Respiratory, thoracic, and mediastinal adverse events associated with ticagrelor: A pharmacovigilance study based on FDA adverse event reporting system

Respiratory, thoracic, and mediastinal adverse events associated with ticagrelor: A pharmacovigilance study based on FDA adverse event reporting system | 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 Respiratory, thoracic, and mediastinal adverse events associated with ticagrelor: A pharmacovigilance study based on FDA adverse event reporting system Yuan Zeng, Lin Lu, Tao Jiang, Gang Wei, Wenwu Zheng, Gong Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6798394/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Jul, 2025 Read the published version in Naunyn-Schmiedeberg's Archives of Pharmacology → Version 1 posted 7 You are reading this latest preprint version Abstract Ticagrelor has been authorized for use as an antiplatelet therapy in individuals diagnosed with acute coronary syndrome (ACS). While numerous clinical trials have reported respiratory-related AEs associated with ticagrelor, real-world evidence from large populations remains limited. In this study, we aimed to assess the safety signals of respiratory, thoracic, and mediastinal disorders related to ticagrelor using data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS).This study utilized data from the FAERS database spanning 2011 to 2024. The reporting odds ratio (ROR) was used to quantify safety signals of respiratory, thoracic, and mediastinal adverse events associated with ticagrelor. Chi-square (χ²) or Fisher’s exact tests were used to compare serious versus non-serious cases. A prioritization scale was applied to rank the identified signals. Additionally, the Weibull distribution was used to model the time-to-onset(TTO) risk of AEs.A total of 4,605 respiratory, thoracic, and mediastinal AEs associated with ticagrelor were identified, with 25 significant safety signals detected. Patient sex (p < 0.001) and weight (p < 0.001) were significantly associated with increased risk of serious AEs, whereas no association was observed with age (p = 0.287). Stratified analyses confirmed the consistent association between ticagrelor and respiratory, thoracic, and mediastinal risks. Nine signals were classified as moderate clinical priority and sixteen as weak priority. Notably, all respiratory, thoracic, and mediastinal AEs exhibited an early failure pattern. This pharmacovigilance study systematically investigated ticagrelor-associated respiratory, thoracic, and mediastinal disorders to support clinicians in optimizing cardiovascular treatment strategies. ticagrelor respiratory system adverse events FAERS pharmacovigilance study Figures Figure 1 Figure 2 Figure 3 Introduction Ticagrelor, a P 2 Y 12 receptor blocker, plays a pivotal role in contemporary antithrombotic treatment when used alongside aspirin, particularly for patients with ACS or undergoing percutaneous coronary intervention (PCI)(Arora et al., 2019 ). It not only prevents thrombus propagation by inhibiting platelet activation, thereby reducing myocardial ischemic injury and thrombotic complications(Li et al., 2023 ; Rosa et al., 2016 ), but also alleviates endothelial dysfunction and atherosclerosis development by suppressing inflammatory activation of endothelial cells, offering long-term benefits in the prevention of adverse cardiovascular events(Rosa et al., 2016 ). With the rising global incidence of coronary artery disease, the use of antiplatelet agents has been expanding, and clinical demand for ticagrelor continues to grow. Therefore, a comprehensive investigation into the AEs and characteristics associated with ticagrelor is crucial to guide clinical decision-making. To date, several studies have evaluated the safety profile of ticagrelor. A recent pharmacovigilance study published in April 2024 systematically assessed ticagrelor-related AEs using the FAERS database, covering all reports from Q4 2010 to Q2 2023(Pan et al., 2024 ). One of the most commonly reported system organ classes (SOCs) in that study was respiratory, thoracic, and mediastinal disorders. In addition, ticagrelor has been associated with an increased risk of gastrointestinal bleeding and cardiac arrhythmias(Serebruany et al., 2013 ; Pujade et al., 2020 ). A clinical study reported that the incidence of ticagrelor discontinuation due to dyspnea was 6.4% at 3 months and 9.1% at 15 months post-PCI, indicating that approximately 1 in 10 patients may discontinue ticagrelor due to dyspnea(Angiolillo et al., 2023 ). Another randomized controlled trial found that the incidence of respiratory AEs was approximately four times higher in patients treated with ticagrelor compared to clopidogrel(Storey et al., 2010 ). Furthermore, rare respiratory-related adverse effects such as central sleep apnea and Cheyne–Stokes respiration have also been reported(Javaheri et al., 2024 ; Giannoni et al., 2016 ). Given these findings, this study focuses specifically on respiratory, thoracic, and mediastinal AEs associated with ticagrelor. Using disproportionality analysis based on the FAERS database, we quantitatively assessed the safety signals of these events. Additionally, we performed analyses of case severity, subgroup stratification, clinical priority ranking of signals, and time-to-onset(TTO) to further characterize the nature of these AEs. Method Study design and data sources A disproportionality analysis based on observational and retrospective data was employed to evaluate the potential association between ticagrelor and respiratory, thoracic, and mediastinal AEs. A disproportional signal was considered to exist if the proportion of target AEs was higher in the case group than in the non-case group, suggesting a possible association between the drug and the AE(Gatti et al., 2021 ). Based on the FDA approval date for ticagrelor, we analyzed all AE reports from Q3 2011 to Q4 2024 in which ticagrelor was identified as the primary suspected drug. Data extraction and descriptive analysis This research was based on data extracted from the FDA Adverse Event Reporting System (FAERS), which includes seven key components: demographics (DEMO), drug details (DRUG), reported reactions (REAC), outcomes (OUTC), sources of reports (RPSR), treatment timelines (THER), and indications for therapy (INDI)(Chen et al., 2024 ). All data were imported into MySQL software (v8.0; Oracle, Sweden). To ensure data quality, duplicate reports were proactively removed based on case ID prior to statistical analysis. For entries sharing the same case ID, only the record with the most recent FDA receipt date (FDA_DT) was retained. Ticagrelor-related cases were identified in the DRUG dataset using the drug names: Ticagrelor, AZD6140, Brilique, and Brilinta. Only reports where ticagrelor was labeled as the primary suspected drug (PS) were included. AE terms in the FAERS database are coded according to the Medical Dictionary for Regulatory Activities (MedDRA)(Meng et al., 2021 ). Our analysis included all Preferred Terms(PTs) under the "Respiratory, Thoracic and Mediastinal Disorders" SOC in MedDRA to capture AEs related to respiratory and thoracic complications. Eligible individual cases were identified and described according to patient characteristics, including sex, age, weight, reporting region, outcomes, reporter type, and report year. Outcomes were categorized into serious and non-serious events. Serious outcomes included death, life-threatening conditions, hospitalization, disability, and other serious outcomes. Notably, the total number of serious outcomes may exceed the number of AE reports, as individual patients may report multiple serious outcomes. The detailed process of data extraction, processing, and analysis is illustrated in Fig. 1 . Statistical analysis The ROR is a widely used algorithm in disproportionality analysis and is calculated based on a 2×2 contingency table (Supplementary Table S1 )(Salem et al., 2018 ). To minimize false-positive findings, only adverse events (AEs) reported 10 times or more were included in the ROR analysis. A signal was deemed significant if the lower bound of the 95% confidence interval (ROR 025 ) was greater than 1.In addition, serious outcomes were compared with non-serious outcomes to identify potential risk factors associated with AEs. Serious outcomes were defined as death, life-threatening conditions, hospitalization, disability, or other serious events. Group comparisons were performed using Pearson’s chi-square test(χ²) or Fisher’s exact test, with statistical significance defined as a two-tailed p-value less than 0.05.Stratified analyses were further conducted by sex, age, body weight, and reporter type (healthcare professionals vs. consumers) to explore whether the association between ticagrelor and respiratory, thoracic, and mediastinal disorders varied across different subgroups. Clinical prioritization of signals Disproportionality signals were categorized into three levels of clinical priority: (1) low, (2) moderate, and (3) high clinical priority(Gatti et al., 2021 ). Following previous literature, we performed a semi-quantitative scoring of disproportional signals based on four features: reporting rate, signal stability, reported case fatality rate, and clinical relevance(Cecco et al., 2024 ). We also reported the number of AE cases, ROR 025 , and the number of deaths. Based on the total score, AEs were classified into three categories of clinical priority: 0–2 (low), 3–5 (moderate), and 6–8 (high). Full details are provided in Supplementary Table S2. Time-to-onset analysis TTO was defined as the interval between the start date of ticagrelor treatment and the onset date of the AE(Shu et al., 2022 ). TTO data were analyzed using the Weibull shape parameter (WSP) test, and the results were summarized using the median, interquartile range (IQR), and Weibull distribution parameters. The Weibull distribution is characterized by a scale parameter (α) and a shape parameter (β)(Mazhar et al., 2021 ). The shape parameter β reflects the nature of risk over time: β 1 indicates an increasing hazard(Chen, 2024 ). We calculated the median TTO and WSP for signals with low or moderate clinical priority to assess the temporal risk profile of these AEs. These findings may offer insights into risk mitigation strategies and guide targeted monitoring interventions. Results Descriptive analysis Since the third quarter of 2011, after excluding duplicates, a total of 18,627,667 AE reports were retrieved from the FAERS database, among which 19,996 were associated with ticagrelor. Of these, 4,605 reports involved AEs related to respiratory, thoracic, and mediastinal disorders. Detailed clinical characteristics are presented in Table 1 .Among 4,356 cases with available sex information, males accounted for 60.45%, which was higher than females (39.55%). The majority of ticagrelor-associated respiratory, thoracic, and mediastinal AEs occurred in the elderly population, with 1,321 patients (61.52%) aged over 65 years. Body weight data were available for 1,887 patients: 47 (2.49%) weighed 100 kg. The median body weight was 79.4 kg.The United States reported the highest number of ticagrelor-associated AEs related to respiratory, thoracic, and mediastinal disorders. Hospitalization was the most frequently reported serious outcome, occurring in 1,278 cases (27.8%). Regarding reporter characteristics, the majority of reports (3,591; 94.67%) were submitted by non-health professionals, while only 202 (5.32%) were reported by healthcare professionals.From Q3 2011 to the end of the study period, the highest number of ticagrelor-related AEs in the respiratory, thoracic, and mediastinal disorders category was recorded in 2016, totaling 820 cases (17.8%). Table 1 Clinical characteristics of patients with ticagrelor-associated respiratory, thoracic, and mediastinal AEs. Characteristic Ticagrelor induced respiratory,thoracic and mediastinal AEs(n = 4,605) Ticagrelor induced overall AEs (n = 19,996) Availble number Value Availble numbe Value Gender,n(%) 4,356(94.59%) - 18,212(91.08%) - Female - 1,723(39.55%) - 6,801(37.34%) Male - 2,633(60.45%) - 11,411 (62.66%) Age(years),n(%) 2,147(46.62%) - 8,268(41.35%) - 85 - 80(3.72%) - 315(3.81%) Median(years) - 67.25 - 66.47 Weight(kg),n(%) 1,887(40.98%) - 5,430(27.16%) - 100 - 249(13.20%) 610 610(11.23%) Median(kg) - 79.4 - 78 Reported countries,n(%) 4,605(100%) - 19,996(100%) - US - 2,912(63.2%) - 11,229(56.2%) Non-US - 1,693(36.8%) - 8,767(43.8%) Outcomes,n(%) 4,605(100%) - 19,996(100%) - Non-serious outcome - 2,997(65.08%) - 4,780(23.90%) Serious outcome - 1,608(34.9%) - 15,216(76.10%) Death - 237(5.1%) - 2,724(13.6%) Life-threatening - 221(4.8%) - 1,246(6.2%) Hospitalization - 1,278(27.8%) - 5,692(28.5%) Disability - 59(1.3%) - 156(0.8%) Other serious outcomes - 1,193(25.9%) - 4780(23.9%) Reporters,n(%) 3,793(82.37%) - 16,895(84.49%) - Health professional - 202(5.32%) - 664(3.93%) Non-health professional - 3,591(94.67%) - 16,231(96.07%) Reporting years 4,605(100%) 19,996(100%) 2011Q3* - 7 (0.2%) - 39 (0.2%) 2012 - 197 (4.3%) - 886 (4.4%) 2013 - 266 (5.8%) - 1,258 (6.3%) 2014 - 266 (5.8%) - 1,427 (7.1%) 2015 - 373 (8.1%) - 1,762 (8.8%) 2016 - 820 (17.8%) - 3,853 (19.3%) 2017 - 467 (10.1%) - 2,157 (10.8%) 2018 - 535 (11.6%) - 1,997 (10.0%) 2019 - 335 (7.3%) - 1,343 (6.7%) 2020 - 345 (7.5%) - 1,148 (5.7%) 2021 - 313 (6.8%) - 1,107 (5.5%) 2022 - 242 (5.3%) - 790 (4.0%) 2023 - 232 (5.0%) - 999 (5.0%) 2024 - 207 (4.5%) - 1,230 (6.2%) *The third quarter of 2011 AEs,adverse events;n number of cases Disproportionality analysis We selected all PTs under the “Respiratory, Thoracic, and Mediastinal Disorders” SOC in the FAERS database that were associated with ticagrelor and had more than 10 reported cases, resulting in a total of 25 PTs. The five most frequently reported AEs in this category were dyspnea (n = 2,870), epistaxis (n = 472), cough (n = 354), asphyxia (n = 161), and exertional dyspnea (n = 134).The disproportionality analysis results for ticagrelor-associated