe cardiovascular events in COPD patients increased with higher frequency and severity of COPD exacerbations. COPD Exacerbations All-cause death Cardiovascular events Figures Figure 1 Figure 2 Background Chronic obstructive pulmonary disease (COPD) is a leading cause of both mortality and morbidity ( 1 ), resulting in more than 3 million deaths each year globally ( 2 ). In China, nearly 100 million people are impacted by COPD, accounting for 32% of all global COPD-related deaths in 2019 ( 3 ). As the population continues to age rapidly in China, the burden of COPD is expected to escalate in the future. COPD exacerbations are a natural course of the disease progression, and the frequency and severity of exacerbations have a significant impact on patient prognosis, including mortality ( 4 ). Despite numerous studies investigating COPD-related mortality ( 2 , 3 , 5 ), there is limited evidence regarding mortality outcomes that are specifically related to COPD exacerbations in China. Previous studies have indicated that the causes of death in COPD patients vary depending on the severity of disease ( 6 ). Cardiac diseases and malignancies, particularly lung cancer, are predominant causes of mortality in patients with mild COPD. As COPD severity increases, however, deaths due to respiratory diseases become more prevalent ( 7 ). COPD exacerbations may also be considered a driving factor for cardiovascular (CV) events ( 8 – 10 ). Data from a nationwide COPD registry in Denmark showed that the odds of a CV event were higher in patients with moderate and severe exacerbations compared to those with no exacerbations ( 10 ). The increased risk of CV events in patients with COPD after an exacerbation may be attributed to shared pathophysiologic mechanisms and specific impacts of the exacerbation event ( 11 ). Currently, there is insufficient data in China to determine the specific causes of mortality associated with COPD exacerbations, as well as to support a clear understanding on the relationship between COPD exacerbations and mortality rates or CV events. Therefore, this study aimed to describe the burden of mortality and severe CV events among Chinese COPD patients and further characterize the associations between COPD exacerbations and death by providing real-world evidence. Part of the results of this study have been previously reported in ATS 2024 ( 12 ). Methods Study design and participants This was a secondary observational retrospective longitudinal cohort study among Chinese patients diagnosed with COPD in routine clinical practice. The Yinzhou regional electronic health records database was used for the study. Yinzhou database is linked to all public health institutions in Yinzhou District of Ningbo, covering data from health information systems in public hospital, community health center, health surveillance system, and death registry from Center for Disease Control and Prevention (CDC) in Zhejiang Province, China. These health information systems in Yinzhou have covered nearly all health-related activities of residents within this region since 2009, from birth to death, across all age groups (13). The Yinzhou database was standardized to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) version 5, which is maintained by the Observational Health Data Sciences and Informatics (OHDSI) Network (14, 15). The study population consisted of a cohort of real-world patients with COPD captured in the Yinzhou database. Patients were screened for eligibility between 1 st January 2014 and 1 st March 2022 (the screening period). Patients were considered eligible if they met the following criteria: 1) had ≥ 2 primary diagnosis items/codes for COPD in the outpatient setting or had ≥1 primary or secondary diagnosis items/codes for COPD in the inpatient setting during the screening period; 2) aged ≥ 40 years upon the first identified diagnosis item/code of COPD; 3) had baseline data continuously available for at least 24 months before the first identified diagnosis item/code of COPD. The date of the first identified COPD diagnosis occurring between the screening period was defined as the index date. Baseline data was obtained from the 24-month pre-index baseline period (including index date). Patients would be excluded if they had a record of Alpha-1 antitrypsin deficiency at baseline. Follow-up was from the day after the index date until (a) 1 st March 2023 (administrative right censoring); (b) loss to follow-up (the last clinical event date recorded in the database); (c) all-cause death (death data was available until 30 Jun 2022), whichever came first ( Figure 1 ). Exposure The exposure of interest was the frequency and severity of COPD exacerbation during the 24-month baseline period, and was classified as follows: no exacerbations, one moderate exacerbation only, ≥2 moderate exacerbations (none severe), and ≥1 severe exacerbation. A moderate exacerbation was defined as an outpatient visit to a physician (general practitioner, pulmonologist or internist) for COPD with a new prescription of systemic corticosteroids (intravenous or oral corticosteroids) and/or antibiotics for respiratory infections. To ensure that these drugs were intended to treat an exacerbation, only prescriptions by general practitioners, pulmonologists or internists were considered. A severe exacerbation was defined as record of hospitalization for COPD exacerbation, which referred to patients with 1) international classification of diseases (ICD)-10 codes of J44, J44.0, or J44.1 as the primary discharge code; or 2) an ICD-10 code of J44.0 as a secondary discharge code (indicating an acute exacerbation that occurred during the hospital stay) (16). Two consecutive exacerbations occurring within 14 days were considered as one single exacerbation and the higher level of severity characterized the episode. Outcomes Study outcomes included all-cause deaths and severe CV events occurred during study follow-up period and recorded in the database. All-cause deaths were categorized into four groups based on the causes of death retrieved from the death registry regulated by CDC in Zhejiang Province, namely: 1) CV-related death, 2) respiratory death, 3) death of other causes, 4) death of unknown causes. A severe CV event was defined as a hospitalization with a primary or secondary discharge code for one of the following events of interest (ICD-10 codes for the following CV events were provided in Additional Table 1 ), including 1) acute coronary syndrome, 2) heart failure decompensation, 3) cerebral ischemia, 4) arrythmia, and 5) CV-related death. Statistical analysis The statistical program SQL and R Project for Statistical Computing, version 4.2.2 or higher were used for analysis, establishing a statistical significance for values of p < 0.05. The full COPD cohort was characterized in terms of demographic and clinical characteristics during the baseline period, including age at index date, gender, body mass index (BMI), smoking status, education level, comorbidities, history of COPD exacerbations, and concomitant medications. Further details on the definition of patient baseline characteristics were shown in Supplementary Table 2 . Continuous variables were described using the mean (standard deviation [SD]), median (interquartile range [IQR]), minimum and maximum values. Dichotomous/categorical variables were described using n (%) of each category. Count variables were described as continuous variables, using n (%) of each count category, where appropriate. Deaths and severe CV events occurring during the follow-up period were described in terms of number (%) of patients with all-cause and cause-specific death, and number (%) of patients with ≥1 severe CV event of any type and specific type. The crude incidence rate and 95% confidence interval (CI) of all-cause and cause-specific death and first severe CV event of any type and specific type were reported overall, and by different baseline exacerbation categories. Cox proportional hazards model was used with binary indicators of each group of baseline COPD exacerbation (no exacerbations as reference group) as covariates to investigate the association between baseline exacerbation frequency and severity and all-cause of death. The model was fitted with and without adjustment for confounders. The confounders were selected from baseline characteristics listed in Additional Table 2 , based on recommendation from medical and evidence from previous studies (8). Smoking status was not included in the adjusted model due to uncertainty regarding the missing rate. The full list of covariates incorporated in the Cox proportional hazard model was summarized in a footnote below Table 4 . Patients with missing values in baseline covariates were not included in the final model. No imputation was performed. Results From 1 Jan 2014 to 1 Mar 2022 (screening period), a total of 14,713 patients with COPD were included in the study for final analysis. The patient attrition flowchart for COPD patients who fulfilled the study inclusion/exclusion criteria is summarized in Figure 2 . Baseline characteristics Details of patient baseline characteristics are shown in Table 1 (at the end of the document text) . Among the included 14,713 patients, 9,862 (67.0%) were male. The mean (SD) age of these patients was 72.0 (11.5). The numbers of patients with no exacerbations, only one moderate exacerbation, ≥ 2 moderate exacerbations (none severe), and ≥ 1 severe exacerbation during the 24-month baseline period were 8,913 (60.6%), 3,055 (20.8%), 739 (5.0%), and 2,006 (13.6%), respectively. The median (IQR) follow-up duration was 41.3 (47.4) months. There were 5,991 (40.7%) patients with an education level of secondary school and above. Hypertension (71.9%) was the most common comorbidity among these patients. In terms of comedications at baseline, 5,029 (34.2%) patients received long-acting COPD treatments, while 3,657 (24.9%) patients received short-acting COPD treatments. Incidence of deaths overall and by COPD exacerbation history at baseline As shown in Table 2 , a total of 2,951 (20.1%) patients died during a median (IQR) follow-up period of 41.3 (47.4) months. Specifically, most patients (1,264/14,710, 8.6%) died from respiratory diseases, followed by death due to other causes, death from CV-related causes, and death from unknown causes. The crude incidence rate for all-cause death was 5.17 (95% CI: 4.98, 5.36) per 100 person-years. The crude incidence rate of experiencing respiratory death was 2.21 (95% CI: 2.09, 2.34) per 100 person-years, which was also higher than that of other categories of death. The proportion of patients who experienced all-cause death increased with higher baseline frequency or severity of COPD exacerbations ( Table 3 ). The crude incidence rate of all-cause death peaked at 10.08 (95% CI: 9.26, 10.95) per 100 person-years among patients with ≥1 severe exacerbation. As for cause-specific deaths, the crude incidence rate of respiratory death increased with higher frequency and severity of baseline COPD exacerbation, from 1.58 (95% CI:1.44, 1.72) per 100 person-years in patients with no exacerbations to 5.21 (95% CI: 4.67, 5.79) per 100 person-years in patients with ≥1 severe exacerbation. The crude incidence rate of respiratory death was elevated across all baseline COPD exacerbation categories, including those with one moderate exacerbation. Incidence of severe CV events overall and by COPD exacerbation history at baseline As shown in Table 2 , a total of 2,394 patients (20.1%) experienced severe CV events during the follow-up period, with a crude incidence rate of 5.48 (95% CI: 5.26, 5.70) per 100 person-years. Heart failure decompensation was the most common severe CV event in these patients (1,521/13,016, 11.7%), followed by arrythmias (1,199/13,403, 8.9%), cerebral ischemia (769/13,854, 5.6%), CV-related death (682/14,710, 4.6%), and acute coronary syndrome (48/14,647, 0.3%). The crude incidence rate (per 100 person-years) of severe CV events increased with higher baseline frequency or severity of COPD exacerbations, from 4.80 (95% CI: 4.53, 5.07) in patients with no exacerbations to 8.54 (95% CI: 7.61, 9.55) in patients with ≥1 severe exacerbation. Patients with ≥1 severe exacerbation exhibited the highest incidence rates of heart failure decompensation, cerebral ischemia, arrythmias, and CV-related death ( Table 3 ). Association between all-cause death and baseline COPD exacerbation history Table 4 summarized the hazard ratios (HR) for all-cause deaths by different COPD exacerbation frequencies and severities at baseline. In the unadjusted Cox model, patients with ≥2 moderate exacerbations (HR: 1.26, 95% CI: 1.10,1.46) or ≥1 severe exacerbation (HR: 2.19, 95% CI: 1.99, 2.40) were at higher risk of all-cause death compared with the reference group (patients with no exacerbations). After adjusting for confounders, patients with ≥1 severe exacerbation still showed an increased risk (HR: 1.26, 95%CI: 1.14, 1.38) of all-cause death, while the increased risk of death in patients with ≥2 moderate exacerbations was no longer statistically significant. Of note, patients with one moderate exacerbation exhibited a decreased risk (HR: 0.88, 95% CI: 0.80, 0.97) of all-cause death compared with the reference group in the confounder-adjusted model. Discussion This study described the cumulative incidence and incidence rate of death and severe CV events among Chinese COPD patients and further explored the association between COPD exacerbations and death. The overall incidence of all-cause death reported in our study (20.1%) is similar with a previous nationwide study in Korea, which reported an overall mortality rate of 26.2% and a 5-year mortality rate of 25.4% (17). However, in some other studies, a notably higher mortality rate was reported. A study in Italy focusing on patients aged 65 and older found a COPD mortality rate of 56.9% after 12 years of follow-up (18). Additionally, in a study including patients aged 65 to 100 years, the COPD mortality rates at 5, 10, and 15 years were reported as 32%, 62%, and 75%, respectively (19). The relatively lower incidence of death in our study may be attributed to the lower age limit of 40 and above, and a shorter median follow-up time of 3.4 years (41.3 months). The two leading causes of death reported in our study were respiratory and CV related, accounting for 42.8% and 23.1% of deaths, respectively. However, there are variations in the distribution of causes of death across different studies. For instance, a prospective cohort study in Spain found that deaths from respiratory causes and CV diseases accounted for 67.2% and 10.3% of deaths, respectively (20), while another cohort study in England reported an overall mortality rate of 28.8%, with COPD-related and CV-related deaths accounting for 25.7% and 23.3% of all deaths, respectively (21). Since COPD patients often die from multiple causes, and the cause definitions vary across studies, it has been suggested that all-cause mortality is likely the most suitable measure of mortality to use