Final Diagnoses and Mortality Rates Among Patients Receiving Inhaled Bronchodilators During Ambulance Transportation

Final Diagnoses and Mortality Rates Among Patients Receiving Inhaled Bronchodilators During Ambulance Transportation | 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 Final Diagnoses and Mortality Rates Among Patients Receiving Inhaled Bronchodilators During Ambulance Transportation Victor Hagenau, Mathilde Gundgaard Mulvad, Jan Brink Valentin, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4177535/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Nov, 2024 Read the published version in Internal and Emergency Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract Objectives : To assess final diagnoses and mortality rates (30-day and 1-year) in patients requiring inhaled bronchodilators administered by ambulance personnel. Methods : In a retrospective observational cohort study, patients experiencing respiratory distress and treated with inhaled bronchodilators in the prehospital setting within the Central Denmark Region during 2018-2019 were included. Results : The study included 6,318 ambulance transports, comprising 3,686 cases of acute exacerbation of chronic obstructive pulmonary disease (AECOPD), 234 with community-acquired pneumonia (CAP), 320 with heart disease (HD), 233 adults with asthma, 1,674 with various other primary ICD-10 diagnoses (other ≥18 years), and 171 patients under 18 years. The 30-day mortality rate for all patients was 10.7% (95% CI 9.8-11.6), with zero deaths within 30 days among adults with asthma and those under 18. Excluding low mortality groups, AECOPD patients had the lowest 30-day mortality at 10.2% (95% CI 9.1-11.3), and HD patients the highest at 15.3% (95% CI 10.6-19.9). The 1-year overall mortality rate increased to 32.1% (95% CI 30.2-34.0), with mortality staying low for asthma and under-18 groups, while differences between other groups lessened and became insignificant. Conclusions : Patients requiring inhaled bronchodilator treatment in ambulances exhibit notably high mortality rates at 30 days and 1 year, except for those with asthma or under 18. The need for prehospital bronchodilators could serve as a clear and unmistakable marker for moderate to severe respiratory distress, enabling early intervention. Emergency Medical Services Lung Diseases Bronchodilator Agents Respiratory Insufficiency Figures Figure 1 Background Respiratory distress frequently leads to prehospital contact, accounting for 6-12% of total hospital admissions facilitated by the emergency medical service (EMS).[1–6] Of these patients, up to 40% receive a non-pulmonary diagnosis upon discharge [1,3], because a multitude of illnesses can result in respiratory distress. Community-acquired pneumonia (CAP), congestive heart failure (CHF), acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and acute asthma are the predominant prehospital conditions associated with this state.[3,7] Among hospitalized patients, CAP, CHF, and AECOPD collectively exhibit a similar 30-day mortality rate of approximately 10%. To specify, CHF presents a range of 7.8% to 15% [7–9], AECOPD from 5% to 11.5% [7,10–13], and for CAP, the range varies from 7% to 13% in hospitalized patients [14–16] and increases to 15.6-27% in intensive care unit (ICU) cases.[17,18] In contrast, asthma patients transported by ambulance experience exceptionally low mortality.[7] Earlier research has used diverse definitions to characterize respiratory distress in the prehospital setting. At the milder end of this spectrum, this condition has often been identified based on the EMS providers' impression that the initial EMS contact was for a respiratory-related reason.[1,19] Notably, in the studies conducted by Prekker et al. and Lindskou et al., only 50% and 63% of the identified patients, respectively, were subsequently admitted to a hospital. Alternatively, respiratory distress has been characterized based on the dispatch code assigned by the Emergency Medical Dispatch Center,[2,4,5] and it has also been defined only as dyspnea necessitating admission to an Emergency Department.[3,20] In the study conducted by Pozner et al., eligible patients for inclusion were those who required both hospitalization and treatment for respiratory distress, including medications, advanced airway management, or cardiac monitoring.[20] A method to identify a group of patients with respiratory distress in the prehospital setting might include treatment targeting respiratory difficulties directly such as inhaled bronchodilators. Prehospital treatment with inhaled bronchodilators stimulates β2-receptors in bronchial smooth muscles, promoting airway relaxation and improved airflow, alleviating respiratory distress due to bronchoconstriction.