respiratory, thoracic, and mediastinal disorders are shown in Fig. 2 . Across the entire FAERS database, the reporting frequency of these AEs was significantly higher for ticagrelor compared to non-ticagrelor drugs, with a lower bound of the 95% confidence interval of the ROR 025 of 2.52.As one of the most widely used antiplatelet agents, ticagrelor demonstrated the second strongest disproportionality signal in the “Respiratory, Thoracic, and Mediastinal Disorders” SOC among all 27 SOCs, following only the cardiovascular system. The corresponding ROR was 2.59 (95% CI: 2.52–2.66), as detailed in Supplementary Table S3. Serious vs. non-serious cases The differences in clinical characteristics between serious and non-serious reports are summarized in Table 2 . Among patients who experienced respiratory, thoracic, and mediastinal AEs during ticagrelor treatment, there were statistically significant differences in gender (p < 0.001) and body weight (p < 0.001) between serious and non-serious cases. However, the male-to-female ratio between the two groups was not significantly different (p = 0.251).A total of 27 AEs (p < 0.05) were more likely to be reported as serious, including dyspnea (p < 0.001), cough (p < 0.001), epistaxis (p = 0.02), dysphonia (p < 0.001), exertional dyspnea (p < 0.001), and oropharyngeal pain (p < 0.001). Conversely, 47 AEs were more likely to be reported as non-serious, such as chronic obstructive pulmonary disease (p = 0.870), wheezing (p = 0.450), sleep apnea syndrome (p = 0.060), asthma (p = 0.100), and suffocation feeling (p = 0.540).Notably, the majority of serious cases were associated with dyspnea events related to ticagrelor. Table 2 Differences in clinical characteristics of serious and non-serious reports. Serious cases Non-serious cases p -value Gender,n(%) - - - Female 648(0.38) 1,075(0.62) < 0.001 a Male 844(0.32) 1,789(0.68) Age(years),n(%) 85 20(0.04) 60(0.04) Weight(kg),n(%) < 50 10(0.02) 37(0.03) 100 101(0.20) 148(0.11) Type of AEs,n(%) - - - Dyspnoea 1133(0.39) 1737(0.61) < 0.001 a Cough 210(0.59) 144(0.41) < 0.001 a Epistaxis 139(0.29) 333(0.71) 0.020 a Dysphonia 38(0.68) 18(0.32) < 0.001 a Dyspnoea exertional 25(0.18) 111(0.82) < 0.001 a Oropharyngeal pain 24(0.62) 15(0.38) < 0.001 a Chronic obstructive pulmonary disease 23(0.33) 47(0.67) 0.870 a Wheezing 21(0.40) 31(0.60) 0.450 a Sleep apnoea syndrome 19(0.24) 60(0.76) 0.060 a Rhinorrhoea 18(0.75) 6(0.25) < 0.001 a Asthma 16(0.24) 50(0.76) 0.100 a Sneezing 16(0.76) 5(0.24) < 0.001 a Suffocation feeling 16(0.30) 38(0.70) 0.540 a Nasal Congestion 15(0.60) 10(0.40) 0.010 a Asphyxia 14(0.09) 147(0.91) < 0.001 a Respiration abnormal 13(0.65) 7(0.35) 0.010 a Sinus disorder 13(0.65) 7(0.35) 0.010 a Throat irritation 13(0.59) 9(0.41) 0.030 a Haemoptysis 12(0.12) 89(0.88) < 0.001 a Orthopnoea 11(0.37) 19(0.63) 0.950 a Productive cough 11(0.52) 10(0.48) 0.130 a Lung disorder 10(0.24) 32(0.76) 0.190 a Hyperventilation 9(0.41) 13(0.59) 0.680 a Bronchospasm 8(0.24) 25(0.76) 0.290 a Nocturnal dyspnoea 8(0.44) 10(0.56) 0.520 a Aphonia 7(0.64) 4(0.36) 0.060 b Dry throat 7(0.88) 1(0.12) < 0.001 b Respiratory depression 7(0.39) 11(0.61) 0.890 a Choking 6(0.23) 20(0.77) 0.310 a Hiccups 6(0.55) 5(0.45) 0.200 b Respiratory disorder 6(0.33) 12(0.67) 1.000 a Throat tightness 6(0.40) 9(0.60) 0.860 a Dyspnoea at rest 5(0.18) 23(0.82) 0.100 a Oropharyngeal discomfort 5(0.56) 4(0.44) 0.290 b The AEs listed above were AEs with significant signal strengths. a Proportions were comparaed using Pearson χ 2 test. b Fisher’s exact test. p -value < 0.05 were considered statistically significant. Stratification analysis To enhance the robustness of the study findings, we applied four different stratification strategies, as shown in Fig. 3 . After stratifying by sex, age, body weight, and reporter type, the lower bounds of the ROR 95% confidence intervals in all subgroups remained greater than 1, indicating that the association between ticagrelor and respiratory, thoracic, and mediastinal disorders persisted across all stratified subgroups. Clinical prioritization of relevant disproportionality signals In the disproportionality analysis, 25 PTs showed statistical significance, among which 9 were classified as Important Medical Events (IMEs). According to the prioritization assessment, 9 events were categorized as having moderate clinical priority, while 16 were deemed to have weak priority. Among them, the strongest association was observed for Cheyne-Stokes respiration (ROR 025 = 39.8), the most frequently reported event was dyspnoea (6.08%), and the highest reported case fatality rate was for pulmonary haemorrhage (38.30%). Additionally, our analysis identified five novel AE signals with statistically significant RORs that are not currently listed on the drug label and have not been clearly reported in previous studies (Table 3 ). Table 3 Clinical priority assessing results of disproportionality signals. PTs n ROR 025 Death Reporting rate Signal stability Reported case fatality rate Clinical relevance Priority level (score) Dyspnoea 2870 6.19 84 6.08% 2 2.93% None Moderate(3) Epistaxis 472 6.95 19 0.95% 2 4.01% None Weak(2) Cough* 354 1.39 3 0.71% 1 0.85% None Weak(1) Asphyxia 161 20.59 1 0.03% 2 0.62% IME Moderate(3) Dyspnoea Exertional 136 3.75 4 0.02% 2 2.94% None Weak(2) Pulmonary Oedema* 111 2.45 22 0.02% 2 19.82% IME Moderate(3) Haemoptysis 101 3.54 8 0.02% 2 7.92% None Weak(2) Sleep Apnoea Syndrome 79 3.88 0 0.02% 2 0 None Weak(2) Chronic Obstructive Pulmonary Disease* 70 1.28 10 0.01% 1 14.29% None Weak(1) Tachypnoea 55 3.82 3 0.01% 2 5.45% None Weak(2) Suffocation Feeling 54 20.31 2 0.01% 2 3.70% None Weak(2) Pulmonary Haemorrhage 47 5.26 18 0.01% 2 38.30% IME Moderate(4) Bronchospasm* 33 1.94 1 0.01% 2 3.03% None Weak(2) Orthopnoea 30 7.69 2 0.01% 2 6.67% None Weak(2) Dyspnoea At Rest 28 8.18 0 0.01% 2 0 IME Moderate(3) Choking* 26 1.11 1 0.01% 1 3.85% IME Weak(2) Pulmonary Alveolar Haemorrhage 25 3.73 9 5.00‰ 2 36.00% IME Moderate(4) Apnoea 24 2.41 2 4.80‰ 2 8.33% IME Moderate(3) Hyperventilation 22 2.94 0 4.40‰ 2 0 None Weak(2) Respiration Abnormal 20 2.36 0 4.00‰ 2 0 None Weak(2) Nocturnal Dyspnoea 18 10.73 2 3.60‰ 2 11.11% None Weak(2) Respiratory Depression 18 1.1 1 3.60‰ 1 5.56% None Weak(2) Acute Pulmonary Oedema 16 2.07 5 3.20‰ 2 31.25% IME Moderate(4) Cheyne-Stokes Respiration 14 39.8 0 2.80‰ 2 0 IME Moderate(3) Choking Sensation 14 1.83 1 2.80‰ 2 7.14% None Weak(2) PTs,Preferred Terms;ROR 025 ,the lower limit of 95% confidence interval of ROR. DME,designated medical event;IME,important medical event. A score of 0–2,3–5,and 6–8 identified,respectively,AEs with low,moderate,or high priority. *Emerging fingdings of ticagrelor-associated respiratory,thoracic and mediastinal AEs from FAERS database. Time-to-onset analysis TTO and WSP analysis results for AEs with moderate and weak clinical priority signals are presented in Table 4 . The median TTO for moderate and weak signals associated with ticagrelor was 5 days (IQR: 2–24) and 10 days (IQR: 3–63), respectively. The Weibull distribution analysis yielded a scale parameter (α) of 86.8 (95% CI: 80.9–92.6) and a shape parameter (β) of 0.617 (95% CI: 0.598–0.635). In the WSP analysis, all β values and their 95% confidence interval upper limits were < 1, indicating that these moderate and weak priority signals follow an early failure type risk pattern. Table 4 Time-to-onset analysis for signals with moderate/weak prioritization. Prioritization Weibull distribution Failure type case TTO(days) Scale parameter Shape parameter n Median(IQR) Min-max α 95%CI β 95%CI Moderate 637 5(2–24) 1-7307 18.06 15.1-21.01 0.5 0.48–0.53 Early Failure Weak 293 10(3–63) 1-1047 38.54 29.83–47.24 0.54 0.49–0.58 Early Failure n,number of cases with available time-to-onset;IQR,interquartile range;TTO,Time-to-onset. Discussion This study, based on real-world data from the FAERS database, presents updated findings on the safety profile of ticagrelor concerning respiratory, thoracic, and mediastinal disorders since its market approval. In this study, we presented all AEs associated with ticagrelor at the SOC level (Supplementary Table S3). The results showed that “Respiratory, thoracic and mediastinal disorders” ranked second in terms of reported case numbers, with a total of 5,779 reports. The highest number of reports was observed in the category of “General disorders and administration site conditions,” but the signal strength for this SOC was relatively weak (ROR = 0.95). Therefore, it can be inferred that the incidence of respiratory, thoracic, and mediastinal disorders during ticagrelor treatment is comparatively higher. A randomized controlled trial on dual antiplatelet therapy (DAPT) in acute myocardial infarction (AMI) patients found that although all participants initially received ticagrelor, some were later transitioned to clopidogrel. Those who switched experienced significantly lower rates of dyspnea at both 3 months (34.3% vs. 51.7%, p < 0.001) and 6 months (25.5% vs. 38.4%, p = 0.002) compared to those who remained on ticagrelor(Kim et al., 2024 ). In a meta-analysis, ticagrelor was associated with a significantly increased risk of dyspnea compared to clopidogrel, with a pooled risk ratio (RR) of 2.15 (95% CI: 1.59–2.92). Subgroup analyses showed this increased risk of dyspnea was consistent across various follow-up durations(Zhang et al., 2020 ). Similarly, our study found that the risk of dyspnea in ticagrelor-treated patients remained significantly elevated across different subgroups defined by sex, age, weight, and reporter type. Current research has recognized the potential risk of respiratory AEs associated with ticagrelor in the treatment of ACS, although the underlying mechanisms remain unclear. Two major hypotheses have been proposed. One suggests that the local accumulation of intracellular cAMP leads to increased adenosine levels, which in turn activate pulmonary vagal C fibers, resulting in dyspnea(Cattaneo and Faioni, 2012 ). Another theory posits that patients treated with ticagrelor exhibit an exaggerated ventilatory response to hyperoxic hypercapnia (central chemoreceptor hypersensitivity) and normoxic hypercapnia, resulting in hyperventilation and sympathetic excitation that may trigger dyspnea(Nattie and Li, 2012 ; Marshall, 1994 ; O'Regan and Majcherczyk, 1982 ). Furthermore, some studies suggest that ticagrelor-induced dyspnea may be due to heightened sensitivity of peripheral (PCh) and central (CCh) chemoreceptors, or preexisting hypersensitivity of these receptors before treatment(Tubek et al., 2023 ). Our study evaluated the characteristics of ticagrelor-related adverse events (AEs) in the respiratory, thoracic, and mediastinal systems, and compared serious and non-serious cases. Among the 34 AEs with more than 5 serious cases, 15 showed statistically significant differences (p < 0.05). Patient sex (p < 0.001) and body weight (p < 0.001), but not age (p = 0.287), were potentially associated with increased severity of respiratory, thoracic, and mediastinal system AEs. Female patients accounted for 38% of severe cases, a proportion significantly higher than that of males, indicating that ticagrelor-related target AEs predominantly occur in females. Numerous studies have demonstrated that certain respiratory diseases are more prevalent in women, such as a higher incidence of symptoms and asthma exacerbations, which lead to reduced quality of life and increased healthcare utilization(Pignataro et al., 2017 ). Non-cystic fibrosis bronchiectasis is predominantly a female-predominant disease in most regions, and registry data indicate that 65–80% of pulmonary arterial hypertension patients are female. Chromosomal sex, sex hormones, and hormone receptors may play complex roles in respiratory diseases(Sodhi et al., 2023 ). Few studies have further assessed the influence of sex on ticagrelor-related side effects, and mechanistic research on sex differences in ticagrelor-induced respiratory diseases remains lacking. Broader basic research is necessary to experimentally validate our findings. Table 2 shows that individuals aged 65–85 years were most susceptible to severe target adverse reactions, accounting for as much as 61%, likely reflecting the predominance of this age group in our study cohort. Moreover, physiological decline and reduced immunity in the elderly increase susceptibility to severe AEs(Biesalski, 2021 ). However, the incidence ratio of severe to non-severe events did not differ significantly across age groups (p = 0.287). Subgroup analysis revealed a significant association between ticagrelor use and target adverse reactions in adolescents under 18 years of age, with a stronger correlation compared to other age groups (ROR = 6.75, 95% CI: 3.18–14.36), warranting attention. Recently, ticagrelor has been investigated for reducing vaso-occlusive crises in pediatric sickle cell disease patients, and novel pediatric dispersible ticagrelor tablets have gradually been introduced across a wide pediatric age range(Niazi et al., 2019 ). While exploring new indications, vigilance regarding ticagrelor-induced AEs is warranted. Given the limited indications of ticagrelor in pediatric and adolescent populations, larger clinical studies are needed to further elucidate the relationship between ticagrelor and target adverse reactions. ACS is closely linked to obesity. A meta-analysis demonstrated that a high body mass index (BMI) significantly increases the risk of ACS in young women (RR 2.51; 95% CI: 1.34–3.68)(Siagian et al., 2023 ). Although the so-called “obesity paradox” suggests that obese adults may have a survival advantage post-ACS compared to non-obese adults(Balayah et al., 2021 ), obesity remains an important risk factor for coronary artery disease(Mornar Jelavic et al., 2023 ). Dual antiplatelet therapy with aspirin and ticagrelor significantly reduces cardiovascular events after ACS(Content Error, 2021 ). In our study, patients weighing more than 100 kg had a higher proportion of severe events compared with the non-severe event group (20% vs. 11%), while those weighing less than 100 kg experienced more non-severe target adverse reactions. Stratified analysis revealed a significant association between low body weight (< 80 kg) and target adverse reactions (ROR = 3.95), with stronger correlations than in medium-weight (80–100 kg; ROR = 2.53) and high-weight groups (100–200 kg; ROR = 2.72). Thus, low body weight ( 100 kg) is associated with a greater likelihood of severe adverse reactions. Moderate weight reduction may reduce both ACS risk and the incidence of severe AEs. To assist clinicians and pharmacovigilance experts in identifying positive signals of drug-related AEs and to guide rational clinical decision-making, we innovatively applied a scoring scale to further analyze disproportionate signals. Ticagrelor-related target disproportionate clinical priority signals with more than 10 cases are listed in Table 3 . Our analysis identified nine moderate-priority signals: dyspnea, asphyxia, pulmonary edema, pulmonary hemorrhage, dyspnea at rest, pulmonary alveolar hemorrhage, apnea, acute pulmonary edema, and Cheyne-Stokes respiration, along with sixteen weak-priority signals. Notably, among the moderate-priority signals, Cheyne-Stokes respiration exhibited a particularly strong signal strength with a reporting ROR of 68.31 (95% CI: 39.8–117.24). Additionally, significant AEs such as suffocation feeling (n = 54, ROR = 26.61, 95% CI: 20.31–34.86), asphyxia (n = 161, ROR = 24.08, 95% CI: 20.59–28.16), nocturnal dyspnea (n = 18, ROR = 17.09, 95% CI: 10.73–27.23), dyspnea at rest (n = 28, ROR = 11.87, 95% CI: 8.18–17.23), and orthopnea (n = 30, ROR = 11.02, 95% CI: 7.69–15.8) were also observed. Most of these AEs are related to respiratory distress. There have been previous reports of ticagrelor-induced Cheyne-Stokes respiration and cardiac arrest(Murat et al., 2024 ). Since P2Y12 receptors are expressed not only on platelets but also on other hematopoietic and non-hematopoietic cells, including microglial cells in the central nervous system, potential stimulation of the chemoreflex system may induce Cheyne-Stokes respiration(Giannoni et al., 2016 ). This severe respiratory condition may be alleviated by aminophylline infusion or drug discontinuation(Conte et al., 2017 ; Minner et al., 2018 ). Weibull parameters were employed to predict the time interval prior to AE onset, which can help guide clinical drug use(Mazhar et al., 2021 ). TTO analysis showed that moderate- and weak-priority signal AEs had median onset times of 5 and 10 days, respectively, with all disproportionate signals exhibiting early failure characteristics. This indicates that most patients experience respiratory, thoracic, and mediastinal system AEs within two weeks of starting ticagrelor, with the probability of AE occurrence decreasing over time. Similarly, the PLATO clinical trial reported that ticagrelor-induced dyspnea symptoms were more likely to occur within 7 days, with a median duration of 23 days(Storey et al., 2011 ), supporting our findings.Furthermore, among 25 AEs, we newly identified five AEs not previously documented in the drug label: cough, pulmonary edema, chronic obstructive pulmonary disease, bronchospasm, and choking. The effects of ticagrelor on these AEs and their underlying mechanisms remain unclear, warranting further extensive investigation. Although our study utilized real-world data mining from the FAERS database, it is inevitably subject to several limitations common to all pharmacovigilance databases. First, the FAERS database contains underreporting, misreporting, and incomplete reports, which may introduce biases that cannot be accurately quantified. Second, the FAERS database only includes patients who experienced AEs, while the total number of patients treated with ticagrelor is unavailable. Third, causal relationships between ticagrelor and target adverse reactions cannot be established, as disproportionality analysis only indicates a statistical association between ticagrelor and the reported adverse reactions. Therefore, further experimental studies, clinical trials, cohort studies, and case-control studies are warranted to validate our findings in the future. Conclusion This study comprehensively analyzed the association between ticagrelor and AEs of the respiratory, thoracic, and mediastinal systems based on the FAERS database, yielding several important findings. First, 25 significantly associated signals were detected, of which five AEs were identified as newly discovered signals. Second, patient sex (p < 0.001) and body weight (p < 0.001), rather than age (p = 0.287), may be related to an increased risk of severe respiratory, thoracic, and mediastinal AEs. Third, nine moderate clinical priority signals and sixteen weak clinical priority signals were defined, with median onset times of 5 and 10 days, respectively. All disproportionate signals exhibited early failure characteristics, indicating that most patients experience respiratory, thoracic, and mediastinal system AEs within two weeks of ticagrelor initiation, with the probability of AEs decreasing over time. Our pharmacovigilance study elucidates the potential risks and characteristics of ticagrelor-related respiratory, thoracic, and mediastinal diseases, providing a reference for rational clinical use to reduce the risk of such adverse reactions. Declarations Competing Interests The authors have no relevant financial or non f inancial interests to disclose. Ethics approval Not applicable. Consent to participate Not applicable. Consent to publish Not applicable. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contribution Conceptualization: Yuan Zeng, Gong Chen. Data Curation: Yuan Zeng, Lin Lu, Wenwu Zheng. Formal Analysis: Yuan Zeng, Lin Lu. Funding Acquisition: Gong Chen. Investigation:Yuan Zeng. Methodology:Yuan Zeng. Project Administration: Wenwu Zheng. Supervision:Wenwu Zheng. Validation:Yuan Zeng, Gong Chen. Visualization: Yuan Zeng, Lin Lu. Writing – Original Draft Preparation:Yuan Zeng, Lin Lu. Writing – Review & Editing: Yuan Zeng, Wenwu Zheng. Acknowledgement We would like to express our sincere gratitude to the individuals who participated in this study, as well as to those who provided invaluable assistance with data analysis. References Angiolillo DJ, Cao D, Sartori S, Baber U, Dangas G, Zhang Z et al (2023) Dyspnea-Related Ticagrelor Discontinuation After Percutaneous Coronary Intervention. JACC Cardiovasc Interv 16(20):2514–2524. http://dx.doi.org/10.1016/j.jcin.2023.08.019 Arora S, Shemisa K, Vaduganathan M, Qamar A, Gupta A, Garg SK et al (2019) Premature Ticagrelor Discontinuation in Secondary Prevention of Atherosclerotic CVD: JACC Review Topic of the Week. J Am Coll Cardiol 73(19):2454–2464. http://dx.doi.org/10.1016/j.jacc.2019.03.470 Balayah Z, Alsheikh-Ali AA, Rashed W, Almahmeed W, Mulla AA, Alrawahi N et al (2021) Association of obesity indices with in-hospital and 1-year mortality following acute coronary syndrome. Int J Obes (Lond) 45(2):358–368. http://dx.doi.org/10.1038/s41366-020-00679-0 Biesalski HK (2021) Obesity, vitamin D deficiency and old age a serious combination with respect to coronavirus disease-2019 severity and outcome. Curr Opin Clin Nutr Metab Care 24(1):18–24. http://dx.doi.org/10.1097/mco.0000000000000700 Cattaneo M, Faioni EM (2012) Why does ticagrelor induce dyspnea? Thromb Haemost 108(6):1031–1036. http://dx.doi.org/10.1160/th12-08-0547 Cecco S, Puligheddu S, Fusaroli M, Gerratana L, Yan M, Zamagni C et al (2024) Emerging Toxicities of Antibody-Drug Conjugates for Breast Cancer: Clinical Prioritization of Adverse Events from the FDA Adverse Event Reporting System. Target Oncol 19(3):435–445. http://dx.doi.org/10.1007/s11523-024-01058-9 Chen H (2024) Real-world pharmacovigilance of ofatumumab in multiple sclerosis: a comprehensive FAERS data analysis. Front Pharmacol 15:1521726. http://dx.doi.org/10.3389/fphar.2024.1521726 Chen H, Yang G, Ma J (2024) Ocular toxicity associated with anti-HER2 agents in breast cancer: A pharmacovigilance analysis using the FAERS database. Int J Cancer 154(9):1616–1625. http://dx.doi.org/10.1002/ijc.34848 Conte L, Pugliese NR, Giannoni A (2017) Reversal of Ticagrelor-Induced Arrhythmias and Cheyne-Stokes Respiration With Aminophylline Infusion. J Cardiovasc Pharmacol 70(5):290–292. http://dx.doi.org/10.1097/fjc.0000000000000518 Content Error (2021) JAMA 326(2):190. http://dx.doi.org/10.1001/jama.2021.9484 Gatti M, Antonazzo IC, Diemberger I, De Ponti F, Raschi E (2021) Adverse events with sacubitril/valsartan in the real world: emerging signals to target preventive strategies from the FDA adverse event reporting system. Eur J Prev Cardiol 28(9):983–989. http://dx.doi.org/10.1177/2047487320915663 Giannoni A, Emdin M, Passino C (2016) Cheyne-Stokes Respiration, Chemoreflex, and Ticagrelor-Related Dyspnea. N Engl J Med 375(10):1004–1006. http://dx.doi.org/10.1056/NEJMc1601662 Javaheri S, Randerath WJ, Badr S, M., Javaheri S (2024) Medication-induced central sleep apnea: a unifying concept. Sleep 47(8). http://dx.doi.org/10.1093/sleep/zsae038 Kim SH, Shin S, Choo EH, Choi IJ, Lim S, Moon D et al (2024) Clinical Impact of Dyspnea after Ticagrelor Treatment and the Effect of Switching to Clopidogrel in Patients with Myocardial Infarction. Thromb Haemost 124(12):1152–1161. http://dx.doi.org/10.1055/a-2299-4537 Li X, Zhang G, Cao X (2023) The Function and Regulation of Platelet P2Y12 Receptor. Cardiovasc Drugs Ther 37(1):199–216. http://dx.doi.org/10.1007/s10557-021-07229-4 Marshall JM (1994) Peripheral chemoreceptors and cardiovascular regulation. Physiol Rev 74(3):543–594. http://dx.doi.org/10.1152/physrev.1994.74.3.543 Mazhar F, Battini V, Gringeri M, Pozzi M, Mosini G, Marran AMN et al (2021) The impact of anti-TNFα agents on weight-related changes: new insights from a real-world pharmacovigilance study using the FDA adverse event reporting system (FAERS) database. Expert Opin Biol Ther 21(9):1281–1290. http://dx.doi.org/10.1080/14712598.2021.1948529 Meng L, Yang B, Qiu F, Jia Y, Sun S, Yang J et al (2021) Lung Cancer Adverse Events Reports for Angiotensin-Converting Enzyme Inhibitors: Data Mining of the FDA Adverse Event Reporting System Database. Front Med (Lausanne) 8:594043. http://dx.doi.org/10.3389/fmed.2021.594043 Minner SA, Simone P, Chung BB, Shah AP (2018) Successful Reversal of Bradycardia and Dyspnea With Aminophylline After Ticagrelor Load. J Pharm Pract 31(1):112–114. http://dx.doi.org/10.1177/0897190016680978 Mornar Jelavic M, Babic Z, Pintaric H (2023) Obesity Paradox in the Intrahospital and Follow-Up Phases of the Acute Coronary Syndrome: A Meta-Analysis and Systematic Review. Cardiology 148(6):528–544. http://dx.doi.org/10.1159/000531985 Murat B, Murat S, Kivanc E (2024) Ticagrelor Induced Cheyne-Stokes Respiration and Asystolic Ventricular Standstill: A Case Report. Kardiologiia 64(2):80–84. http://dx.doi.org/10.18087/cardio.2024.2.n2123 Nattie E, Li A (2012) Central chemoreceptors: locations and functions. Compr Physiol 2(1):221–254. http://dx.doi.org/10.1002/cphy.c100083 Niazi M, Wissmar J, Berggren AR, Karlsson C, Johanson P (2019) Development Strategy and Relative Bioavailability of a Pediatric Tablet Formulation of Ticagrelor. Clin Drug Investig 39(8):765–773. http://dx.doi.org/10.1007/s40261-019-00800-w O'Regan RG, Majcherczyk S (1982) Role of peripheral chemoreceptors and central chemosensitivity in the regulation of respiration and circulation. J Exp Biol 100:23–40. http://dx.doi.org/10.1242/jeb.100.1.23 Pan Y, Wang Y, Zheng Y, Chen J, Li J (2024) A disproportionality analysis of FDA adverse event reporting system (FAERS) events for ticagrelor. Front Pharmacol 15:1251961. http://dx.doi.org/10.3389/fphar.2024.1251961 Pignataro FS, Bonini M, Forgione A, Melandri S, Usmani OS (2017) Asthma and gender: The female lung. Pharmacol Res 119:384–390. http://dx.doi.org/10.1016/j.phrs.2017.02.017 Pujade I, Perino J, Mathieu C, Arnaud M, Raschi E, Gatti M et al (2020) Risk of bradyarrhythmia related to ticagrelor: A systematic review and meta-analysis. Pharmacol Res 160:105089. http://dx.doi.org/10.1016/j.phrs.2020.105089 Rosa GM, Bianco D, Valbusa A, Massobrio L, Chiarella F, Brunelli C (2016) Pharmacokinetics and pharmacodynamics of ticagrelor in the treatment of cardiac ischemia. Expert Opin Drug Metab Toxicol 12(12):1491–1502. http://dx.doi.org/10.1080/17425255.2016.1244524 Salem JE, Manouchehri A, Moey M, Lebrun-Vignes B, Bastarache L, Pariente A et al (2018) Cardiovascular toxicities associated with immune checkpoint inhibitors: an observational, retrospective, pharmacovigilance study. Lancet Oncol 19(12):1579–1589. http://dx.doi.org/10.1016/s1470-2045(18)30608-9 Serebruany VL, Dinicolantonio JJ, Can MM, Pershukov IV, Kuliczkowski W (2013) Gastrointestinal adverse events after dual antiplatelet therapy: clopidogrel is safer than ticagrelor, but prasugrel data are lacking or inconclusive. Cardiology 126(1):35–40. http://dx.doi.org/10.1159/000350961 Shu Y, Ding Y, Dai B, Zhang Q (2022) A real-world pharmacovigilance study of axitinib: data mining of the public version of FDA adverse event reporting system. Expert Opin Drug Saf 21(4):563–572. http://dx.doi.org/10.1080/14740338.2022.2016696 Siagian SN, Christianto C, Angellia P, Holiyono HI (2023) The Risk Factors of Acute Coronary Syndrome in Young Women: A Systematic Review and Meta-Analysis. Curr Cardiol Rev 19(3):e161122210969. http://dx.doi.org/10.2174/1573403x19666221116113208 Sodhi A, Cox-Flaherty K, Greer MK, Lat TI, Gao Y, Polineni D et al (2023) Sex and Gender in Lung Diseases and Sleep Disorders: A State-of-the-Art Review: Part 2. Chest 163(2):366–382. http://dx.doi.org/10.1016/j.chest.2022.08.2240 Storey RF, Becker RC, Harrington RA, Husted S, James SK, Cools F et al (2011) Characterization of dyspnoea in PLATO study patients treated with ticagrelor or clopidogrel and its association with clinical outcomes. Eur Heart J 32(23):2945–2953. http://dx.doi.org/10.1093/eurheartj/ehr231 Storey RF, Bliden KP, Patil SB, Karunakaran A, Ecob R, Butler K et al (2010) Incidence of dyspnea and assessment of cardiac and pulmonary function in patients with stable coronary artery disease receiving ticagrelor, clopidogrel, or placebo in the ONSET/OFFSET study. J Am Coll Cardiol 56(3):185–193. http://dx.doi.org/10.1016/j.jacc.2010.01.062 Tubek S, Niewinski P, Langner-Hetmanczuk A, Jura M, Kuliczkowski W, Reczuch K et al (2023) The effects of P2Y(12) adenosine receptors' inhibitors on central and peripheral chemoreflexes. Front Physiol 14:1214893. http://dx.doi.org/10.3389/fphys.2023.1214893 Zhang N, Xu W, Li O, Zhang B (2020) The risk of dyspnea in patients treated with third-generation P2Y(12) inhibitors compared with clopidogrel: a meta-analysis of randomized controlled trials. BMC Cardiovasc Disord 20(1):140. http://dx.doi.org/10.1186/s12872-020-01419-y Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 16 Jul, 2025 Read the published version in Naunyn-Schmiedeberg's Archives of Pharmacology → Version 1 posted Editorial decision: Revision requested 11 Jun, 2025 Reviews received at journal 11 Jun, 2025 Reviewers agreed at journal 11 Jun, 2025 Reviewers invited by journal 11 Jun, 2025 Editor assigned by journal 04 Jun, 2025 Submission checks completed at journal 04 Jun, 2025 First submitted to journal 01 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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03:08:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6798394/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6798394/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00210-025-04428-w","type":"published","date":"2025-07-16T16:05:40+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84816999,"identity":"699a0d39-b06a-46fd-b4b9-9cf1395ee872","added_by":"auto","created_at":"2025-06-17 15:47:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118773,"visible":true,"origin":"","legend":"\u003cp\u003eThe process of selecting ticagrelor-associated respiratory, thoracic, and mediastinal adverse events from food and drug administration adverse event reporting database.