in COPD (22). In addition, many patients in our study had comorbid CV diseases at baseline, such as hypertension, coronary artery disease, and heart failure. The physiological stressors and inflammatory responses related to COPD exacerbations may aggravate these pre-existing CV conditions, potentially contributing to the high incidence of CV-related deaths. In previous research, COPD exacerbations have been shown to be associated with increased risk of mortality in patients with COPD. One retrospective study reported one-year mortality rate of 26.2% and five-year mortality rate of 64.3% for patients admitted for acute exacerbations of COPD (23). The EXACOS-UK study found that the rate of all-cause mortality and COPD-related mortality among COPD patients was increased with more frequent and severe baseline COPD exacerbations (24). Another cohort study in England demonstrated both increased frequency and severity of COPD exacerbations were associated with higher risk of COPD-related mortality (≥2 exacerbations vs none, adjusted HR: 1.64, 95% CI: 1.57,1.71; 1 severe vs none, adjusted HR: 2.17, 95% CI: 2.04, 2.31) (21). In another study in Spain, the patients with the greatest mortality risk were those with three or more acute COPD exacerbations (HR: 4.13, 95% CI: 1.80, 9.41) (20). Our study revealed that the mortality rate was higher in patients with COPD exacerbations at baseline, with crude incidence rate of death being highest in those with severe exacerbation(s), which aligned with existing evidence. Our study also found that the crude incidence rate of respiratory death increased with higher frequency and severity of baseline COPD exacerbation, which was supported by previous studies that deaths from respiratory diseases are becoming more common as the severity of COPD increases (7). In our confounder-adjusted Cox model, patients with history of any severe COPD exacerbation had a significantly higher risk of all-cause death (adjusted HR: 1.26, 95% CI: 1.14, 1.38), compared with patients without history of COPD exacerbation, which was consistent with previous studies. However, no significant association was observed between patients with ≥2 moderate exacerbations at baseline and all-cause mortality (adjusted HR: 1.07, 95% CI: 0.92, 1.23), while a lower risk of death was observed in patients with one moderate exacerbation at baseline (adjusted HR: 0.88, 95% CI: 0.80, 0.97) compared to patients with no exacerbations, which may seem paradoxical. Firstly, this may be partially due to our definition of a moderate exacerbation by outpatient visiting for COPD with a new prescription of systemic corticosteroids and/or antibiotics for respiratory infections. Some patients experiencing moderate exacerbations may have opted not to seek medical treatment, leading to a misclassification of individuals with a moderate exacerbation being counted as having no exacerbations. This may occur more frequently in patients with infrequent exacerbations (only 1 moderate) than those with frequent (≥2 moderate) exacerbations. Secondly, individuals who sought medical attention were more likely to adhere to prescribed treatments and seek healthcare when experiencing exacerbation symptoms, indicating a higher level of health awareness and literacy in managing COPD, potentially associated with improved overall health and reduced mortality risk (25). Thirdly, our study's definition implied that patients experiencing a moderate exacerbation may have received timely medical attention and appropriate pharmacological treatment, contributing to better COPD and comorbidity management. Prompt medical care and monitoring during a moderate exacerbation might have led to improved overall health outcomes and reduced mortality risk compared to patients with no exacerbations (26). Our findings highlighted the significant burden of severe CV events in patients with COPD. The overall cumulative incidence of severe CV events in our study was 20.1%, with a crude incidence rate of 5.48 per 100 person-years. Heart failure decompensation was the most common CV event observed. These findings are consistent with previous studies that have demonstrated an increased burden of CV diseases in COPD patients (11, 27-31). The increased risk of CV events in COPD patients has been attributed to shared risk factors (environmental and/or genetic) and shared pathophysiological pathways (32). Our study also revealed that patients with baseline COPD exacerbation histories had a higher incidence rate of severe CV events. Similarly, data from the PHARMO Data Network in the Netherlands demonstrated that the risk of severe CV events was significantly increased and remained elevated for over one year after a moderate or severe COPD exacerbation (8). The results in our study emphasize the need for better COPD management strategies that can be provided earlier in the course of the disease, particularly for those who experience severe COPD exacerbations. The notable risk of CV-related mortality and incidence of severe CV events in COPD patients with exacerbations may require even more clinical awareness and active measures to treat or prevent cardiovascular complications in this population. There are some limitations to our study design. First, the definition of a moderate exacerbation in our study encompassed an outpatient visit for COPD with a new prescription or purchase of systemic corticosteroids and/or antibiotics for respiratory infections. This definition might have led to an overestimation of the population in the subgroup with no exacerbations, as some patients experiencing exacerbations may have opted not to seek medical treatment. Second, as an observational study, we have to acknowledge that residual confounding cannot be entirely eliminated, and there was high rate of missing values in FEV1 and smoking status, whereas these two factors are essential in defining and assessing COPD (33, 34). The absence of comprehensive data on these variables could introduce bias into the analysis and impact the accuracy of the findings. Lastly, Yinzhou is a developed district of Ningbo city, located in East China. Research on disease burden in China has demonstrated that Eastern provinces exhibit a lower burden of COPD, including lower incidence, prevalence, and mortality rates (3). Therefore, caution should be taken when applying the study findings to other areas with potentially different disease burdens and clinical practices. Conclusions To our knowledge, this study was the largest retrospective cohort study investigating mortality and CV outcomes among COPD patients in China. The study reported an incidence rate of death of 5.17 per 100 person-years, with respiratory disease being the most common cause of death. Patients with history of severe COPD exacerbation(s) at baseline had a higher risk of death and severe CV events compared with patients without an exacerbation. These findings also yielded significant implications stressing the importance of clinical practice and patient management within the field of COPD in China and globally. Abbreviations BMI Body Mass Index CDC Center for Disease Control and Prevention CI Confidence Interval COPD Chronic Obstructive Pulmonary Disease CV Cardiovascular HR Hazard Ratio ICD International Classification of Diseases ICS Inhaled Corticosteroids IQR Interquartile Range LABA Long-Acting β2 Agonists LAMA Long-Acting Muscarinic Antagonists OHDSI Observational Health Data Sciences and Informatics OMOP CDM Observational Medical Outcomes Partnership Common Data Model SABA Short-Acting β2 Agonists SAMA Short-Acting Muscarinic Antagonist SD Standard Deviation Declarations Ethics approval and consent to participate A protocol for this research was approved by the Peking University Institutional Review Board (IRB00001052-23112) and the Medical Ethics Committee of Zhongshan Hospital, Fudan University (B2023-206(2)). Consent for publication Not applicable Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available due to the protection of personal information and requirements from the data source. Competing interests The authors declare that they have no competing interests. Funding This study was funded by AstraZeneca UK Limited. Authors' contributions F.S. and Y.S. participated in study conceptualization and design. D.H., Z.L., X.L., P.S., W.L., M.Z., I.C., H.L., S.Z., F.S., Y.C., and Y.S. participated in data analysis and interpretation. F.S. and Y.S. participated in manuscript draft. D.H., Z.L, X.L., W.L., I.C., F.S., and Y.S. participated in manuscript editing and revision. All authors approved the final version for submission. Acknowledgements The authors would like to thank Jennifer Quint, Professor of Respiratory Epidemiology at the School of Public Health, Imperial College London, for her valuable professional advice. Medical writing and editorial support were provided by Xiaoqing Wang, Frank Lu, and Savannah Gui of IQVIA, which received funding from AstraZeneca UK Limited. References Christenson SA, Smith BM, Bafadhel M, Putcha N. Chronic obstructive pulmonary disease. Lancet. 2022;399(10342):2227-42. Safiri S, Carson-Chahhoud K, Noori M, Nejadghaderi SA, Sullman MJM, Ahmadian Heris J, et al. Burden of chronic obstructive pulmonary disease and its attributable risk factors in 204 countries and territories, 1990-2019: results from the Global Burden of Disease Study 2019. Bmj. 2022;378:e069679. Yin P, Wu J, Wang L, Luo C, Ouyang L, Tang X, et al. The Burden of COPD in China and Its Provinces: Findings From the Global Burden of Disease Study 2019. Front Public Health. 2022;10:859499. Janson C, Nwaru BI, Wiklund F, Telg G, Ekström M. Management and Risk of Mortality in Patients Hospitalised Due to a First Severe COPD Exacerbation. Int J Chron Obstruct Pulmon Dis. 2020;15:2673-82. Liu W, Wang W, Liu J, Liu Y, Meng S, Wang F, et al. Trend of Mortality and Years of Life Lost Due to Chronic Obstructive Pulmonary Disease in China and Its Provinces, 2005-2020. Int J Chron Obstruct Pulmon Dis. 2021;16:2973-81. Garcia-Aymerich J, Serra Pons I, Mannino DM, Maas AK, Miller DP, Davis KJ. Lung function impairment, COPD hospitalisations and subsequent mortality. Thorax. 2011;66(7):585-90. Berry CE, Wise RA. Mortality in COPD: causes, risk factors, and prevention. Copd. 2010;7(5):375-82. Swart KMA, Baak BN, Lemmens L, Penning-van Beest FJA, Bengtsson C, Lobier M, et al. Risk of cardiovascular events after an exacerbation of chronic obstructive pulmonary disease: results from the EXACOS-CV cohort study using the PHARMO Data Network in the Netherlands. Respir Res. 2023;24(1):293. Claus V, Sami S, Edeltraut G, Don S, Nathaniel H, Nicolas M, et al. Increased risk of severe cardiovascular events following exacerbations of COPD: a multi-database cohort study. European Respiratory Journal. 2023;62(suppl 67):PA3013. Løkke A, Hilberg O, Lange P, Ibsen R, Telg G, Stratelis G, et al. Exacerbations Predict Severe Cardiovascular Events in Patients with COPD and Stable Cardiovascular Disease-A Nationwide, Population-Based Cohort Study. Int J Chron Obstruct Pulmon Dis. 2023;18:419-29. Morgan AD, Zakeri R, Quint JK. Defining the relationship between COPD and CVD: what are the implications for clinical practice? Ther Adv Respir Dis. 2018;12:1753465817750524. Li W, Liu Z, Zhang M, Li X, Cheang I, Sun F, et al. Exacerbations of Chronic Obstructive Pulmonary Disease and Cardiovascular Diseases (EXACOS-CV): A Database Study in China on Mortality and Severe Cardiovascular Events. A48 COPD EXACERBATIONS AND HOSPITALIZATIONS: DETERMINANTS AND DRIVERS. p. A1866-A. Lin H, Tang X, Shen P, Zhang D, Wu J, Zhang J, et al. Using big data to improve cardiovascular care and outcomes in China: a protocol for the CHinese Electronic health Records Research in Yinzhou (CHERRY) Study. BMJ Open. 2018;8(2):e019698. Hripcsak G, Duke JD, Shah NH, Reich CG, Huser V, Schuemie MJ, et al. Observational Health Data Sciences and Informatics (OHDSI): opportunities for observational researchers. Studies in health technology and informatics. 2015;216:574. Overhage JM, Ryan PB, Reich CG, Hartzema AG, Stang PE. Validation of a common data model for active safety surveillance research. Journal of the American Medical Informatics Association. 2012;19(1):54-60. World Health Organization. ICD-10 Version:2019 2019 [Available from: https://icd.who.int/browse10/2019/en. Park SC, Kim DW, Park EC, Shin CS, Rhee CK, Kang YA, et al. Mortality of patients with chronic obstructive pulmonary disease: a nationwide populationbased cohort study. Korean J Intern Med. 2019;34(6):1272-8. Testa G, Cacciatore F, Bianco A, Della-Morte D, Mazzella F, Galizia G, et al. Chronic obstructive pulmonary disease and long-term mortality in elderly subjects with chronic heart failure. Aging Clin Exp Res. 2017;29(6):1157-64. Sorino C, Pedone C, Scichilone N. Fifteen-year mortality of patients with asthma-COPD overlap syndrome. Eur J Intern Med. 2016;34:72-7. Soler-Cataluña JJ, Martínez-García MA, Román Sánchez P, Salcedo E, Navarro M, Ochando R. Severe acute exacerbations and mortality in patients with chronic obstructive pulmonary disease. Thorax. 2005;60(11):925-31. Hannah W, Kieran JR, Jennifer KQ. Cause-specific mortality in COPD subpopulations: a cohort study of 339 647 people in England. Thorax. 2023:thorax-2022-219320. Cazzola M, MacNee W, Martinez FJ, Rabe KF, Franciosi LG, Barnes PJ, et al. Outcomes for COPD pharmacological trials: from lung function to biomarkers. Eur Respir J. 2008;31(2):416-69. García-Sanz MT, Cánive-Gómez JC, Senín-Rial L, Aboal-Viñas J, Barreiro-García A, López-Val E, et al. One-year and long-term mortality in patients hospitalized for chronic obstructive pulmonary disease. J Thorac Dis. 2017;9(3):636-45. Whittaker H, Rubino A, Müllerová H, Morris T, Varghese P, Xu Y, et al. Frequency and severity of exacerbations of COPD associated with future risk of exacerbations and mortality: a UK routine health care data study. International Journal of Chronic Obstructive Pulmonary Disease. 2022:427-37. Omachi TA, Sarkar U, Yelin EH, Blanc PD, Katz PP. Lower health literacy is associated with poorer health status and outcomes in chronic obstructive pulmonary disease. J Gen Intern Med. 2013;28(1):74-81. Simpson SH, Eurich DT, Majumdar SR, Padwal RS, Tsuyuki RT, Varney J, et al. A meta-analysis of the association between adherence to drug therapy and mortality. Bmj. 2006;333(7557):15. Schneider C, Bothner U, Jick SS, Meier CR. Chronic obstructive pulmonary disease and the risk of cardiovascular diseases. Eur J Epidemiol. 2010;25(4):253-60. Chen W, Thomas J, Sadatsafavi M, FitzGerald JM. Risk of cardiovascular comorbidity in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. Lancet Respir Med. 2015;3(8):631-9. Miller J, Edwards LD, Agustí A, Bakke P, Calverley PM, Celli B, et al. Comorbidity, systemic inflammation and outcomes in the ECLIPSE cohort. Respir Med. 2013;107(9):1376-84. Donaldson GC, Hurst JR, Smith CJ, Hubbard RB, Wedzicha JA. Increased risk of myocardial infarction and stroke following exacerbation of COPD. Chest. 