[21] Not all patients experiencing respiratory distress receive treatment with inhaled bronchodilators; the utilization rate for these medications in cases of respiratory distress varies between 20% and 55%.[3,7,22] However, in the Central Denmark Region, it is recommended to administer inhaled bronchodilators to all patients having symptoms of prolonged expiration and respiratory distress. Inhaled bronchodilator treatment may serve as an identifier for a homogeneous group of patients with moderate to severe respiratory distress in the prehospital setting - an unambiguously easy identifiable patient cohort not previously examined. This study aims to determine the final diagnoses and mortality rates (30-day and 1-year) among patients treated with inhaled bronchodilators in the prehospital setting and admitted to the hospital. Methods Study design and setting This study was an observational cohort study including patients treated with inhaled bronchodilators in the prehospital setting in the Central Denmark Region in 2018-2019. This study adhered to the STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology).[23] The regional Emergency Medical Service The region is populated by 1.3 million inhabitants, constituting 23% of the entire Danish population. Within the region there are 8 hospitals differing in size and specialization, with five of them equipped with an emergency department. The Central Denmark Region has contracted three distinct ambulance services, with a combined workforce of about 650 EMS providers operating 70 ambulances.[24,25] Ambulances are deployed through the Emergency Medical Dispatch Center (EMDC) when responding to calls received via the national emergency number (112) or calls received directly from the patient’s primary care physician. Each ambulance is staffed by two EMS providers, consisting of either emergency medical technicians or paramedics. Furthermore, the EMDC can dispatch a medical emergency care unit staffed by a prehospital anesthesiologist and a paramedic. Patient transportation primarily prioritizes the nearest hospital, occasionally taking into account the specific medical condition.[25] Study population Patients were included in the study if they received treatment with an inhaled β2 bronchodilator medication (specifically salbutamol) either at the prehospital scene or while being transported by ambulance between January 2018 and December 2019. COVID-19 did not influence EMS management in the study period. We excluded patients with unknown Civil Registration Numbers, and patients that were not admitted to a hospital in the Central Denmark Region. The latter applied to cases where treatment was completed at the scene or when patients were admitted to hospitals located outside the region. Exposure Included patients were divided into six groups based on the main diagnosis established at the hospital. Using the ICD-10 classification system, we identified the following groups: patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), community-acquired pneumonia (CAP), any heart-related disease (HD), asthma, patients with another primary ICD-10 (other ≥18 years) and patients under the age of 18 (patients <18 years) (Supplemental Table S3) For patients to be classified as having AECOPD, it was necessary for their primary diagnosis to be COPD or for COPD to be listed as a secondary diagnosis alongside a primary diagnosis indicating a lung infection or displaying airway-related symptoms suggestive of a COPD exacerbation (Supplemental Table S3). COPD was defined as the ICD-10 codes J40-J44.[26] Supplemental Table S3 contains comprehensive lists of primary ICD-10 diagnoses for the different patient groups. Outcome The primary outcome was all-cause 30 day mortality and secondary outcome was all-cause 1-year mortality. Data Sources Data from the electronic Prehospital Patient Record (ePPR) utilized by EMS providers were used to identify patients who received inhaled bronchodilator treatment (Salbutamol) during the prehospital phase of care. Vital sign data were also obtained from the ePPR. Prehospital transport data were retrieved from the dispatch system Logis used in the Emergency Medical Dispatch Center. Additionally, data on 30-day and 1-year mortality, length of stay, primary discharge diagnosis, and 10 years of historical diagnoses to determine comorbidity were extracted from the electronic patient record used in hospitals within the Central Denmark Region Statistics Basal characteristics, vital sign, comorbidities, readmission rate, length of hospital stay and in-hospital treatment were compared between exposure groups as frequencies and percentages or median and interquartile range (IQR) where appropriate. These numbers were presented for all observations as well as unique patients, where in the latter case we used the last observation in chronological order. Comorbidities were categorized according to the Charlson Comorbidity Index based on the ICD-10 diagnostic coding method as specified by Thygesen et al.