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6798394/v1/d914f69128e7f9d59a566bfb.png"},{"id":84817003,"identity":"b7540e34-7da0-4ba6-b806-b7b712a49db4","added_by":"auto","created_at":"2025-06-17 15:47:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":303578,"visible":true,"origin":"","legend":"\u003cp\u003eReporting odds ratios (ROR) with 95% CI for all positive ticagrelor-associated respiratory, thoracic, and mediastinal AEs.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6798394/v1/b9878dab22d79df9e69fc7ef.png"},{"id":84818782,"identity":"b2edc80e-a06c-4a4d-9035-476caaa44cb5","added_by":"auto","created_at":"2025-06-17 15:55:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":236274,"visible":true,"origin":"","legend":"\u003cp\u003eStratification analysis of ticagrelor-associated respiratory, thoracic, and mediastinal disorders.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6798394/v1/6a44d5845a557683fe273748.png"},{"id":87220339,"identity":"11f472f8-45b0-43e1-89dc-ec21ba0a4f37","added_by":"auto","created_at":"2025-07-21 16:11:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1936813,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6798394/v1/be2ed0f1-5e9b-413f-8f8f-218fb039802b.pdf"},{"id":84817001,"identity":"9687c214-2bc2-408d-b8aa-b3c16fabca57","added_by":"auto","created_at":"2025-06-17 15:47:13","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":689953,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6798394/v1/5f8826f8f68330b7d8d2f5ec.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Respiratory, thoracic, and mediastinal adverse events associated with ticagrelor: A pharmacovigilance study based on FDA adverse event reporting system","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTicagrelor, a P\u003csub\u003e2\u003c/sub\u003eY\u003csub\u003e12\u003c/sub\u003e receptor blocker, plays a pivotal role in contemporary antithrombotic treatment when used alongside aspirin, particularly for patients with ACS or undergoing percutaneous coronary intervention (PCI)(Arora et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It not only prevents thrombus propagation by inhibiting platelet activation, thereby reducing myocardial ischemic injury and thrombotic complications(Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rosa et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), but also alleviates endothelial dysfunction and atherosclerosis development by suppressing inflammatory activation of endothelial cells, offering long-term benefits in the prevention of adverse cardiovascular events(Rosa et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWith the rising global incidence of coronary artery disease, the use of antiplatelet agents has been expanding, and clinical demand for ticagrelor continues to grow. Therefore, a comprehensive investigation into the AEs and characteristics associated with ticagrelor is crucial to guide clinical decision-making.\u003c/p\u003e \u003cp\u003eTo date, several studies have evaluated the safety profile of ticagrelor. A recent pharmacovigilance study published in April 2024 systematically assessed ticagrelor-related AEs using the FAERS database, covering all reports from Q4 2010 to Q2 2023(Pan et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). One of the most commonly reported system organ classes (SOCs) in that study was respiratory, thoracic, and mediastinal disorders. In addition, ticagrelor has been associated with an increased risk of gastrointestinal bleeding and cardiac arrhythmias(Serebruany et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Pujade et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A clinical study reported that the incidence of ticagrelor discontinuation due to dyspnea was 6.4% at 3 months and 9.1% at 15 months post-PCI, indicating that approximately 1 in 10 patients may discontinue ticagrelor due to dyspnea(Angiolillo et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Another randomized controlled trial found that the incidence of respiratory AEs was approximately four times higher in patients treated with ticagrelor compared to clopidogrel(Storey et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Furthermore, rare respiratory-related adverse effects such as central sleep apnea and Cheyne\u0026ndash;Stokes respiration have also been reported(Javaheri et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Giannoni et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven these findings, this study focuses specifically on respiratory, thoracic, and mediastinal AEs associated with ticagrelor. Using disproportionality analysis based on the FAERS database, we quantitatively assessed the safety signals of these events. Additionally, we performed analyses of case severity, subgroup stratification, clinical priority ranking of signals, and time-to-onset(TTO) to further characterize the nature of these AEs.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and data sources\u003c/h2\u003e \u003cp\u003eA disproportionality analysis based on observational and retrospective data was employed to evaluate the potential association between ticagrelor and respiratory, thoracic, and mediastinal AEs. A disproportional signal was considered to exist if the proportion of target AEs was higher in the case group than in the non-case group, suggesting a possible association between the drug and the AE(Gatti et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Based on the FDA approval date for ticagrelor, we analyzed all AE reports from Q3 2011 to Q4 2024 in which ticagrelor was identified as the primary suspected drug.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData extraction and descriptive analysis\u003c/h3\u003e\n\u003cp\u003eThis research was based on data extracted from the FDA Adverse Event Reporting System (FAERS), which includes seven key components: demographics (DEMO), drug details (DRUG), reported reactions (REAC), outcomes (OUTC), sources of reports (RPSR), treatment timelines (THER), and indications for therapy (INDI)(Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). All data were imported into MySQL software (v8.0; Oracle, Sweden). To ensure data quality, duplicate reports were proactively removed based on case ID prior to statistical analysis. For entries sharing the same case ID, only the record with the most recent FDA receipt date (FDA_DT) was retained.\u003c/p\u003e \u003cp\u003eTicagrelor-related cases were identified in the DRUG dataset using the drug names: Ticagrelor, AZD6140, Brilique, and Brilinta. Only reports where ticagrelor was labeled as the primary suspected drug (PS) were included. AE terms in the FAERS database are coded according to the Medical Dictionary for Regulatory Activities (MedDRA)(Meng et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Our analysis included all Preferred Terms(PTs) under the \"Respiratory, Thoracic and Mediastinal Disorders\" SOC in MedDRA to capture AEs related to respiratory and thoracic complications.\u003c/p\u003e \u003cp\u003eEligible individual cases were identified and described according to patient characteristics, including sex, age, weight, reporting region, outcomes, reporter type, and report year. Outcomes were categorized into serious and non-serious events. Serious outcomes included death, life-threatening conditions, hospitalization, disability, and other serious outcomes. Notably, the total number of serious outcomes may exceed the number of AE reports, as individual patients may report multiple serious outcomes. The detailed process of data extraction, processing, and analysis is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe ROR is a widely used algorithm in disproportionality analysis and is calculated based on a 2\u0026times;2 contingency table (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)(Salem et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). To minimize false-positive findings, only adverse events (AEs) reported 10 times or more were included in the ROR analysis. A signal was deemed significant if the lower bound of the 95% confidence interval (ROR\u003csub\u003e025\u003c/sub\u003e) was greater than 1.In addition, serious outcomes were compared with non-serious outcomes to identify potential risk factors associated with AEs. Serious outcomes were defined as death, life-threatening conditions, hospitalization, disability, or other serious events. Group comparisons were performed using Pearson\u0026rsquo;s chi-square test(χ\u0026sup2;) or Fisher\u0026rsquo;s exact test, with statistical significance defined as a two-tailed p-value less than 0.05.Stratified analyses were further conducted by sex, age, body weight, and reporter type (healthcare professionals vs. consumers) to explore whether the association between ticagrelor and respiratory, thoracic, and mediastinal disorders varied across different subgroups.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical prioritization of signals\u003c/h3\u003e\n\u003cp\u003eDisproportionality signals were categorized into three levels of clinical priority: (1) low, (2) moderate, and (3) high clinical priority(Gatti et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Following previous literature, we performed a semi-quantitative scoring of disproportional signals based on four features: reporting rate, signal stability, reported case fatality rate, and clinical relevance(Cecco et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We also reported the number of AE cases, ROR\u003csub\u003e025\u003c/sub\u003e, and the number of deaths. Based on the total score, AEs were classified into three categories of clinical priority: 0\u0026ndash;2 (low), 3\u0026ndash;5 (moderate), and 6\u0026ndash;8 (high). Full details are provided in Supplementary Table S2.\u003c/p\u003e\n\u003ch3\u003eTime-to-onset analysis\u003c/h3\u003e\n\u003cp\u003eTTO was defined as the interval between the start date of ticagrelor treatment and the onset date of the AE(Shu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). TTO data were analyzed using the Weibull shape parameter (WSP) test, and the results were summarized using the median, interquartile range (IQR), and Weibull distribution parameters. The Weibull distribution is characterized by a scale parameter (α) and a shape parameter (β)(Mazhar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe shape parameter β reflects the nature of risk over time: β\u0026thinsp;\u0026lt;\u0026thinsp;1 indicates a decreasing hazard, β\u0026thinsp;=\u0026thinsp;1 indicates a constant hazard, and β\u0026thinsp;\u0026gt;\u0026thinsp;1 indicates an increasing hazard(Chen, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We calculated the median TTO and WSP for signals with low or moderate clinical priority to assess the temporal risk profile of these AEs. These findings may offer insights into risk mitigation strategies and guide targeted monitoring interventions.