2010;137(5):1091-7. Reilev M, Pottegård A, Lykkegaard J, Søndergaard J, Ingebrigtsen TS, Hallas J. Increased risk of major adverse cardiac events following the onset of acute exacerbations of COPD. Respirology. 2019;24(12):1183-90. Vishanna B, Andrea SM, Alice MT, Michael N. Cardiovascular disease in chronic obstructive pulmonary disease: a narrative review. Thorax. 2022;77(9):939. Gülşen A. Pulmonary Function Changes in Chronic Obstructive Pulmonary Disease Patients According to Smoking Status. Turk Thorac J. 2020;21(2):80-6. Doherty DE. A review of the role of FEV1 in the COPD paradigm. Copd. 2008;5(5):310-8. Tables Table 1 . Baseline characteristics of the full COPD cohort overall and by 24-month baseline COPD exacerbation status. Baseline characteristics All patients Has no exacerbations during baseline Has 1 moderate exacerbation during baseline Has ≥2 moderate exacerbations during baseline Has ≥1 severe exacerbation(s) during baseline N=14,713 N=8,913 N=3,055 N=739 N=2,006 n (%) n (%) n (%) n (%) n (%) Age in years mean [SD] 72.0 [11.5] 70.9 [11.8] 71.5 [11.0] 72.7 [10.1] 77.4 [9.6] median [IQR] 73.0 [17.0] 71.0 [17.0] 72.0 [16.0] 74.0 [15.0] 79.0 [13.0] min, max 40.0, 101.0 40.0, 101.0 40.0, 99.0 42.0, 96.0 42.0, 101.0 Gender Male 9,862 (67.0%) 5,822 (65.3%) 2,175 (71.2%) 522 (70.6%) 1,343 (66.9%) Female 4,804 (32.7%) 3,067 (34.4%) 873 (28.6%) 215 (29.1%) 649 (32.4%) Missing 47 (0.3%) 24 (0.3%) 7 (0.2%) 2 (0.3%) 14 (0.7%) # of moderate exacerbations during baseline 0 10,533 (71.6%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1,620 (80.8%) 1 3,285 (22.3%) 0 (0.0%) 3,055 (100.0%) 0 (0.0%) 230 (11.5%) ≥2 895 (6.1%) 0 (0.0%) 0 (0.0%) 739 (100.0%) 156 (7.8%) # of severe exacerbations during baseline 0 12,707 (86.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 1,888 (12.8%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1,888 (94.1%) ≥2 118 (0.8%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 118 (5.9%) # of moderate/severe exacerbations during baseline 1 0 8,913 (60.6%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 4,720 (32.1%) 0 (0.0%) 3,055 (100.0%) 0 (0.0%) 1,665 (83.0%) ≥2 1,080 (7.3%) 0 (0.0%) 0 (0.0%) 739 (100.0%) 341 (17.0%) Follow-up time in months 2 mean [SD] 46.6 [30.0] 43.5 [28.0] 55.9 [30.4] 66.0 [33.2] 39.0 [30.7] median [IQR] 41.3 [47.4] 37.5 [41.8] 52.9 [51.7] 67.1 [60.6] 33.3 [47.5] min 3 , max 0.0, 109.9 0.0, 109.9 0.1, 109.9 0.3, 109.9 0.0, 109.9 BMI (recorded or height / weight derived) at baseline and closest to index date, kg/m² 7,584 (51.5%) 4,685 (52.6%) 1,559 (51.0%) 365 (49.4%) 975 (48.6%) mean [SD] 23.1 [3.6] 23.2 [3.6] 22.9 [3.6] 22.4 [3.5] 22.7 [3.9] median [IQR] 22.9 [4.8] 23.1 [4.7] 22.8 [4.6] 22.1 [4.7] 22.3 [5.0] min, max 9.0, 53.0 9.0, 53.0 12.0, 40.0 15.0, 34.0 13.0, 45.0 Missing 7,129 (48.5%) 4,228 (47.4%) 1,496 (49.0%) 374 (50.6%) 1,031 (51.4%) Education level Unknown 1,736 (11.8%) 1,073 (12.0%) 306 (10.0%) 66 (8.9%) 291 (14.5%) Illiteracy 1,832 (12.5%) 970 (10.9%) 379 (12.4%) 119 (16.1%) 364 (18.1%) Elementary school 5,154 (35.0%) 2,989 (33.5%) 1,129 (37.0%) 310 (41.9%) 726 (36.2%) Secondary school and above 5,991 (40.7%) 3,881 (43.5%) 1,241 (40.6%) 244 (33.0%) 625 (31.2%) Comorbidities (any time prior to index date, including index date) Obesity 11 (0.1%) 6 (0.1%) 3 (0.1%) 0 (0.0%) 2 (0.1%) Diabetes mellitus type-1 or -2 1,939 (13.2%) 1,297 (14.6%) 310 (10.1%) 62 (8.4%) 270 (13.5%) Any Disorders of lipoprotein metabolism and other lipidaemia 5,902 (40.1%) 3,861 (43.3%) 1,109 (36.3%) 224 (30.3%) 708 (35.3%) Ischemic heart diseases 6,293 (42.8%) 4,069 (45.7%) 1,110 (36.3%) 261 (35.3%) 853 (42.5%) Hypertension 10,572 (71.9%) 6,494 (72.9%) 2,043 (66.9%) 523 (70.8%) 1,512 (75.4%) Heart failure 3,265 (22.2%) 1,723 (19.3%) 501 (16.4%) 200 (27.1%) 841 (41.9%) Pulmonary oedema 8 (0.1%) 6 (0.1%) 1 (0.0%) 0 (0.0%) 1 (0.0%) Pulmonary hypertension 91 (0.6%) 48 (0.5%) 8 (0.3%) 0 (0.0%) 35 (1.7%) Venous thromboembolism 311 (2.1%) 200 (2.2%) 55 (1.8%) 12 (1.6%) 44 (2.2%) Cerebrovascular disease 5,748 (39.1%) 3,730 (41.8%) 994 (32.5%) 234 (31.7%) 790 (39.4%) Arrythmia 4,096 (27.8%) 2,592 (29.1%) 691 (22.6%) 177 (24.0%) 636 (31.7%) Current asthma 6,142 (41.7%) 3,768 (42.3%) 1,277 (41.8%) 406 (54.9%) 691 (34.4%) Chronic kidney disease, renal failure 572 (3.9%) 406 (4.6%) 71 (2.3%) 17 (2.3%) 78 (3.9%) Anxiety disorder 3,437 (23.4%) 2,280 (25.6%) 636 (20.8%) 126 (17.1%) 395 (19.7%) Comedications (baseline, including index date) COPD drug - Long-acting treatments 4 5,029 (34.2%) 3,258 (36.6%) 879 (28.8%) 218 (29.5%) 674 (33.6%) COPD drug - Short-acting treatments 5 3,657 (24.9%) 1,755 (19.7%) 685 (22.4%) 279 (37.8%) 938 (46.8%) Theophylline 1,890 (12.8%) 905 (10.2%) 354 (11.6%) 130 (17.6%) 501 (25.0%) Cardiac drugs 6 12,409 (84.3%) 7,454 (83.6%) 2,570 (84.1%) 677 (91.6%) 1,708 (85.1%) 1 Combined moderate and severe exacerbations within 14 days during baseline (including index date) 2 Follow-up time is defined as from the day after index date until the first occurrence of (a) 1 Mar 2023 (study end); (b) loss to follow-up in the database; or (c) all-cause death (death data was available until 30 June 2022) For patients who died on the index date or had no follow-up information after the index date, their follow-up time would be 0. 3 All COPD drugs presented in the table only contain fixed dose products. 4 Long-acting COPD treatments: ICS (Inhaled Corticosteroids), LAMA (Long-Acting Muscarinic Antagonists), LABA (Long-Acting β2 Agonists), ICS+LABA, LAMA+LABA, ICS+LAMA+LABA. 5 Short acting COPD treatments: SABA (Short-Acting β2 Agonists), SAMA (Short-Acting Muscarinic Antagonist) 6 Cardiac drugs: antithrombotic and anticoagulants, cardiac therapy, antihypertensives, diuretics, beta blocking agents, calcium channel blockers, statins. Table 2 . Incidence rate of death and severe CV events during follow-up in full cohort. Total * N (%) Crude incidence rate (95% CI) + All-cause death & 14,710 2,951 (20.1%) 5.17 (4.98, 5.36) CV-related death $ 14,710 682 (4.6%) 1.19 (1.11, 1.29) Respiratory death 14,710 1,264 (8.6%) 2.21 (2.09, 2.34) Death of other causes 14,710 939 (6.4%) 1.64 (1.54, 1.75) Death of unknown causes 14,710 66 (0.4%) 0.12 (0.09, 0.15) Any severe CV event & 11896 2,394 (20.1%) 5.48 (5.26, 5.70) Acute coronary syndrome 14647 48 (0.3%) 0.08 (0.06, 0.11) Heart failure decompensation 13016 1,521 (11.7%) 3.09 (2.94, 3.25) Cerebral ischemia 13854 769 (5.6%) 1.45 (1.35, 1.56) Arrythmias 13403 1,199 (8.9%) 2.36 (2.23, 2.50) * : For each outcome, the “Total” excluded patients who 1) had severe CV events at any time prior to or on the index date or 2) died on the index date or 3) had no follow-up information after the index date. + : per 100 person-years & : The all-cause death and severe CV events referred to all deaths / events during the follow-up period (starting from one day after index date). Mortality data were only available until 30 Jun 2022. $ : Based on definition, CV-related death was one of the severe CV events. Abbreviations: CV: cardiovascular; CI: confidence interval Table 3 . Incidence rate of death and severe CV events during follow-up by COPD exacerbation history during 24-month baseline. Patients with no exacerbations Patients with 1 moderate exacerbation Patients with ≥ 2 moderate exacerbations (not severe) Patients with ≥ 1 severe exacerbation Total * N (%) Crude incidence rate (95% CI) + Total * N (%) Crude incidence rate (95% CI) + Total * N (%) Crude incidence rate (95% CI) + Total * N (%) Crude incidence rate (95% CI) + All-cause death & 8,911 1,475 (16.6%) 4.57 (4.34, 4.80) 3,055 598 (19.6%) 4.20 (3.87, 4.55) 739 226 (30.6%) 5.56 (4.86, 6.34) 2,005 652 (32.5%) 10.01 (9.26, 10.81) CV-related death $ 8,911 413 (4.6%) 1.28 (1.16, 1.41) 3,055 107 (3.5%) 0.75 (0.62, 0.91) 739 33 (4.5%) 0.81 (0.56, 1.14) 2,005 129 (6.4%) 1.98 (1.65, 2.35) Respiratory death 8,911 510 (5.7%) 1.58 (1.44, 1.72) 3,055 289 (9.5%) 2.03 (1.80, 2.28) 739 126 (17.1%) 3.10 (2.58, 3.69) 2,005 339 (16.9%) 5.21 (4.67, 5.79) Death of other causes 8,911 524 (5.9%) 1.62 (1.49, 1.77) 3,055 183 (6.0%) 1.29 (1.11, 1.49) 739 67 (9.1%) 1.65 (1.21, 2.01) 2,005 184 (9.2%) 2.83 (2.20, 3.00) Death of unknown causes 8,911 28 (0.3%) 0.09 (0.06, 0.13) 3,055 19 (0.6%) 0.13 (0.08, 0.21) 739 3 (0.4%) 0.07 (0.02, 0.22) 2,005 16 (0.8%) 0.25 (0.14, 0.40) Any severe CV event & 7,324 1,230 (16.8%) 4.80 (4.53, 5.07) 2,743 622 (22.7%) 5.40 (4.99, 5.85) 636 236 (37.1%) 7.88 (6.91, 8.95) 1,193 306 (25.6%) 8.54 (7.61, 9.55) Acute coronary syndrome 8,860 32 (0.4%) 0.10 (0.07, 0.14) 3,050 8 (0.3%) 0.06 (0.02, 0.11) 739 3 (0.4%) 0.07 (0.02, 0.22) 1,998 5 (0.3%) 0.08 (0.03, 0.18) Heart failure decompensation 8,061 745 (9.2%) 2.59 (2.41, 2.79) 2,885 393 (13.6%) 3.09 (2.79, 3.41) 663 164 (24.7%) 4.87 (4.15, 5.67) 1,407 219 (15.6%) 4.95 (4.32, 5.65) Cerebral ischemia 8,338 418 (5.0%) 1.40 (1.26, 1.54) 2,960 165 (5.6%) 1.23 (1.05, 1.43) 720 71 (9.9%) 1.88 (1.47, 2.37) 1,836 115 (6.3%) 2.00 (1.65, 2.40) Arrythmias 8,143 604 (7.4%) 2.08 (1.92, 2.25) 2,902 311 (10.7%) 2.41 (2.15, 2.69) 700 102 (14.6%) 2.80 (2.28, 3.40) 1,658 182 (11.0%) 3.53 (3.03, 4.08) * : For each outcome, the “Total” excluded patients who 1) had severe CV events any time prior to or on the index date or 2) died on the index date or 3) had no follow-up information after the index date + : 100 per person-years & : The all-cause death and severe CV events referred to all deaths / events during the follow-up period (starting from one day after index date). Mortality data were only available until 30 Jun 2022. $ : Based on definition, CV-related death was one of the severe CV events. Abbreviations: CV: cardiovascular; CI: confidence interval Table 4. Hazard ratios of deaths by baseline COPD exacerbation history. Outcome Baseline COPD exacerbation history (vs. no exacerbations) Unadjusted Adjusted + HR (95% CI) p-value HR (95% CI) p-value No exacerbations (reference) - - - - All-cause death & 1 moderate exacerbation 0.94 (0.85, 1.03) 0.18 0.88 (0.80, 0.97) 0.01 * ≥2 moderate exacerbations 1.26 (1.10, 1.46) <0.01 ** 1.07 (0.92, 1.23) 0.37 1 severe exacerbation 2.19 (1.99, 2.40) <0.01 ** 1.26 (1.14, 1.38) <0.01 ** *: p<0.05; ** p<0.01; + : Adjusted for baseline covariates: age, gender, education level, comorbidities recorded any time prior to index date including index date (obesity, diabetes mellitus type-1 or -2, any disorders of lipoprotein metabolism and other lipidaemias, ischemic heart diseases, hypertensive diseases, heart failure, venous thromboembolism, arrythmia, current asthma, chronic kidney disease, mental illness), drug use at baseline (long-acting and short acting COPD drugs, theophylline, cardiac drugs) & : In the model, the all-cause death referred to all deaths during the follow-up period (starting from the day after index date). Mortality data were only available until 30 Jun 2022. Abbreviations: CV: cardiovascular; COPD: chronic obstructive pulmonary disease; HR: hazard ratio; CI: confidence interval Additional Declarations No competing interests reported. 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07:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4678295/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4678295/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12931-025-03316-4","type":"published","date":"2025-07-23T15:58:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":61358760,"identity":"40711df6-bfa6-43e9-b84e-b61983657052","added_by":"auto","created_at":"2024-07-29 21:23:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82201,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eStudy design scheme\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4678295/v1/b55150480f2c94e6e6694db4.png"},{"id":61358050,"identity":"19d76e98-de3e-431f-94cd-93325cfc2ce4","added_by":"auto","created_at":"2024-07-29 21:15:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":84276,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePatient attrition flowchart\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4678295/v1/2fbdbff6384d14ac26b2524c.png"},{"id":87756765,"identity":"1e805bdb-ec55-40c2-acf0-46d41eb046a8","added_by":"auto","created_at":"2025-07-28 16:09:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1694355,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4678295/v1/af68784d-9b75-4f75-9c36-a07052bc6698.pdf"},{"id":61358052,"identity":"a3a4d387-fc4d-408e-91ff-fd30ed4fa5dd","added_by":"auto","created_at":"2024-07-29 21:15:30","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19705,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-4678295/v1/666d1881c13ee5a0571933f0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impacts of COPD Exacerbation History on Mortality and Severe Cardiovascular Events among Patients with COPD in China: A Retrospective Cohort Study","fulltext":[{"header":"Background","content":"\u003cp\u003eChronic obstructive pulmonary disease (COPD) is a leading cause of both mortality and morbidity (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), resulting in more than 3\u0026nbsp;million deaths each year globally (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In China, nearly 100\u0026nbsp;million people are impacted by COPD, accounting for 32% of all global COPD-related deaths in 2019 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). As the population continues to age rapidly in China, the burden of COPD is expected to escalate in the future. COPD exacerbations are a natural course of the disease progression, and the frequency and severity of exacerbations have a significant impact on patient prognosis, including mortality (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Despite numerous studies investigating COPD-related mortality (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), there is limited evidence regarding mortality outcomes that are specifically related to COPD exacerbations in China.\u003c/p\u003e \u003cp\u003ePrevious studies have indicated that the causes of death in COPD patients vary depending on the severity of disease (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Cardiac diseases and malignancies, particularly lung cancer, are predominant causes of mortality in patients with mild COPD. As COPD severity increases, however, deaths due to respiratory diseases become more prevalent (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). COPD exacerbations may also be considered a driving factor for cardiovascular (CV) events (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Data from a nationwide COPD registry in Denmark showed that the odds of a CV event were higher in patients with moderate and severe exacerbations compared to those with no exacerbations (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The increased risk of CV events in patients with COPD after an exacerbation may be attributed to shared pathophysiologic mechanisms and specific impacts of the exacerbation event (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Currently, there is insufficient data in China to determine the specific causes of mortality associated with COPD exacerbations, as well as to support a clear understanding on the relationship between COPD exacerbations and mortality rates or CV events.