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive analysis\u003c/h2\u003e \u003cp\u003eSince the third quarter of 2011, after excluding duplicates, a total of 18,627,667 AE reports were retrieved from the FAERS database, among which 19,996 were associated with ticagrelor. Of these, 4,605 reports involved AEs related to respiratory, thoracic, and mediastinal disorders. Detailed clinical characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.Among 4,356 cases with available sex information, males accounted for 60.45%, which was higher than females (39.55%). The majority of ticagrelor-associated respiratory, thoracic, and mediastinal AEs occurred in the elderly population, with 1,321 patients (61.52%) aged over 65 years. Body weight data were available for 1,887 patients: 47 (2.49%) weighed\u0026thinsp;\u0026lt;\u0026thinsp;50 kg, 1,591 (84.31%) were between 50\u0026ndash;100 kg, and 249 (13.20%) weighed\u0026thinsp;\u0026gt;\u0026thinsp;100 kg. The median body weight was 79.4 kg.The United States reported the highest number of ticagrelor-associated AEs related to respiratory, thoracic, and mediastinal disorders. Hospitalization was the most frequently reported serious outcome, occurring in 1,278 cases (27.8%). Regarding reporter characteristics, the majority of reports (3,591; 94.67%) were submitted by non-health professionals, while only 202 (5.32%) were reported by healthcare professionals.From Q3 2011 to the end of the study period, the highest number of ticagrelor-related AEs in the respiratory, thoracic, and mediastinal disorders category was recorded in 2016, totaling 820 cases (17.8%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics of patients with ticagrelor-associated respiratory, thoracic, and mediastinal AEs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTicagrelor induced respiratory,thoracic and mediastinal AEs(n\u0026thinsp;=\u0026thinsp;4,605)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eTicagrelor induced overall AEs\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;19,996)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAvailble number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAvailble numbe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender,n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,356(94.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18,212(91.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,723(39.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e6,801(37.34%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,633(60.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e11,411 (62.66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge(years),n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,147(46.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,268(41.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(0.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e12(0.15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026thinsp;~\u0026thinsp;64.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e819(38.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e3,563(43.09%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026thinsp;~\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,241(57.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4,378(52.95%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(3.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e315(3.81%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e66.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeight(kg),n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,887(40.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,430(27.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(2.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e139(2.56%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026thinsp;~\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,591(84.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4,681(86.21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e249(13.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e610(11.23%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian(kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReported countries,n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,605(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19,996(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,912(63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e11,229(56.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-US\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,693(36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e8,767(43.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcomes,n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,605(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e19,996(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-serious outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,997(65.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4,780(23.90%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerious outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,608(34.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e15,216(76.10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237(5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e2,724(13.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLife-threatening\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221(4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,246(6.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,278(27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e5,692(28.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59(1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e156(0.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther serious outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,193(25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4780(23.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReporters,n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,793(82.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16,895(84.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth professional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202(5.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e664(3.93%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-health professional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,591(94.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e16,231(96.07%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReporting years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,605(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19,996(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2011Q3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e39 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e197 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e886 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e266 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,258 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e266 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,427 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e373 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,762 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e820 (17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e3,853 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e467 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e2,157 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e535 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,997 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e335 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,343 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e345 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,148 (5.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e313 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,107 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e790 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e999 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e207 (4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1,230 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*The third quarter of 2011\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAEs,adverse events;n number of cases\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDisproportionality analysis\u003c/h3\u003e\n\u003cp\u003eWe selected all PTs under the \u0026ldquo;Respiratory, Thoracic, and Mediastinal Disorders\u0026rdquo; SOC in the FAERS database that were associated with ticagrelor and had more than 10 reported cases, resulting in a total of 25 PTs. The five most frequently reported AEs in this category were dyspnea (n\u0026thinsp;=\u0026thinsp;2,870), epistaxis (n\u0026thinsp;=\u0026thinsp;472), cough (n\u0026thinsp;=\u0026thinsp;354), asphyxia (n\u0026thinsp;=\u0026thinsp;161), and exertional dyspnea (n\u0026thinsp;=\u0026thinsp;134).The disproportionality analysis results for ticagrelor-associated respiratory, thoracic, and mediastinal disorders are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Across the entire FAERS database, the reporting frequency of these AEs was significantly higher for ticagrelor compared to non-ticagrelor drugs, with a lower bound of the 95% confidence interval of the ROR\u003csub\u003e025\u003c/sub\u003e of 2.52.As one of the most widely used antiplatelet agents, ticagrelor demonstrated the second strongest disproportionality signal in the \u0026ldquo;Respiratory, Thoracic, and Mediastinal Disorders\u0026rdquo; SOC among all 27 SOCs, following only the cardiovascular system. The corresponding ROR was 2.59 (95% CI: 2.52\u0026ndash;2.66), as detailed in Supplementary Table S3.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSerious vs. non-serious cases\u003c/h2\u003e \u003cp\u003eThe differences in clinical characteristics between serious and non-serious reports are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among patients who experienced respiratory, thoracic, and mediastinal AEs during ticagrelor treatment, there were statistically significant differences in gender (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and body weight (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) between serious and non-serious cases. However, the male-to-female ratio between the two groups was not significantly different (p\u0026thinsp;=\u0026thinsp;0.251).A total of 27 AEs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were more likely to be reported as serious, including dyspnea (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), cough (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), epistaxis (p\u0026thinsp;=\u0026thinsp;0.02), dysphonia (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), exertional dyspnea (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and oropharyngeal pain (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, 47 AEs were more likely to be reported as non-serious, such as chronic obstructive pulmonary disease (p\u0026thinsp;=\u0026thinsp;0.870), wheezing (p\u0026thinsp;=\u0026thinsp;0.450), sleep apnea syndrome (p\u0026thinsp;=\u0026thinsp;0.060), asthma (p\u0026thinsp;=\u0026thinsp;0.100), and suffocation feeling (p\u0026thinsp;=\u0026thinsp;0.540).Notably, the majority of serious cases were associated with dyspnea events related to ticagrelor.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in clinical characteristics of serious and non-serious reports.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerious cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-serious cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender,n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e648(0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,075(0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e844(0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,789(0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years),n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.287\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026thinsp;~\u0026thinsp;64.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161(0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e658(0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026thinsp;~\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284(0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e957(0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60(0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight(kg),n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026thinsp;~\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e404(0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1187(0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101(0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148(0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of AEs,n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1133(0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1737(0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e210(0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144(0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpistaxis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139(0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e333(0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDysphonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38(0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnoea exertional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25(0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111(0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOropharyngeal pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23(0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.870\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21(0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.450\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep apnoea syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60(0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.060\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRhinorrhoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50(0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.100\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSneezing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuffocation feeling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38(0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.540\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNasal Congestion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsphyxia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147(0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiration abnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSinus disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThroat irritation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaemoptysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89(0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthopnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.950\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProductive cough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.130\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.190\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.680\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchospasm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.290\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNocturnal dyspnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.520\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAphonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.060\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry throat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.890\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.310\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHiccups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.200\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThroat tightness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.860\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnoea at rest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.100\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOropharyngeal discomfort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.290\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe AEs listed above were AEs with significant signal strengths.