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to describe the burden of mortality and severe CV events among Chinese COPD patients and further characterize the associations between COPD exacerbations and death by providing real-world evidence. Part of the results of this study have been previously reported in ATS 2024 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a secondary observational retrospective longitudinal cohort study among Chinese patients diagnosed with COPD in routine clinical practice.\u003c/p\u003e\n\u003cp\u003eThe Yinzhou regional electronic health records database was used for the study. Yinzhou database is linked to all public health institutions in Yinzhou District of Ningbo, covering data from health information systems in public hospital, community health center, health surveillance system, and death registry from Center for Disease Control and Prevention (CDC) in Zhejiang Province, China. These health information systems in Yinzhou have covered nearly all health-related activities of residents within this region since 2009, from birth to death, across all age groups\u0026nbsp;(13). The Yinzhou database was standardized to the Observational Medical Outcomes Partnership Common Data Model\u0026nbsp;(OMOP CDM) version 5, which is maintained by the Observational Health Data Sciences and Informatics\u0026nbsp;(OHDSI) Network\u0026nbsp;(14, 15).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study population consisted of a cohort of real-world patients with COPD captured in the Yinzhou database. Patients were screened for eligibility between 1\u003csup\u003est\u003c/sup\u003e January 2014 and 1\u003csup\u003est\u003c/sup\u003e March 2022 (the screening period). Patients were considered eligible if they met the following criteria: 1) had \u0026ge; 2 primary diagnosis items/codes for COPD in the outpatient setting or had \u0026ge;1 primary or secondary diagnosis items/codes for COPD in the inpatient setting during the screening period; 2) aged \u0026ge; 40 years upon the first identified diagnosis item/code of COPD; 3) had baseline data continuously available for at least 24 months before the first identified diagnosis item/code of COPD. The date of the first identified COPD diagnosis occurring between the screening period was defined as the index date. Baseline data was obtained from the 24-month pre-index baseline period (including index date). Patients would be excluded if they had a record of Alpha-1 antitrypsin deficiency at baseline. Follow-up was from the day after the index date until (a) 1\u003csup\u003est\u003c/sup\u003e March 2023 (administrative right censoring); (b) loss to follow-up (the last clinical event date recorded in the database); (c) all-cause death (death data was available until 30 Jun 2022), whichever came first (\u003cstrong\u003e\u003cem\u003eFigure 1\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExposure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe exposure of interest was the frequency and severity of COPD exacerbation during the 24-month baseline period, and was classified as follows: no exacerbations, one moderate exacerbation only, \u0026ge;2 moderate exacerbations (none severe), and \u0026ge;1 severe exacerbation. A moderate exacerbation was defined as an outpatient visit to a physician (general practitioner, pulmonologist or internist)\u0026nbsp;for COPD\u0026nbsp;with a new prescription of systemic corticosteroids (intravenous or oral corticosteroids) and/or antibiotics for respiratory infections. To ensure that these drugs were intended to treat an exacerbation, only prescriptions by general practitioners, pulmonologists or internists were considered. A severe exacerbation was defined as record of hospitalization for COPD exacerbation, which referred to patients with 1) international classification of diseases (ICD)-10 codes of J44, J44.0, or J44.1 as the primary discharge code; or 2) an ICD-10 code of J44.0 as a secondary discharge code (indicating an acute exacerbation that occurred during the hospital stay)\u0026nbsp;(16). Two consecutive exacerbations occurring within 14 days were considered as one single exacerbation and the higher level of severity characterized the episode.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy outcomes included all-cause deaths and severe CV events occurred during study follow-up period and recorded in the database.\u003c/p\u003e\n\u003cp\u003eAll-cause deaths\u0026nbsp;were categorized into four groups based on the causes of death retrieved from the death registry regulated by CDC in Zhejiang Province, namely: 1) CV-related death, 2) respiratory death, 3) death of other causes, 4) death of unknown causes.\u003c/p\u003e\n\u003cp\u003eA\u0026nbsp;severe CV event\u0026nbsp;was defined as a hospitalization with a primary or secondary discharge code for one of the following events of interest\u0026nbsp;(ICD-10 codes for the following CV events were provided in \u003cstrong\u003eAdditional Table 1\u003c/strong\u003e), including 1) acute coronary syndrome, 2) heart failure decompensation, 3) cerebral ischemia, 4) arrythmia, and 5) CV-related death.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe statistical program SQL and R Project for Statistical Computing, version 4.2.2 or higher were used for analysis, establishing a statistical significance for values of p \u0026lt; 0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe full COPD cohort was characterized in terms of demographic and clinical characteristics during the baseline period, including age at index date, gender, body mass index (BMI), smoking status, education level, comorbidities, history of COPD exacerbations, and concomitant medications. Further details on the definition of patient baseline characteristics were shown in \u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e. Continuous variables were described using the mean (standard deviation [SD]), median (interquartile range [IQR]), minimum and maximum values. Dichotomous/categorical variables were described using n (%) of each category. Count variables were described as continuous variables, using n (%) of each count category, where appropriate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDeaths and severe CV events occurring during the follow-up period were described in terms of number (%) of patients with all-cause and cause-specific death, and number (%) of patients with \u0026ge;1 severe CV event of any type and specific type.\u0026nbsp;The crude incidence rate and 95% confidence interval\u0026nbsp;(CI) of all-cause and cause-specific death and first severe CV event of any type and specific type were reported overall, and by different baseline exacerbation categories.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCox proportional hazards model was used with binary indicators of each group of baseline COPD exacerbation (no exacerbations as reference group) as covariates to investigate the association between baseline exacerbation frequency and severity and all-cause of death. The model was fitted with and without adjustment for confounders. The confounders were selected from baseline characteristics listed in \u003cstrong\u003eAdditional Table 2\u003c/strong\u003e, based on recommendation from medical and evidence from previous studies\u0026nbsp;(8). Smoking status was not included in the adjusted model due to uncertainty regarding the missing rate. The full list of covariates incorporated in the Cox proportional hazard model was summarized in a footnote below \u003cstrong\u003eTable 4\u003c/strong\u003e. Patients with missing values in baseline covariates were not included in the final model. No imputation was performed.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFrom 1 Jan 2014 to 1 Mar 2022 (screening period), a total of 14,713 patients with COPD were included in the study for final analysis. The patient attrition flowchart for COPD patients who fulfilled the study inclusion/exclusion criteria is summarized in \u003cstrong\u003eFigure 2\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDetails of patient baseline characteristics are shown in \u003cstrong\u003eTable 1 (at the end of the document text)\u003c/strong\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAmong the included 14,713 patients,\u0026nbsp;9,862 (67.0%) were male. The mean (SD) age of these patients was 72.0 (11.5). The numbers of patients with no exacerbations, only one moderate exacerbation, \u0026ge; 2 moderate exacerbations (none severe), and \u0026ge; 1 severe exacerbation during the 24-month baseline period were 8,913 (60.6%), 3,055 (20.8%), 739 (5.0%), and 2,006 (13.6%), respectively. The median (IQR) follow-up duration was\u0026nbsp;41.3 (47.4)\u0026nbsp;months. There were 5,991 (40.7%) patients with an education level of secondary school and above. Hypertension (71.9%) was the most common comorbidity among these patients. In terms of comedications at baseline, 5,029 (34.2%) patients received long-acting COPD treatments, while 3,657 (24.9%) patients received short-acting COPD treatments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncidence of deaths overall and by COPD exacerbation history at baseline\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in \u003cstrong\u003eTable 2\u003c/strong\u003e, a total of 2,951 (20.1%) patients died during a median (IQR) follow-up period of\u0026nbsp;41.3 (47.4)\u0026nbsp;months. Specifically, most patients (1,264/14,710, 8.6%) died from respiratory diseases, followed by death due to other causes, death from CV-related causes, and death from unknown causes. The crude incidence rate for all-cause death was 5.17 (95% CI: 4.98, 5.36) per 100 person-years. The crude incidence rate of experiencing respiratory death was 2.21 (95% CI: 2.09, 2.34) per 100 person-years, which was also higher than that of other categories of death.\u003c/p\u003e\n\u003cp\u003eThe proportion of patients who experienced all-cause death increased with higher baseline frequency or severity of COPD exacerbations\u0026nbsp;(\u003cstrong\u003eTable 3\u003c/strong\u003e). The crude incidence rate of all-cause death peaked at 10.08 (95% CI: 9.26, 10.95) per 100 person-years among patients with \u0026ge;1 severe exacerbation. As for cause-specific deaths, the crude incidence rate of respiratory death increased with higher frequency and severity of baseline COPD exacerbation, from 1.58 (95% CI:1.44, 1.72) per 100 person-years in patients with no exacerbations to 5.21 (95% CI: 4.67, 5.79) per 100 person-years in patients with \u0026ge;1 severe exacerbation. The crude incidence rate of respiratory death was elevated across all baseline COPD exacerbation\u0026nbsp;categories, including those with one moderate exacerbation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncidence of severe CV events overall and by COPD exacerbation history at baseline\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in \u003cstrong\u003eTable 2\u003c/strong\u003e, a total of 2,394 patients (20.1%) experienced severe CV events during the follow-up period, with a crude incidence rate of 5.48 (95% CI: 5.26, 5.70) per 100 person-years. Heart failure decompensation was the most common severe CV event in these patients (1,521/13,016, 11.7%), followed by arrythmias (1,199/13,403, 8.9%), cerebral ischemia (769/13,854, 5.6%), CV-related death (682/14,710, 4.6%), and acute coronary syndrome (48/14,647, 0.3%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe crude incidence rate (per 100 person-years) of severe CV events increased with higher baseline frequency or severity of COPD exacerbations, from 4.80 (95% CI: 4.53, 5.07) in patients with no exacerbations to 8.54 (95% CI: 7.61, 9.55) in patients with \u0026ge;1 severe exacerbation. Patients with \u0026ge;1 severe exacerbation exhibited the highest incidence rates of heart failure decompensation, cerebral ischemia, arrythmias, and CV-related death (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between all-cause death and baseline COPD exacerbation history\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e summarized the hazard ratios (HR) for all-cause deaths by different COPD exacerbation frequencies and severities at baseline. In the unadjusted Cox model, patients with \u0026ge;2 moderate exacerbations (HR: 1.26, 95% CI: 1.10,1.46) or \u0026ge;1 severe exacerbation (HR: 2.19, 95% CI: 1.99, 2.40) were at higher risk of all-cause death compared with the reference group (patients with no exacerbations). After adjusting for confounders, patients with \u0026ge;1 severe exacerbation still showed an increased risk (HR: 1.26, 95%CI: 1.14, 1.38) of all-cause death, while the increased risk of death in patients with \u0026ge;2 moderate exacerbations was no longer statistically significant. Of note, patients with one moderate exacerbation exhibited a decreased risk (HR: 0.88, 95% CI: 0.80, 0.97) of all-cause death compared with the reference group in the confounder-adjusted model.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study\u0026nbsp;described the cumulative incidence and incidence rate of death and severe CV events among Chinese COPD patients and further explored the association between COPD exacerbations and death.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe overall incidence of all-cause death reported in our study (20.1%) is similar with a previous nationwide study in Korea, which reported an overall mortality rate of 26.2% and a 5-year mortality rate of 25.4%\u0026nbsp;(17). However, in some other studies, a notably higher mortality rate was reported. A study in Italy focusing on patients aged 65 and older found a COPD mortality rate of 56.9% after 12 years of follow-up\u0026nbsp;(18). Additionally, in a study including patients aged 65 to 100 years, the COPD mortality rates at 5, 10, and 15 years were reported as 32%, 62%, and 75%, respectively\u0026nbsp;(19). The relatively lower incidence of death in our study may be attributed to the lower age limit of 40 and above, and a shorter median follow-up time of 3.4 years (41.3 months). The two leading causes of death reported in our study were respiratory and CV related, accounting for 42.8% and 23.1% of deaths, respectively. However, there are variations in the distribution of causes of death across different studies. For instance, a prospective cohort study in Spain found that deaths from respiratory causes and CV diseases accounted for 67.2% and 10.3% of deaths, respectively\u0026nbsp;(20), while another cohort study in England reported an overall mortality rate of 28.8%, with COPD-related and CV-related deaths accounting for 25.7% and 23.3% of all deaths, respectively\u0026nbsp;(21). Since COPD patients often die from multiple causes, and the cause definitions vary across studies, it has been suggested that all-cause mortality is likely the most suitable measure of mortality to use in COPD\u0026nbsp;(22). In addition, many patients in our study had comorbid CV diseases at baseline, such as hypertension, coronary artery disease, and heart failure. The physiological stressors and inflammatory responses related to COPD exacerbations may aggravate these pre-existing CV conditions, potentially contributing to the high incidence of CV-related deaths.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn previous research, COPD exacerbations have been shown to be associated with increased risk of mortality in patients with COPD.\u0026nbsp;One retrospective study reported one-year mortality rate of 26.2% and five-year mortality rate of 64.3% for patients admitted for acute exacerbations of COPD\u0026nbsp;(23). The EXACOS-UK study found that the rate of all-cause mortality and COPD-related mortality among COPD patients was increased with more frequent and severe baseline COPD exacerbations\u0026nbsp;(24). Another cohort study in England demonstrated both increased frequency and severity of COPD exacerbations were associated with higher risk of COPD-related mortality (\u0026ge;2 exacerbations vs none, adjusted HR: 1.64, 95% CI: 1.57,1.71; 1 severe vs none, adjusted HR: 2.17, 95% CI: 2.04, 2.31)\u0026nbsp;(21). \u0026nbsp;In another study in Spain, the patients with the greatest mortality risk were those with three or more acute COPD exacerbations (HR: 4.13, 95% CI: 1.80, 9.41)\u0026nbsp;(20). Our study revealed that the mortality rate was higher in patients with COPD exacerbations at baseline, with crude incidence rate of death being highest in those with severe exacerbation(s), which aligned with existing evidence. Our study also found that the crude incidence rate of respiratory death increased with higher frequency and severity of baseline COPD exacerbation, which was supported by previous studies that deaths from respiratory diseases are becoming more common as the severity of COPD increases\u0026nbsp;(7). In our confounder-adjusted Cox model, patients with history of any severe COPD exacerbation had a significantly higher risk of all-cause death (adjusted HR: 1.26, 95% CI: 1.14, 1.38), compared with patients without history of COPD exacerbation, which was consistent with previous studies. However, no significant association was observed between patients with \u0026ge;2 moderate exacerbations at baseline and all-cause mortality (adjusted HR: 1.07, 95% CI: 0.92, 1.23), while a lower risk of death was observed in patients with one moderate exacerbation at baseline (adjusted HR: 0.88, 95% CI: 0.80, 0.97) compared to patients with no exacerbations, which may seem paradoxical. Firstly, this may be partially due to our definition of\u0026nbsp;a moderate exacerbation by outpatient visiting for COPD with a new prescription of systemic corticosteroids and/or antibiotics for respiratory infections. Some patients experiencing moderate exacerbations may have opted not to seek medical treatment, leading to a misclassification of individuals with a moderate exacerbation being counted as having no exacerbations.\u0026nbsp;This may occur more frequently in patients with infrequent exacerbations (only 1 moderate) than those with frequent (\u0026ge;2 moderate) exacerbations. Secondly, individuals who sought medical attention were more likely to adhere to prescribed treatments\u0026nbsp;and seek healthcare when experiencing exacerbation symptoms, indicating a higher level of health awareness and literacy in managing COPD, potentially associated with improved overall health and reduced mortality risk\u0026nbsp;(25). Thirdly, our study\u0026apos;s definition implied that patients experiencing a moderate exacerbation may have received timely medical attention and appropriate pharmacological treatment, contributing to better COPD and comorbidity management. Prompt medical care and monitoring during a moderate exacerbation might have led to improved overall health outcomes and reduced mortality risk compared to patients with no exacerbations\u0026nbsp;(26).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings highlighted the significant burden of severe CV events in patients with COPD. The overall cumulative incidence of severe CV events in our study was 20.1%, with a crude incidence rate of 5.48 per 100 person-years. Heart failure decompensation was the most common CV event observed. These findings are consistent with previous studies that have demonstrated an increased burden of CV diseases in COPD patients\u0026nbsp;(11, 27-31).\u0026nbsp;The increased risk of CV events in COPD patients has been attributed to shared risk factors (environmental and/or genetic) and shared pathophysiological pathways\u0026nbsp;(32).\u0026nbsp;Our study also revealed that patients with baseline COPD exacerbation histories had a higher incidence rate of severe CV events.\u0026nbsp;Similarly, data from the PHARMO Data Network in the Netherlands demonstrated that the risk of severe CV events was significantly increased and remained elevated for over one year after a moderate or severe COPD exacerbation\u0026nbsp;(8). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results in our study emphasize the need for better COPD management strategies that can be provided earlier in the course of the disease, particularly for those who experience severe COPD exacerbations. The notable risk of CV-related mortality and incidence of severe CV events in COPD patients with exacerbations may require even more clinical awareness and active measures to treat or prevent cardiovascular complications in this population.\u003c/p\u003e\n\u003cp\u003eThere are some limitations to our study design. First, the definition of a moderate exacerbation in our study encompassed an outpatient visit for COPD with a new prescription or purchase of systemic corticosteroids and/or antibiotics for respiratory infections. This definition might have led to an overestimation of the population in the subgroup with no exacerbations, as some patients experiencing exacerbations may have opted not to seek medical treatment. Second, as an observational study, we have to acknowledge that residual confounding cannot be entirely eliminated, and there was high rate of missing values in FEV1 and smoking status, whereas these two factors are essential in defining and assessing COPD (33, 34). The absence of comprehensive data on these variables could introduce bias into the analysis and impact the accuracy of the findings. Lastly, Yinzhou is a developed district of Ningbo city, located in East China. Research on disease burden in China has demonstrated that Eastern provinces exhibit a lower burden of COPD, including lower incidence, prevalence, and mortality rates (3). Therefore, caution should be taken when applying the study findings to other areas with potentially different disease burdens and clinical practices.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eTo our knowledge, this study was the largest retrospective cohort study investigating mortality and CV outcomes among COPD patients in China. The study reported an incidence rate of death of 5.17 per 100 person-years, with respiratory disease being the most common cause of death. Patients with history of severe COPD exacerbation(s) at baseline had a higher risk of death and severe CV events compared with patients without an exacerbation. These findings also yielded significant implications stressing the importance of clinical practice and patient management within the field of COPD in China and globally.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eBody Mass Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eCDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eCenter for Disease Control and Prevention\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eChronic Obstructive Pulmonary Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eCardiovascular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eHazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eICD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eInternational Classification of Diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eICS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eInhaled Corticosteroids\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eInterquartile Range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eLABA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eLong-Acting \u0026beta;2 Agonists\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eLAMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eLong-Acting Muscarinic Antagonists\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eOHDSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eObservational Health Data Sciences and Informatics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eOMOP CDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eObservational Medical Outcomes Partnership Common Data Model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eSABA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eShort-Acting \u0026beta;2 Agonists\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eSAMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eShort-Acting Muscarinic Antagonist\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.958333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.04166666666667%\" valign=\"top\"\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA protocol for this research was approved by the Peking University Institutional Review Board (IRB00001052-23112) and the Medical Ethics Committee of Zhongshan Hospital, Fudan University (B2023-206(2)).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to the protection of personal information and requirements from the data source.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by AstraZeneca UK Limited.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eF.S. and Y.S. participated in study conceptualization and design. D.H., Z.L., X.L., P.S., W.L., M.Z., I.C., H.L., S.Z., F.S., Y.C., and Y.S. participated in data analysis and interpretation. F.S. and Y.S. participated in manuscript draft. D.H., Z.L, X.L., W.L., I.C., F.S., and Y.S. participated in manuscript editing and revision. All authors approved the final version for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Jennifer Quint, Professor of Respiratory Epidemiology at the School of Public Health, Imperial College London, for her valuable professional advice. Medical writing and editorial support were provided by Xiaoqing Wang, Frank Lu, and Savannah Gui of IQVIA, which received funding from AstraZeneca UK Limited.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChristenson SA, Smith BM, Bafadhel M, Putcha N. Chronic obstructive pulmonary disease. Lancet. 2022;399(10342):2227-42.\u003c/li\u003e\n\u003cli\u003eSafiri S, Carson-Chahhoud K, Noori M, Nejadghaderi SA, Sullman MJM, Ahmadian Heris J, et al. Burden of chronic obstructive pulmonary disease and its attributable risk factors in 204 countries and territories, 1990-2019: results from the Global Burden of Disease Study 2019. Bmj. 2022;378:e069679.\u003c/li\u003e\n\u003cli\u003eYin P, Wu J, Wang L, Luo C, Ouyang L, Tang X, et al. The Burden of COPD in China and Its Provinces: Findings From the Global Burden of Disease Study 2019. Front Public Health. 2022;10:859499.\u003c/li\u003e\n\u003cli\u003eJanson C, Nwaru BI, Wiklund F, Telg G, Ekstr\u0026ouml;m M. Management and Risk of Mortality in Patients Hospitalised Due to a First Severe COPD Exacerbation. Int J Chron Obstruct Pulmon Dis. 2020;15:2673-82.\u003c/li\u003e\n\u003cli\u003eLiu W, Wang W, Liu J, Liu Y, Meng S, Wang F, et al. Trend of Mortality and Years of Life Lost Due to Chronic Obstructive Pulmonary Disease in China and Its Provinces, 2005-2020. Int J Chron Obstruct Pulmon Dis. 2021;16:2973-81.\u003c/li\u003e\n\u003cli\u003eGarcia-Aymerich J, Serra Pons I, Mannino DM, Maas AK, Miller DP, Davis KJ. Lung function impairment, COPD hospitalisations and subsequent mortality. Thorax. 2011;66(7):585-90.\u003c/li\u003e\n\u003cli\u003eBerry CE, Wise RA. Mortality in COPD: causes, risk factors, and prevention. Copd. 2010;7(5):375-82.\u003c/li\u003e\n\u003cli\u003eSwart KMA, Baak BN, Lemmens L, Penning-van Beest FJA, Bengtsson C, Lobier M, et al. Risk of cardiovascular events after an exacerbation of chronic obstructive pulmonary disease: results from the EXACOS-CV cohort study using the PHARMO Data Network in the Netherlands. Respir Res. 2023;24(1):293.\u003c/li\u003e\n\u003cli\u003eClaus V, Sami S, Edeltraut G, Don S, Nathaniel H, Nicolas M, et al. Increased risk of severe cardiovascular events following exacerbations of COPD: a multi-database cohort study. European Respiratory Journal. 2023;62(suppl 67):PA3013.\u003c/li\u003e\n\u003cli\u003eL\u0026oslash;kke A, Hilberg O, Lange P, Ibsen R, Telg G, Stratelis G, et al. Exacerbations Predict Severe Cardiovascular Events in Patients with COPD and Stable Cardiovascular Disease-A Nationwide, Population-Based Cohort Study. Int J Chron Obstruct Pulmon Dis. 2023;18:419-29.\u003c/li\u003e\n\u003cli\u003eMorgan AD, Zakeri R, Quint JK. Defining the relationship between COPD and CVD: what are the implications for clinical practice? Ther Adv Respir Dis. 2018;12:1753465817750524.\u003c/li\u003e\n\u003cli\u003eLi W, Liu Z, Zhang M, Li X, Cheang I, Sun F, et al. Exacerbations of Chronic Obstructive Pulmonary Disease and Cardiovascular Diseases (EXACOS-CV): A Database Study in China on Mortality and Severe Cardiovascular Events. A48 COPD EXACERBATIONS AND HOSPITALIZATIONS: DETERMINANTS AND DRIVERS. p. A1866-A.\u003c/li\u003e\n\u003cli\u003eLin H, Tang X, Shen P, Zhang D, Wu J, Zhang J, et al. Using big data to improve cardiovascular care and outcomes in China: a protocol for the CHinese Electronic health Records Research in Yinzhou (CHERRY) Study. BMJ Open. 2018;8(2):e019698.\u003c/li\u003e\n\u003cli\u003eHripcsak G, Duke JD, Shah NH, Reich CG, Huser V, Schuemie MJ, et al. Observational Health Data Sciences and Informatics (OHDSI): opportunities for observational researchers. Studies in health technology and informatics. 2015;216:574.\u003c/li\u003e\n\u003cli\u003eOverhage JM, Ryan PB, Reich CG, Hartzema AG, Stang PE. Validation of a common data model for active safety surveillance research. Journal of the American Medical Informatics Association. 2012;19(1):54-60.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. ICD-10 Version:2019 2019 [Available from: https://icd.who.int/browse10/2019/en.\u003c/li\u003e\n\u003cli\u003ePark SC, Kim DW, Park EC, Shin CS, Rhee CK, Kang YA, et al. Mortality of patients with chronic obstructive pulmonary disease: a nationwide populationbased cohort study. Korean J Intern Med. 2019;34(6):1272-8.\u003c/li\u003e\n\u003cli\u003eTesta G, Cacciatore F, Bianco A, Della-Morte D, Mazzella F, Galizia G, et al. Chronic obstructive pulmonary disease and long-term mortality in elderly subjects with chronic heart failure. Aging Clin Exp Res. 2017;29(6):1157-64.\u003c/li\u003e\n\u003cli\u003eSorino C, Pedone C, Scichilone N. Fifteen-year mortality of patients with asthma-COPD overlap syndrome. Eur J Intern Med. 2016;34:72-7.