\u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003eProportions were comparaed using Pearson χ\u003csup\u003e2\u003c/sup\u003e test.\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003eFisher\u0026rsquo;s exact test.\u003c/p\u003e \u003cp\u003e \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStratification analysis\u003c/h2\u003e \u003cp\u003eTo enhance the robustness of the study findings, we applied four different stratification strategies, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. After stratifying by sex, age, body weight, and reporter type, the lower bounds of the ROR 95% confidence intervals in all subgroups remained greater than 1, indicating that the association between ticagrelor and respiratory, thoracic, and mediastinal disorders persisted across all stratified subgroups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eClinical prioritization of relevant disproportionality signals\u003c/h2\u003e \u003cp\u003eIn the disproportionality analysis, 25 PTs showed statistical significance, among which 9 were classified as Important Medical Events (IMEs). According to the prioritization assessment, 9 events were categorized as having moderate clinical priority, while 16 were deemed to have weak priority. Among them, the strongest association was observed for Cheyne-Stokes respiration (ROR\u003csub\u003e025\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;39.8), the most frequently reported event was dyspnoea (6.08%), and the highest reported case fatality rate was for pulmonary haemorrhage (38.30%). Additionally, our analysis identified five novel AE signals with statistically significant RORs that are not currently listed on the drug label and have not been clearly reported in previous studies (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical priority assessing results of disproportionality signals.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eROR\u003csub\u003e025\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReporting rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSignal stability\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eReported case fatality rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClinical relevance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePriority level\u003c/p\u003e \u003cp\u003e(score)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.08%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpistaxis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsphyxia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnoea Exertional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.94%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary Oedema*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaemoptysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep Apnoea Syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Obstructive Pulmonary Disease*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTachypnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.45%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuffocation Feeling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary Haemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchospasm*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.03%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthopnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnoea At Rest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChoking*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary Alveolar Haemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.00\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.80\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.40\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiration Abnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.00\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNocturnal Dyspnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.60\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.60\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Pulmonary Oedema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.20\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheyne-Stokes Respiration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.80\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate(3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChoking Sensation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.80\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeak(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePTs,Preferred Terms;ROR\u003csub\u003e025\u003c/sub\u003e,the lower limit of 95% confidence interval of ROR.\u003c/p\u003e \u003cp\u003eDME,designated medical event;IME,important medical event.\u003c/p\u003e \u003cp\u003eA score of 0\u0026ndash;2,3\u0026ndash;5,and 6\u0026ndash;8 identified,respectively,AEs with low,moderate,or high priority.\u003c/p\u003e \u003cp\u003e*Emerging fingdings of ticagrelor-associated respiratory,thoracic and mediastinal AEs from FAERS database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTime-to-onset analysis\u003c/h2\u003e \u003cp\u003eTTO and WSP analysis results for AEs with moderate and weak clinical priority signals are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The median TTO for moderate and weak signals associated with ticagrelor was 5 days (IQR: 2\u0026ndash;24) and 10 days (IQR: 3\u0026ndash;63), respectively. The Weibull distribution analysis yielded a scale parameter (α) of 86.8 (95% CI: 80.9\u0026ndash;92.6) and a shape parameter (β) of 0.617 (95% CI: 0.598\u0026ndash;0.635). In the WSP analysis, all β values and their 95% confidence interval upper limits were \u0026lt;\u0026thinsp;1, indicating that these moderate and weak priority signals follow an early failure type risk pattern.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTime-to-onset analysis for signals with moderate/weak prioritization.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrioritization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cp\u003eWeibull distribution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eFailure type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTTO(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eScale parameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eShape parameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian(IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin-max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eα\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(2\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1-7307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.1-21.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.48\u0026ndash;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEarly Failure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(3\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1-1047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.83\u0026ndash;47.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.49\u0026ndash;0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEarly Failure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003en,number of cases with available time-to-onset;IQR,interquartile range;TTO,Time-to-onset.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study, based on real-world data from the FAERS database, presents updated findings on the safety profile of ticagrelor concerning respiratory, thoracic, and mediastinal disorders since its market approval. In this study, we presented all AEs associated with ticagrelor at the SOC level (Supplementary Table S3). The results showed that \u0026ldquo;Respiratory, thoracic and mediastinal disorders\u0026rdquo; ranked second in terms of reported case numbers, with a total of 5,779 reports. The highest number of reports was observed in the category of \u0026ldquo;General disorders and administration site conditions,\u0026rdquo; but the signal strength for this SOC was relatively weak (ROR\u0026thinsp;=\u0026thinsp;0.95). Therefore, it can be inferred that the incidence of respiratory, thoracic, and mediastinal disorders during ticagrelor treatment is comparatively higher.\u003c/p\u003e \u003cp\u003eA randomized controlled trial on dual antiplatelet therapy (DAPT) in acute myocardial infarction (AMI) patients found that although all participants initially received ticagrelor, some were later transitioned to clopidogrel. Those who switched experienced significantly lower rates of dyspnea at both 3 months (34.3% vs. 51.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 6 months (25.5% vs. 38.4%, p\u0026thinsp;=\u0026thinsp;0.002) compared to those who remained on ticagrelor(Kim et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In a meta-analysis, ticagrelor was associated with a significantly increased risk of dyspnea compared to clopidogrel, with a pooled risk ratio (RR) of 2.15 (95% CI: 1.59\u0026ndash;2.92). Subgroup analyses showed this increased risk of dyspnea was consistent across various follow-up durations(Zhang et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, our study found that the risk of dyspnea in ticagrelor-treated patients remained significantly elevated across different subgroups defined by sex, age, weight, and reporter type.\u003c/p\u003e \u003cp\u003eCurrent research has recognized the potential risk of respiratory AEs associated with ticagrelor in the treatment of ACS, although the underlying mechanisms remain unclear. Two major hypotheses have been proposed. One suggests that the local accumulation of intracellular cAMP leads to increased adenosine levels, which in turn activate pulmonary vagal C fibers, resulting in dyspnea(Cattaneo and Faioni, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Another theory posits that patients treated with ticagrelor exhibit an exaggerated ventilatory response to hyperoxic hypercapnia (central chemoreceptor hypersensitivity) and normoxic hypercapnia, resulting in hyperventilation and sympathetic excitation that may trigger dyspnea(Nattie and Li, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Marshall, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; O'Regan and Majcherczyk, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Furthermore, some studies suggest that ticagrelor-induced dyspnea may be due to heightened sensitivity of peripheral (PCh) and central (CCh) chemoreceptors, or preexisting hypersensitivity of these receptors before treatment(Tubek et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study evaluated the characteristics of ticagrelor-related adverse events (AEs) in the respiratory, thoracic, and mediastinal systems, and compared serious and non-serious cases. Among the 34 AEs with more than 5 serious cases, 15 showed statistically significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Patient sex (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and body weight (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but not age (p\u0026thinsp;=\u0026thinsp;0.287), were potentially associated with increased severity of respiratory, thoracic, and mediastinal system AEs. Female patients accounted for 38% of severe cases, a proportion significantly higher than that of males, indicating that ticagrelor-related target AEs predominantly occur in females. Numerous studies have demonstrated that certain respiratory diseases are more prevalent in women, such as a higher incidence of symptoms and asthma exacerbations, which lead to reduced quality of life and increased healthcare utilization(Pignataro et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Non-cystic fibrosis bronchiectasis is predominantly a female-predominant disease in most regions, and registry data indicate that 65\u0026ndash;80% of pulmonary arterial hypertension patients are female. Chromosomal sex, sex hormones, and hormone receptors may play complex roles in respiratory diseases(Sodhi et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Few studies have further assessed the influence of sex on ticagrelor-related side effects, and mechanistic research on sex differences in ticagrelor-induced respiratory diseases remains lacking. Broader basic research is necessary to experimentally validate our findings.