\u003c/li\u003e\n\u003cli\u003eSoler-Catalu\u0026ntilde;a JJ, Mart\u0026iacute;nez-Garc\u0026iacute;a MA, Rom\u0026aacute;n S\u0026aacute;nchez P, Salcedo E, Navarro M, Ochando R. Severe acute exacerbations and mortality in patients with chronic obstructive pulmonary disease. Thorax. 2005;60(11):925-31.\u003c/li\u003e\n\u003cli\u003eHannah W, Kieran JR, Jennifer KQ. Cause-specific mortality in COPD subpopulations: a cohort study of 339 647 people in England. Thorax. 2023:thorax-2022-219320.\u003c/li\u003e\n\u003cli\u003eCazzola M, MacNee W, Martinez FJ, Rabe KF, Franciosi LG, Barnes PJ, et al. Outcomes for COPD pharmacological trials: from lung function to biomarkers. Eur Respir J. 2008;31(2):416-69.\u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a-Sanz MT, C\u0026aacute;nive-G\u0026oacute;mez JC, Sen\u0026iacute;n-Rial L, Aboal-Vi\u0026ntilde;as J, Barreiro-Garc\u0026iacute;a A, L\u0026oacute;pez-Val E, et al. One-year and long-term mortality in patients hospitalized for chronic obstructive pulmonary disease. J Thorac Dis. 2017;9(3):636-45.\u003c/li\u003e\n\u003cli\u003eWhittaker H, Rubino A, M\u0026uuml;llerov\u0026aacute; H, Morris T, Varghese P, Xu Y, et al. Frequency and severity of exacerbations of COPD associated with future risk of exacerbations and mortality: a UK routine health care data study. International Journal of Chronic Obstructive Pulmonary Disease. 2022:427-37.\u003c/li\u003e\n\u003cli\u003eOmachi TA, Sarkar U, Yelin EH, Blanc PD, Katz PP. Lower health literacy is associated with poorer health status and outcomes in chronic obstructive pulmonary disease. J Gen Intern Med. 2013;28(1):74-81.\u003c/li\u003e\n\u003cli\u003eSimpson SH, Eurich DT, Majumdar SR, Padwal RS, Tsuyuki RT, Varney J, et al. A meta-analysis of the association between adherence to drug therapy and mortality. Bmj. 2006;333(7557):15.\u003c/li\u003e\n\u003cli\u003eSchneider C, Bothner U, Jick SS, Meier CR. Chronic obstructive pulmonary disease and the risk of cardiovascular diseases. Eur J Epidemiol. 2010;25(4):253-60.\u003c/li\u003e\n\u003cli\u003eChen W, Thomas J, Sadatsafavi M, FitzGerald JM. Risk of cardiovascular comorbidity in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. Lancet Respir Med. 2015;3(8):631-9.\u003c/li\u003e\n\u003cli\u003eMiller J, Edwards LD, Agust\u0026iacute; A, Bakke P, Calverley PM, Celli B, et al. Comorbidity, systemic inflammation and outcomes in the ECLIPSE cohort. Respir Med. 2013;107(9):1376-84.\u003c/li\u003e\n\u003cli\u003eDonaldson GC, Hurst JR, Smith CJ, Hubbard RB, Wedzicha JA. Increased risk of myocardial infarction and stroke following exacerbation of COPD. Chest. 2010;137(5):1091-7.\u003c/li\u003e\n\u003cli\u003eReilev M, Potteg\u0026aring;rd A, Lykkegaard J, S\u0026oslash;ndergaard J, Ingebrigtsen TS, Hallas J. Increased risk of major adverse cardiac events following the onset of acute exacerbations of COPD. Respirology. 2019;24(12):1183-90.\u003c/li\u003e\n\u003cli\u003eVishanna B, Andrea SM, Alice MT, Michael N. Cardiovascular disease in chronic obstructive pulmonary disease: a narrative review. Thorax. 2022;77(9):939.\u003c/li\u003e\n\u003cli\u003eG\u0026uuml;lşen A. Pulmonary Function Changes in Chronic Obstructive Pulmonary Disease Patients According to Smoking Status. Turk Thorac J. 2020;21(2):80-6.\u003c/li\u003e\n\u003cli\u003eDoherty DE. A review of the role of FEV1 in the COPD paradigm. Copd. 2008;5(5):310-8.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 1\u003c/em\u003e\u003c/strong\u003e. \u003cem\u003eBaseline characteristics of the full COPD cohort overall and by 24-month baseline COPD exacerbation status.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" style=\"margin-right: calc(0%); width: 100%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" rowspan=\"3\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHas no exacerbations during baseline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHas 1 moderate exacerbation during baseline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHas \u0026ge;2 moderate exacerbations during baseline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHas \u0026ge;1 severe exacerbation(s)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;during baseline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=14,713\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=8,913\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=3,055\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=739\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=2,006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.642857142857142%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge in years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"bottom\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emean [SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e72.0 [11.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e70.9 [11.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e71.5 [11.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e72.7 [10.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e77.4 [9.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emedian [IQR]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e73.0 [17.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e71.0 [17.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e72.0 [16.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e74.0 [15.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e79.0 [13.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emin, max\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e40.0, 101.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e40.0, 101.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e40.0, 99.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e42.0, 96.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e42.0, 101.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"bottom\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e9,862 (67.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e5,822 (65.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e2,175 (71.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e522 (70.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1,343 (66.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e4,804 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e3,067 (34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e873 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e215 (29.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e649 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e47 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e24 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e7 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e2 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e14 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e# of moderate exacerbations during baseline\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e10,533 (71.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1,620 (80.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"bottom\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e3,285 (22.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e3,055 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e230 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u0026ge;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e895 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e739 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e156 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e# of severe exacerbations during baseline\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e12,707 (86.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"bottom\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e1,888 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1,888 (94.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u0026ge;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e118 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e118 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e# of moderate/severe exacerbations during baseline\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e8,913 (60.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"bottom\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e4,720 (32.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e3,055 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1,665 (83.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u0026ge;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e1,080 (7.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e739 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e341 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFollow-up time in months\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"bottom\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emean [SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e46.6 [30.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e43.5 [28.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e55.9 [30.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e66.0 [33.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e39.0 [30.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emedian [IQR]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e41.3\u0026nbsp;[47.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e37.5 [41.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e52.9 [51.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e67.1 [60.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e33.3 [47.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emin\u003csup\u003e3\u003c/sup\u003e, max\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e0.0, 109.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e0.0, 109.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e0.1, 109.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0.3, 109.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e0.0, 109.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (recorded or height / weight derived) at baseline and closest to index date, kg/m\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e7,584 (51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e4,685 (52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1,559 (51.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e365 (49.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e975 (48.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emean [SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e23.1 [3.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e23.2 [3.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e22.9 [3.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e22.4 [3.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e22.7 [3.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emedian [IQR]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e22.9 [4.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e23.1 [4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e22.8 [4.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e22.1 [4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e22.3 [5.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003emin, max\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e9.0, 53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e9.0, 53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e12.0, 40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e15.0, 34.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e13.0, 45.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e7,129 (48.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e4,228 (47.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1,496 (49.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e374 (50.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1,031 (51.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e1,736 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e1,073 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e306 (10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e66 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e291 (14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eIlliteracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e1,832 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e970 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e379 (12.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e119 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e364 (18.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eElementary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e5,154 (35.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e2,989 (33.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1,129 (37.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e310 (41.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e726 (36.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eSecondary school and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e5,991 (40.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e3,881 (43.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1,241 (40.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e244 (33.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e625 (31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities (any time prior to index date, including index date)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"bottom\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eObesity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e11 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e6 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e3 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e2 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eDiabetes mellitus type-1 or -2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e1,939 (13.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e1,297 (14.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e310 (10.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e62 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e270 (13.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eAny Disorders of lipoprotein metabolism and other lipidaemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e5,902 (40.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e3,861 (43.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1,109 (36.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e224 (30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e708 (35.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eIschemic heart diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e6,293 (42.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e4,069 (45.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1,110 (36.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e261 (35.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e853 (42.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e10,572 (71.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e6,494 (72.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e2,043 (66.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e523 (70.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1,512 (75.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eHeart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e3,265 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e1,723 (19.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e501 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e200 (27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e841 (41.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003ePulmonary oedema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e8 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e6 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003ePulmonary hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e91 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e48 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e8 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e35 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eVenous thromboembolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e311 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e200 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e55 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e12 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e44 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eCerebrovascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e5,748 (39.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e3,730 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e994 (32.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e234 (31.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e790 (39.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eArrythmia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e4,096 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e2,592 (29.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e691 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e177 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e636 (31.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eCurrent asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e6,142 (41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e3,768 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e1,277 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e406 (54.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e691 (34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"bottom\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eChronic kidney disease, renal failure\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e572 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e406 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e71 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e17 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e78 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eAnxiety disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e3,437 (23.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e2,280 (25.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e636 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e126 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e395 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComedications (baseline, including index date)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" valign=\"bottom\" style=\"width: 15.3433%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"bottom\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eCOPD drug - Long-acting treatments\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e5,029 (34.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e3,258 (36.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e879 (28.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e218 (29.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e674 (33.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" valign=\"bottom\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eCOPD drug - Short-acting treatments\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e3,657 (24.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e1,755 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e685 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e279 (37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e938 (46.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eTheophylline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e1,890 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e905 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e354 (11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e130 (17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e501 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.857142857142854%\" style=\"width: 31.7597%;\"\u003e\n \u003cp\u003eCardiac drugs\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 15.3433%;\"\u003e\n \u003cp\u003e12,409 (84.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 16.309%;\"\u003e\n \u003cp\u003e7,454 (83.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 14.9142%;\"\u003e\n \u003cp\u003e2,570 (84.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 10.3004%;\"\u003e\n \u003cp\u003e677 (91.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\" style=\"width: 11.3734%;\"\u003e\n \u003cp\u003e1,708 (85.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Combined moderate and severe exacerbations within 14 days during baseline (including index date)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Follow-up time is defined as from the day after index date until the first occurrence of (a) 1 Mar 2023 (study end); (b) loss to follow-up in the database; or (c) all-cause death (death data was available until 30 June 2022)\u003c/p\u003e\n\u003cp\u003eFor patients who died on the index date or had no follow-up information after the index date, their follow-up time would be 0.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e All COPD drugs presented in the table only contain fixed dose products.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e Long-acting COPD treatments: ICS (Inhaled Corticosteroids), LAMA (Long-Acting Muscarinic Antagonists), LABA (Long-Acting \u0026beta;2 Agonists), ICS+LABA, LAMA+LABA, ICS+LAMA+LABA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u0026nbsp;\u003c/sup\u003eShort acting COPD treatments: SABA (Short-Acting \u0026beta;2 Agonists), SAMA (Short-Acting Muscarinic Antagonist)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e6\u003c/sup\u003e Cardiac drugs: antithrombotic and anticoagulants, cardiac therapy, antihypertensives, diuretics, beta blocking agents, calcium channel blockers, statins.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 2\u003c/em\u003e\u003c/strong\u003e. \u003cem\u003eIncidence rate of death and severe CV events during follow-up in full cohort.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal \u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude incidence rate\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(95% CI)\u003csup\u003e\u0026nbsp;+\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause death\u003csup\u003e\u0026amp;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e14,710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e2,951 (20.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e5.17 (4.98, 5.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eCV-related death\u003csup\u003e$\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e14,710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e682 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e1.19 (1.11, 1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eRespiratory death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e14,710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e1,264 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e2.21 (2.09, 2.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eDeath of other causes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e14,710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e939 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e1.64 (1.54, 1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eDeath of unknown causes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e14,710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e66 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e0.12 (0.09, 0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny severe CV event\u003csup\u003e\u0026amp;\u003c/sup\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e11896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e2,394 (20.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e5.48 (5.26, 5.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eAcute coronary syndrome\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e14647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e48 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e0.08 (0.06, 0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eHeart failure decompensation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e13016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e1,521 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e3.09 (2.94, 3.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eCerebral ischemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e13854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e769 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e1.45 (1.35, 1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\"\u003e\n \u003cp\u003eArrythmias\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e13403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\"\u003e\n \u003cp\u003e1,199 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003e2.36 (2.23, 2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e: For each outcome, the \u0026ldquo;Total\u0026rdquo; excluded patients who 1) had severe CV events at any time prior to or on the index date or 2) died on the index date or 3) had no follow-up information after the index date.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e+\u003c/sup\u003e: per 100 person-years\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026amp;\u003c/sup\u003e: The all-cause death and severe CV events referred to all deaths / events during the follow-up period (starting from one day after index date). Mortality data were only available until 30 Jun 2022.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e$\u003c/sup\u003e: Based on definition, CV-related death was one of the severe CV events.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CV: cardiovascular; CI: confidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 3\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. Incidence rate of death and severe CV events during follow-up by COPD exacerbation history during 24-month baseline.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with no exacerbations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with 1 moderate exacerbation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with \u0026ge; 2 moderate exacerbations (not severe)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with \u0026ge; 1 severe exacerbation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003eTotal\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003eCrude incidence rate\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(95% CI)\u003csup\u003e\u0026nbsp;+\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003eTotal\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003eCrude incidence rate\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(95% CI)\u003csup\u003e\u0026nbsp;+\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003eTotal\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003eCrude incidence rate\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(95% CI)\u003csup\u003e\u0026nbsp;+\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003eTotal\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003eCrude incidence rate\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(95% CI)\u003csup\u003e\u0026nbsp;+\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause death\u003csup\u003e\u0026amp;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e1,475 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e4.57\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.34, 4.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e3,055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e598 (19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e4.20\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(3.87, 4.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e226 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e5.56\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.86, 6.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e652 (32.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e10.01\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(9.26, 10.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eCV-related death\u003csup\u003e$\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e413 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e1.28\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.16, 1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e3,055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e107 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e0.75\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.62, 0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e33 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e0.81\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.56, 1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e129 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e1.98\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.65, 2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eRespiratory death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e510 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e1.58\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.44, 1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e3,055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e289 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e2.03\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.80, 2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e126 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e3.10\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.58, 3.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e339 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e5.21\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.67, 5.