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that individuals aged 65\u0026ndash;85 years were most susceptible to severe target adverse reactions, accounting for as much as 61%, likely reflecting the predominance of this age group in our study cohort. Moreover, physiological decline and reduced immunity in the elderly increase susceptibility to severe AEs(Biesalski, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, the incidence ratio of severe to non-severe events did not differ significantly across age groups (p\u0026thinsp;=\u0026thinsp;0.287). Subgroup analysis revealed a significant association between ticagrelor use and target adverse reactions in adolescents under 18 years of age, with a stronger correlation compared to other age groups (ROR\u0026thinsp;=\u0026thinsp;6.75, 95% CI: 3.18\u0026ndash;14.36), warranting attention. Recently, ticagrelor has been investigated for reducing vaso-occlusive crises in pediatric sickle cell disease patients, and novel pediatric dispersible ticagrelor tablets have gradually been introduced across a wide pediatric age range(Niazi et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). While exploring new indications, vigilance regarding ticagrelor-induced AEs is warranted. Given the limited indications of ticagrelor in pediatric and adolescent populations, larger clinical studies are needed to further elucidate the relationship between ticagrelor and target adverse reactions.\u003c/p\u003e \u003cp\u003eACS is closely linked to obesity. A meta-analysis demonstrated that a high body mass index (BMI) significantly increases the risk of ACS in young women (RR 2.51; 95% CI: 1.34\u0026ndash;3.68)(Siagian et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although the so-called \u0026ldquo;obesity paradox\u0026rdquo; suggests that obese adults may have a survival advantage post-ACS compared to non-obese adults(Balayah et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), obesity remains an important risk factor for coronary artery disease(Mornar Jelavic et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Dual antiplatelet therapy with aspirin and ticagrelor significantly reduces cardiovascular events after ACS(Content Error, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In our study, patients weighing more than 100 kg had a higher proportion of severe events compared with the non-severe event group (20% vs. 11%), while those weighing less than 100 kg experienced more non-severe target adverse reactions. Stratified analysis revealed a significant association between low body weight (\u0026lt;\u0026thinsp;80 kg) and target adverse reactions (ROR\u0026thinsp;=\u0026thinsp;3.95), with stronger correlations than in medium-weight (80\u0026ndash;100 kg; ROR\u0026thinsp;=\u0026thinsp;2.53) and high-weight groups (100\u0026ndash;200 kg; ROR\u0026thinsp;=\u0026thinsp;2.72). Thus, low body weight (\u0026lt;\u0026thinsp;80 kg) may increase the risk of respiratory, thoracic, and mediastinal adverse reactions in patients taking ticagrelor, whereas higher body weight (\u0026gt;\u0026thinsp;100 kg) is associated with a greater likelihood of severe adverse reactions. Moderate weight reduction may reduce both ACS risk and the incidence of severe AEs.\u003c/p\u003e \u003cp\u003eTo assist clinicians and pharmacovigilance experts in identifying positive signals of drug-related AEs and to guide rational clinical decision-making, we innovatively applied a scoring scale to further analyze disproportionate signals. Ticagrelor-related target disproportionate clinical priority signals with more than 10 cases are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Our analysis identified nine moderate-priority signals: dyspnea, asphyxia, pulmonary edema, pulmonary hemorrhage, dyspnea at rest, pulmonary alveolar hemorrhage, apnea, acute pulmonary edema, and Cheyne-Stokes respiration, along with sixteen weak-priority signals. Notably, among the moderate-priority signals, Cheyne-Stokes respiration exhibited a particularly strong signal strength with a reporting ROR of 68.31 (95% CI: 39.8\u0026ndash;117.24). Additionally, significant AEs such as suffocation feeling (n\u0026thinsp;=\u0026thinsp;54, ROR\u0026thinsp;=\u0026thinsp;26.61, 95% CI: 20.31\u0026ndash;34.86), asphyxia (n\u0026thinsp;=\u0026thinsp;161, ROR\u0026thinsp;=\u0026thinsp;24.08, 95% CI: 20.59\u0026ndash;28.16), nocturnal dyspnea (n\u0026thinsp;=\u0026thinsp;18, ROR\u0026thinsp;=\u0026thinsp;17.09, 95% CI: 10.73\u0026ndash;27.23), dyspnea at rest (n\u0026thinsp;=\u0026thinsp;28, ROR\u0026thinsp;=\u0026thinsp;11.87, 95% CI: 8.18\u0026ndash;17.23), and orthopnea (n\u0026thinsp;=\u0026thinsp;30, ROR\u0026thinsp;=\u0026thinsp;11.02, 95% CI: 7.69\u0026ndash;15.8) were also observed. Most of these AEs are related to respiratory distress. There have been previous reports of ticagrelor-induced Cheyne-Stokes respiration and cardiac arrest(Murat et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Since P2Y12 receptors are expressed not only on platelets but also on other hematopoietic and non-hematopoietic cells, including microglial cells in the central nervous system, potential stimulation of the chemoreflex system may induce Cheyne-Stokes respiration(Giannoni et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This severe respiratory condition may be alleviated by aminophylline infusion or drug discontinuation(Conte et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Minner et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWeibull parameters were employed to predict the time interval prior to AE onset, which can help guide clinical drug use(Mazhar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). TTO analysis showed that moderate- and weak-priority signal AEs had median onset times of 5 and 10 days, respectively, with all disproportionate signals exhibiting early failure characteristics. This indicates that most patients experience respiratory, thoracic, and mediastinal system AEs within two weeks of starting ticagrelor, with the probability of AE occurrence decreasing over time. Similarly, the PLATO clinical trial reported that ticagrelor-induced dyspnea symptoms were more likely to occur within 7 days, with a median duration of 23 days(Storey et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), supporting our findings.Furthermore, among 25 AEs, we newly identified five AEs not previously documented in the drug label: cough, pulmonary edema, chronic obstructive pulmonary disease, bronchospasm, and choking. The effects of ticagrelor on these AEs and their underlying mechanisms remain unclear, warranting further extensive investigation.\u003c/p\u003e \u003cp\u003eAlthough our study utilized real-world data mining from the FAERS database, it is inevitably subject to several limitations common to all pharmacovigilance databases. First, the FAERS database contains underreporting, misreporting, and incomplete reports, which may introduce biases that cannot be accurately quantified. Second, the FAERS database only includes patients who experienced AEs, while the total number of patients treated with ticagrelor is unavailable. Third, causal relationships between ticagrelor and target adverse reactions cannot be established, as disproportionality analysis only indicates a statistical association between ticagrelor and the reported adverse reactions. Therefore, further experimental studies, clinical trials, cohort studies, and case-control studies are warranted to validate our findings in the future.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study comprehensively analyzed the association between ticagrelor and AEs of the respiratory, thoracic, and mediastinal systems based on the FAERS database, yielding several important findings. First, 25 significantly associated signals were detected, of which five AEs were identified as newly discovered signals. Second, patient sex (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and body weight (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), rather than age (p\u0026thinsp;=\u0026thinsp;0.287), may be related to an increased risk of severe respiratory, thoracic, and mediastinal AEs. Third, nine moderate clinical priority signals and sixteen weak clinical priority signals were defined, with median onset times of 5 and 10 days, respectively. All disproportionate signals exhibited early failure characteristics, indicating that most patients experience respiratory, thoracic, and mediastinal system AEs within two weeks of ticagrelor initiation, with the probability of AEs decreasing over time. Our pharmacovigilance study elucidates the potential risks and characteristics of ticagrelor-related respiratory, thoracic, and mediastinal diseases, providing a reference for rational clinical use to reduce the risk of such adverse reactions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors have no relevant financial or non f inancial interests to disclose.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to publish\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: Yuan Zeng, Gong Chen. Data Curation: Yuan Zeng, Lin Lu, Wenwu Zheng. Formal Analysis: Yuan Zeng, Lin Lu. Funding Acquisition: Gong Chen. Investigation:Yuan Zeng. Methodology:Yuan Zeng. Project Administration: Wenwu Zheng. Supervision:Wenwu Zheng. Validation:Yuan Zeng, Gong Chen. Visualization: Yuan Zeng, Lin Lu. Writing \u0026ndash; Original Draft Preparation:Yuan Zeng, Lin Lu. Writing \u0026ndash; Review \u0026amp; Editing: Yuan Zeng, Wenwu Zheng.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to express our sincere gratitude to the individuals who participated in this study, as well as to those who provided invaluable assistance with data analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAngiolillo DJ, Cao D, Sartori S, Baber U, Dangas G, Zhang Z et al (2023) Dyspnea-Related Ticagrelor Discontinuation After Percutaneous Coronary Intervention. JACC Cardiovasc Interv 16(20):2514\u0026ndash;2524. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.jcin.2023.08.019\u003c/span\u003e\u003cspan address=\"10.1016/j.jcin.2023.08.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArora S, Shemisa K, Vaduganathan M, Qamar A, Gupta A, Garg SK et al (2019) Premature Ticagrelor Discontinuation in Secondary Prevention of Atherosclerotic CVD: JACC Review Topic of the Week. J Am Coll Cardiol 73(19):2454\u0026ndash;2464. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.jacc.2019.03.470\u003c/span\u003e\u003cspan address=\"10.1016/j.jacc.2019.03.470\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalayah Z, Alsheikh-Ali AA, Rashed W, Almahmeed W, Mulla AA, Alrawahi N et al (2021) Association of obesity indices with in-hospital and 1-year mortality following acute coronary syndrome. Int J Obes (Lond) 45(2):358\u0026ndash;368. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41366-020-00679-0\u003c/span\u003e\u003cspan address=\"10.1038/s41366-020-00679-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiesalski HK (2021) Obesity, vitamin D deficiency and old age a serious combination with respect to coronavirus disease-2019 severity and outcome. Curr Opin Clin Nutr Metab Care 24(1):18\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1097/mco.0000000000000700\u003c/span\u003e\u003cspan address=\"10.1097/mco.0000000000000700\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCattaneo M, Faioni EM (2012) Why does ticagrelor induce dyspnea? Thromb Haemost 108(6):1031\u0026ndash;1036. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1160/th12-08-0547\u003c/span\u003e\u003cspan address=\"10.1160/th12-08-0547\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCecco S, Puligheddu S, Fusaroli M, Gerratana L, Yan M, Zamagni C et al (2024) Emerging Toxicities of Antibody-Drug Conjugates for Breast Cancer: Clinical Prioritization of Adverse Events from the FDA Adverse Event Reporting System. Target Oncol 19(3):435\u0026ndash;445. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1007/s11523-024-01058-9\u003c/span\u003e\u003cspan address=\"10.1007/s11523-024-01058-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen H (2024) Real-world pharmacovigilance of ofatumumab in multiple sclerosis: a comprehensive FAERS data analysis. Front Pharmacol 15:1521726. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.3389/fphar.2024.1521726\u003c/span\u003e\u003cspan address=\"10.3389/fphar.2024.1521726\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen H, Yang G, Ma J (2024) Ocular toxicity associated with anti-HER2 agents in breast cancer: A pharmacovigilance analysis using the FAERS database. Int J Cancer 154(9):1616\u0026ndash;1625. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1002/ijc.34848\u003c/span\u003e\u003cspan address=\"10.1002/ijc.34848\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConte L, Pugliese NR, Giannoni A (2017) Reversal of Ticagrelor-Induced Arrhythmias and Cheyne-Stokes Respiration With Aminophylline Infusion. J Cardiovasc Pharmacol 70(5):290\u0026ndash;292. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1097/fjc.0000000000000518\u003c/span\u003e\u003cspan address=\"10.1097/fjc.0000000000000518\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eContent Error (2021) JAMA 326(2):190. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1001/jama.2021.9484\u003c/span\u003e\u003cspan address=\"10.1001/jama.2021.9484\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGatti M, Antonazzo IC, Diemberger I, De Ponti F, Raschi E (2021) Adverse events with sacubitril/valsartan in the real world: emerging signals to target preventive strategies from the FDA adverse event reporting system. Eur J Prev Cardiol 28(9):983\u0026ndash;989. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1177/2047487320915663\u003c/span\u003e\u003cspan address=\"10.1177/2047487320915663\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiannoni A, Emdin M, Passino C (2016) Cheyne-Stokes Respiration, Chemoreflex, and Ticagrelor-Related Dyspnea. N Engl J Med 375(10):1004\u0026ndash;1006. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1056/NEJMc1601662\u003c/span\u003e\u003cspan address=\"10.1056/NEJMc1601662\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJavaheri S, Randerath WJ, Badr S, M., Javaheri S (2024) Medication-induced central sleep apnea: a unifying concept. Sleep 47(8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/sleep/zsae038\u003c/span\u003e\u003cspan address=\"10.1093/sleep/zsae038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim SH, Shin S, Choo EH, Choi IJ, Lim S, Moon D et al (2024) Clinical Impact of Dyspnea after Ticagrelor Treatment and the Effect of Switching to Clopidogrel in Patients with Myocardial Infarction. Thromb Haemost 124(12):1152\u0026ndash;1161. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1055/a-2299-4537\u003c/span\u003e\u003cspan address=\"10.1055/a-2299-4537\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Zhang G, Cao X (2023) The Function and Regulation of Platelet P2Y12 Receptor. Cardiovasc Drugs Ther 37(1):199\u0026ndash;216. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1007/s10557-021-07229-4\u003c/span\u003e\u003cspan address=\"10.1007/s10557-021-07229-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarshall JM (1994) Peripheral chemoreceptors and cardiovascular regulation. Physiol Rev 74(3):543\u0026ndash;594. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1152/physrev.1994.74.3.543\u003c/span\u003e\u003cspan address=\"10.1152/physrev.1994.74.3.543\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMazhar F, Battini V, Gringeri M, Pozzi M, Mosini G, Marran AMN et al (2021) The impact of anti-TNFα agents on weight-related changes: new insights from a real-world pharmacovigilance study using the FDA adverse event reporting system (FAERS) database. Expert Opin Biol Ther 21(9):1281\u0026ndash;1290. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1080/14712598.2021.1948529\u003c/span\u003e\u003cspan address=\"10.1080/14712598.2021.1948529\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeng L, Yang B, Qiu F, Jia Y, Sun S, Yang J et al (2021) Lung Cancer Adverse Events Reports for Angiotensin-Converting Enzyme Inhibitors: Data Mining of the FDA Adverse Event Reporting System Database. Front Med (Lausanne) 8:594043. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.3389/fmed.2021.594043\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2021.594043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinner SA, Simone P, Chung BB, Shah AP (2018) Successful Reversal of Bradycardia and Dyspnea With Aminophylline After Ticagrelor Load. J Pharm Pract 31(1):112\u0026ndash;114. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1177/0897190016680978\u003c/span\u003e\u003cspan address=\"10.1177/0897190016680978\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMornar Jelavic M, Babic Z, Pintaric H (2023) Obesity Paradox in the Intrahospital and Follow-Up Phases of the Acute Coronary Syndrome: A Meta-Analysis and Systematic Review. Cardiology 148(6):528\u0026ndash;544. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1159/000531985\u003c/span\u003e\u003cspan address=\"10.1159/000531985\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurat B, Murat S, Kivanc E (2024) Ticagrelor Induced Cheyne-Stokes Respiration and Asystolic Ventricular Standstill: A Case Report. Kardiologiia 64(2):80\u0026ndash;84. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.18087/cardio.2024.2.n2123\u003c/span\u003e\u003cspan address=\"10.18087/cardio.2024.2.n2123\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNattie E, Li A (2012) Central chemoreceptors: locations and functions. Compr Physiol 2(1):221\u0026ndash;254. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1002/cphy.c100083\u003c/span\u003e\u003cspan address=\"10.1002/cphy.c100083\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNiazi M, Wissmar J, Berggren AR, Karlsson C, Johanson P (2019) Development Strategy and Relative Bioavailability of a Pediatric Tablet Formulation of Ticagrelor. Clin Drug Investig 39(8):765\u0026ndash;773. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1007/s40261-019-00800-w\u003c/span\u003e\u003cspan address=\"10.1007/s40261-019-00800-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Regan RG, Majcherczyk S (1982) Role of peripheral chemoreceptors and central chemosensitivity in the regulation of respiration and circulation. J Exp Biol 100:23\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1242/jeb.100.1.23\u003c/span\u003e\u003cspan address=\"10.1242/jeb.100.1.23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan Y, Wang Y, Zheng Y, Chen J, Li J (2024) A disproportionality analysis of FDA adverse event reporting system (FAERS) events for ticagrelor. Front Pharmacol 15:1251961. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.3389/fphar.2024.1251961\u003c/span\u003e\u003cspan address=\"10.3389/fphar.2024.1251961\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePignataro FS, Bonini M, Forgione A, Melandri S, Usmani OS (2017) Asthma and gender: The female lung. Pharmacol Res 119:384\u0026ndash;390. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.phrs.2017.02.017\u003c/span\u003e\u003cspan address=\"10.1016/j.phrs.2017.02.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePujade I, Perino J, Mathieu C, Arnaud M, Raschi E, Gatti M et al (2020) Risk of bradyarrhythmia related to ticagrelor: A systematic review and meta-analysis. Pharmacol Res 160:105089. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.phrs.2020.105089\u003c/span\u003e\u003cspan address=\"10.1016/j.phrs.2020.105089\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosa GM, Bianco D, Valbusa A, Massobrio L, Chiarella F, Brunelli C (2016) Pharmacokinetics and pharmacodynamics of ticagrelor in the treatment of cardiac ischemia. Expert Opin Drug Metab Toxicol 12(12):1491\u0026ndash;1502. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1080/17425255.2016.1244524\u003c/span\u003e\u003cspan address=\"10.1080/17425255.2016.1244524\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalem JE, Manouchehri A, Moey M, Lebrun-Vignes B, Bastarache L, Pariente A et al (2018) Cardiovascular toxicities associated with immune checkpoint inhibitors: an observational, retrospective, pharmacovigilance study. Lancet Oncol 19(12):1579\u0026ndash;1589. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/s1470-2045(18)30608-9\u003c/span\u003e\u003cspan address=\"10.1016/s1470-2045(18)30608-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSerebruany VL, Dinicolantonio JJ, Can MM, Pershukov IV, Kuliczkowski W (2013) Gastrointestinal adverse events after dual antiplatelet therapy: clopidogrel is safer than ticagrelor, but prasugrel data are lacking or inconclusive. Cardiology 126(1):35\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1159/000350961\u003c/span\u003e\u003cspan address=\"10.1159/000350961\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShu Y, Ding Y, Dai B, Zhang Q (2022) A real-world pharmacovigilance study of axitinib: data mining of the public version of FDA adverse event reporting system. Expert Opin Drug Saf 21(4):563\u0026ndash;572. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1080/14740338.2022.2016696\u003c/span\u003e\u003cspan address=\"10.1080/14740338.2022.2016696\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiagian SN, Christianto C, Angellia P, Holiyono HI (2023) The Risk Factors of Acute Coronary Syndrome in Young Women: A Systematic Review and Meta-Analysis. Curr Cardiol Rev 19(3):e161122210969. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.2174/1573403x19666221116113208\u003c/span\u003e\u003cspan address=\"10.2174/1573403x19666221116113208\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSodhi A, Cox-Flaherty K, Greer MK, Lat TI, Gao Y, Polineni D et al (2023) Sex and Gender in Lung Diseases and Sleep Disorders: A State-of-the-Art Review: Part 2. Chest 163(2):366\u0026ndash;382. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.chest.2022.08.2240\u003c/span\u003e\u003cspan address=\"10.1016/j.chest.2022.08.2240\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStorey RF, Becker RC, Harrington RA, Husted S, James SK, Cools F et al (2011) Characterization of dyspnoea in PLATO study patients treated with ticagrelor or clopidogrel and its association with clinical outcomes. Eur Heart J 32(23):2945\u0026ndash;2953. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1093/eurheartj/ehr231\u003c/span\u003e\u003cspan address=\"10.1093/eurheartj/ehr231\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStorey RF, Bliden KP, Patil SB, Karunakaran A, Ecob R, Butler K et al (2010) Incidence of dyspnea and assessment of cardiac and pulmonary function in patients with stable coronary artery disease receiving ticagrelor, clopidogrel, or placebo in the ONSET/OFFSET study. J Am Coll Cardiol 56(3):185\u0026ndash;193. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.jacc.2010.01.062\u003c/span\u003e\u003cspan address=\"10.1016/j.jacc.2010.01.062\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTubek S, Niewinski P, Langner-Hetmanczuk A, Jura M, Kuliczkowski W, Reczuch K et al (2023) The effects of P2Y(12) adenosine receptors' inhibitors on central and peripheral chemoreflexes. Front Physiol 14:1214893. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.3389/fphys.2023.1214893\u003c/span\u003e\u003cspan address=\"10.3389/fphys.2023.1214893\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang N, Xu W, Li O, Zhang B (2020) The risk of dyspnea in patients treated with third-generation P2Y(12) inhibitors compared with clopidogrel: a meta-analysis of randomized controlled trials. BMC Cardiovasc Disord 20(1):140. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1186/s12872-020-01419-y\u003c/span\u003e\u003cspan address=\"10.1186/s12872-020-01419-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"naunyn-schmiedebergs-archives-of-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nsap","sideBox":"Learn more about [Naunyn-Schmiedeberg's Archives of Pharmacology](https://www.springer.com/journal/210)","snPcode":"210","submissionUrl":"https://submission.nature.com/new-submission/210/3","title":"Naunyn-Schmiedeberg's Archives of Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"ticagrelor, respiratory system, adverse events, FAERS, pharmacovigilance study","lastPublishedDoi":"10.21203/rs.3.rs-6798394/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6798394/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTicagrelor has been authorized for use as an antiplatelet therapy in individuals diagnosed with acute coronary syndrome (ACS). While numerous clinical trials have reported respiratory-related AEs associated with ticagrelor, real-world evidence from large populations remains limited. In this study, we aimed to assess the safety signals of respiratory, thoracic, and mediastinal disorders related to ticagrelor using data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS).This study utilized data from the FAERS database spanning 2011 to 2024. The reporting odds ratio (ROR) was used to quantify safety signals of respiratory, thoracic, and mediastinal adverse events associated with ticagrelor. Chi-square (χ\u0026sup2;) or Fisher\u0026rsquo;s exact tests were used to compare serious versus non-serious cases. A prioritization scale was applied to rank the identified signals. Additionally, the Weibull distribution was used to model the time-to-onset(TTO) risk of AEs.A total of 4,605 respiratory, thoracic, and mediastinal AEs associated with ticagrelor were identified, with 25 significant safety signals detected. Patient sex (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and weight (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with increased risk of serious AEs, whereas no association was observed with age (p\u0026thinsp;=\u0026thinsp;0.287). Stratified analyses confirmed the consistent association between ticagrelor and respiratory, thoracic, and mediastinal risks. Nine signals were classified as moderate clinical priority and sixteen as weak priority. Notably, all respiratory, thoracic, and mediastinal AEs exhibited an early failure pattern. This pharmacovigilance study systematically investigated ticagrelor-associated respiratory, thoracic, and mediastinal disorders to support clinicians in optimizing cardiovascular treatment strategies.\u003c/p\u003e","manuscriptTitle":"Respiratory, thoracic, and mediastinal adverse events associated with ticagrelor: A pharmacovigilance study based on FDA adverse event reporting system","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 15:47:09","doi":"10.21203/rs.3.rs-6798394/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-11T13:13:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-11T12:56:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"285594837482043005198485709876901317029","date":"2025-06-11T12:30:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-11T11:58:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-04T04:42:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-04T04:41:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Naunyn-Schmiedeberg's Archives of Pharmacology","date":"2025-06-02T03:04:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"naunyn-schmiedebergs-archives-of-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nsap","sideBox":"Learn more about [Naunyn-Schmiedeberg's Archives of Pharmacology](https://www.springer.com/journal/210)","snPcode":"210","submissionUrl":"https://submission.nature.com/new-submission/210/3","title":"Naunyn-Schmiedeberg's Archives of Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5f42b51d-8330-42bb-b28f-74f7c34d9665","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T16:09:00+00:00","versionOfRecord":{"articleIdentity":"rs-6798394","link":"https://doi.org/10.1007/s00210-025-04428-w","journal":{"identity":"naunyn-schmiedebergs-archives-of-pharmacology","isVorOnly":false,"title":"Naunyn-Schmiedeberg's Archives of Pharmacology"},"publishedOn":"2025-07-16 16:05:40","publishedOnDateReadable":"July 16th, 2025"},"versionCreatedAt":"2025-06-17 15:47:09","video":"","vorDoi":"10.1007/s00210-025-04428-w","vorDoiUrl":"https://doi.org/10.1007/s00210-025-04428-w","workflowStages":[]},"version":"v1","identity":"rs-6798394","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6798394","identity":"rs-6798394","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}