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eDeath of other causes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e524 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e1.62\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.49, 1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e3,055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e183 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e1.29\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.11, 1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e67 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e1.65\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.21, 2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e184 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e2.83\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.20, 3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eDeath of unknown causes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e28 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e0.09\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.06, 0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e3,055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e19 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e0.13\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.08, 0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e3 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e0.07\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.02, 0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e16 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e0.25\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.14, 0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny severe CV event\u003csup\u003e\u0026amp;\u003c/sup\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e7,324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e1,230 (16.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e4.80\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.53, 5.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e622 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e5.40 (4.99, 5.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e236 (37.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e7.88\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(6.91, 8.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e1,193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e306 (25.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e\u0026nbsp;8.54\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(7.61, 9.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eAcute coronary syndrome\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e32 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e0.10\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.07, 0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e3,050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e8 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e0.06\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.02, 0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e3 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e0.07\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.02, 0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e1,998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e5 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e0.08\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.03, 0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eHeart failure decompensation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e745 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e2.59\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.41, 2.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e393 (13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e3.09\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.79, 3.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e164 (24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e4.87\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.15, 5.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e1,407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e219 (15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e4.95\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.32, 5.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eCerebral ischemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e418 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e1.40\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.26, 1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e165 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e1.23\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.05, 1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e71 (9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e1.88\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.47, 2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e1,836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e115 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e2.00\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.65, 2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.053763440860216%\"\u003e\n \u003cp\u003eArrythmias\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e8,143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.451612903225806%\"\u003e\n \u003cp\u003e604 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e2.08\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.92, 2.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e2,902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e311 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\"\u003e\n \u003cp\u003e2.41\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.15, 2.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.301075268817204%\"\u003e\n \u003cp\u003e700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.526881720430108%\"\u003e\n \u003cp\u003e102 (14.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e2.80\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.28, 3.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e1,658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.376344086021505%\"\u003e\n \u003cp\u003e182 (11.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.67741935483871%\"\u003e\n \u003cp\u003e3.53\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(3.03, 4.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e: For each outcome, the \u0026ldquo;Total\u0026rdquo; excluded patients who 1) had severe CV events any time prior to or on the index date or 2) died on the index date or 3) had no follow-up information after the index date\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e+\u003c/sup\u003e: 100 per person-years\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026amp;\u003c/sup\u003e: The all-cause death and severe CV events referred to all deaths / events during the follow-up period (starting from one day after index date). Mortality data were only available until 30 Jun 2022.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e$\u003c/sup\u003e: Based on definition, CV-related death was one of the severe CV events.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CV: cardiovascular; CI: confidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 4.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eHazard ratios of deaths by baseline COPD exacerbation history.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"94%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.161616161616163%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.31313131313131%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline COPD exacerbation history\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(vs. no exacerbations)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnadjusted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.252525252525253%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.95876288659794%\"\u003e\n \u003cp\u003eNo exacerbations (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.49484536082474%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause death\u003csup\u003e\u0026amp;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.95876288659794%\"\u003e\n \u003cp\u003e1 moderate exacerbation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e0.94\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.85, 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e0.88\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.80, 0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27160493827161%\"\u003e\n \u003cp\u003e\u0026ge;2 moderate exacerbations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.753086419753085%\"\u003e\n \u003cp\u003e1.26\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.10, 1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.345679012345679%\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.28395061728395%\"\u003e\n \u003cp\u003e1.07\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.92, 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.345679012345679%\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27160493827161%\"\u003e\n \u003cp\u003e1 severe exacerbation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.753086419753085%\"\u003e\n \u003cp\u003e2.19\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.99, 2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.345679012345679%\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.28395061728395%\"\u003e\n \u003cp\u003e1.26\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.14, 1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.345679012345679%\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*: p\u0026lt;0.05; ** p\u0026lt;0.01; \u003csup\u003e+\u003c/sup\u003e: Adjusted for baseline covariates: age, gender, education level, comorbidities recorded any time prior to index date including index date (obesity, diabetes mellitus type-1 or -2, any disorders of lipoprotein metabolism and other lipidaemias, ischemic heart diseases, hypertensive diseases, heart failure, venous thromboembolism, arrythmia, current asthma, chronic kidney disease, mental illness), drug use at baseline (long-acting and short acting COPD drugs, theophylline, cardiac drugs)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026amp;\u003c/sup\u003e: In the model, the all-cause death referred to all deaths during the follow-up period (starting from the day after index date). Mortality data were only available until 30 Jun 2022.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CV: cardiovascular; COPD: chronic obstructive pulmonary disease; HR: hazard ratio; CI: confidence interval\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"respiratory-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rere","sideBox":"Learn more about [Respiratory Research](http://respiratory-research.biomedcentral.com/)","snPcode":"12931","submissionUrl":"https://submission.nature.com/new-submission/12931/3","title":"Respiratory Research","twitterHandle":"@RespiratoryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COPD, Exacerbations, All-cause death, Cardiovascular events","lastPublishedDoi":"10.21203/rs.3.rs-4678295/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4678295/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eChronic Obstructive Pulmonary Disease (COPD) exacerbations are associated with increased mortality and cardiovascular events. However, there is limited evidence on the relationship between COPD exacerbations and mortality and cardiovascular outcomes in China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study included Chinese COPD patients aged\u0026thinsp;\u0026ge;\u0026thinsp;40 years from the Yinzhou regional electronic health records database. Patients were screened for eligibility between 1 Jan 2014 and 1 Mar 2022, with the index date being the first identified COPD diagnosis within this timeframe. Patient characteristics and frequency and severity of COPD exacerbations were collected during the 24-month baseline period prior to the index date. Outcomes included all-cause mortality and severe cardiovascular events. The incidence of death and first severe cardiovascular event was reported overall, and by baseline exacerbation history. Cox proportional hazards models were employed to identify the association between baseline COPD exacerbation history and all-cause death.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 14,713 COPD patients were included, with a median follow-up duration of 41.3 months. During the follow-up period, 20.1% of patients died, with a crude incidence rate of 5.17 (95% CI: 4.98, 5.36) per 100 person-years. 20.1% of patients experienced severe cardiovascular events. The incidence of severe cardiovascular events increased with higher frequency and severity of baseline COPD exacerbations. Patients with history of severe COPD exacerbations exhibited an increased risk (adjusted HR: 1.26, 95%CI: 1.14, 1.38) of all-cause death compared with patients with no exacerbations.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe burden of all-cause death and severe cardiovascular events in COPD patients increased with higher frequency and severity of COPD exacerbations.\u003c/p\u003e","manuscriptTitle":"Impacts of COPD Exacerbation History on Mortality and Severe Cardiovascular Events among Patients with COPD in China: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-29 21:15:25","doi":"10.21203/rs.3.rs-4678295/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-09T23:38:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-19T18:14:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11737179994916815901835937111199748205","date":"2025-01-09T18:28:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"194593437938677309468346922901400097157","date":"2025-01-07T13:51:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-17T20:58:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"285021318356874579638869363587725678090","date":"2024-08-27T06:58:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-18T22:13:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-06T11:17:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-04T13:15:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Respiratory Research","date":"2024-07-03T07:07:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"respiratory-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rere","sideBox":"Learn more about [Respiratory Research](http://respiratory-research.biomedcentral.com/)","snPcode":"12931","submissionUrl":"https://submission.nature.com/new-submission/12931/3","title":"Respiratory Research","twitterHandle":"@RespiratoryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84f6374e-7b5f-4111-99bf-ea2f8ce1222a","owner":[],"postedDate":"July 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-28T16:03:59+00:00","versionOfRecord":{"articleIdentity":"rs-4678295","link":"https://doi.org/10.1186/s12931-025-03316-4","journal":{"identity":"respiratory-research","isVorOnly":false,"title":"Respiratory Research"},"publishedOn":"2025-07-23 15:58:12","publishedOnDateReadable":"July 23rd, 2025"},"versionCreatedAt":"2024-07-29 21:15:25","video":"","vorDoi":"10.1186/s12931-025-03316-4","vorDoiUrl":"https://doi.org/10.1186/s12931-025-03316-4","workflowStages":[]},"version":"v1","identity":"rs-4678295","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4678295","identity":"rs-4678295","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}