[27] Outcomes were presented as incidence rates (IR) and incidence rate ratios (IRR) with 95% confidence intervals (CI) using Poisson regression analysis with the AECOPD group as reference. We used cluster-robust variance to alleviate the assumption of independent observations for patients with multiple observations. In addition, patients with multiple observations were censored at the time of readmission if this occurred within the follow-up period. All analyses were stratified by sex, however, since the exposure group definitions were inherently associated with age and comorbidities, we did not adjust for these. Statistical analyses were performed using Stata 18.0 (StataCorp. 2023. Stata Statistical Software: Release 18 . College Station, TX: StataCorp LLC.). Results In 2018 and 2019, a total of 4,261 patients received prehospital inhaled bronchodilator treatment during 6,318 ambulance transports in the Central Denmark Region. The final study cohort was reached after the exclusion of 330 cases lacking primary outcome data, 15 due to hospital admissions outside the region, 62 from home treatment without hospitalization, and 253 having unaccountable missing data (Figure 1). Within the study cohort, there were 6,147 adults (18 years and older) and 171 patients under 18. Among adults, 3,686 cases were diagnosed with acute COPD exacerbation, 234 with CAP, 320 with heart disease, and 233 adults with asthma. Additionally, 1,674 cases fell under other primary ICD-10 categories (other ≥18 years). Moreover, 889 cases had established COPD without acute exacerbation, including 165 in the heart disease group, 718 in the “other ≥18 years” group, and 6 in the under-18 age category. Among the 6,318 ambulance transports analyzed, 2,057 cases involved readmissions within the study period, resulting in a readmission rate of 32.6% (95% CI 31.4-33.7). The readmission rate showed no significant difference between sexes (data not shown). During the two-year study period, the distribution of readmissions was as follows: 588 patients were readmitted once, 228 patients twice, 166 patients between three and five times, 34 patients more than five times, and 11 patients more than ten times. In all patient groups, except for the under-18 years category, there was a slight to moderate predominance of female participants, ranging from 52.3% to 69.5%. In the under-18 years category, the proportion of females was only 42.7% (Table 1). In terms of age, the AECOPD, CAP, HD, and “other ICD-10 ≥18 years” groups displayed a comparable median age, ranging from 73 to 78 years. Participants in the asthma group had a notably lower median age of 45 years, while for patients under 18 years of age, the median age was 4. The prevalence and distribution of comorbidities showed significant similarities between the AECOPD and the “other ICD-10 ≥18 years” group, possibly influenced by a relatively large proportion of known COPD patients in the latter. Similarly, comorbidity patterns between the asthma and under-18 groups were comparably infrequent, with a consistently higher prevalence of comorbidities in the asthma group, likely due to its higher median age. The HD group displayed a distinct comorbidity profile with a notably high prevalence of prior myocardial infarction and congestive heart disease, along with the highest rates of hypertension, diabetes mellitus, renal disease, and atherosclerosis-related comorbidities such as peripheral vascular disease, cerebrovascular disease, and dementia (Table 2). These findings were further correlated with the Charlson Comorbidity Score, revealing that the asthma and under-18 groups exhibited the lowest scores, while the remaining groups demonstrated relatively similar scores, with the highest scores observed in the HD group (Table 2). In assessing vital signs, comparable values were observed across the groups in terms of respiratory rate, heart rate, systolic, and diastolic blood pressures, except for individuals under the age of 18. This subgroup displayed lower blood pressure and a higher pulse rate, aligning with expected physiological variances in this age category. Notably, oxygen saturation levels exhibited variations among the groups. The asthma group and individuals under 18 demonstrated the highest oxygen saturation levels, whereas the AECOPD, CAP, and HD categories manifested the lowest levels within the study cohort (Table 1). Exclusively considering unique patient IDs did not alter baseline characteristics, comorbidity, and physiological parameters (supplemental Table S1 and S2). The length of hospital stay varied little among all groups (0.6-1.5 days). The HD group had the highest proportion of cases admitted to the ICU (Table 1). Table 1. Basal characteristics, hospital admission and physiological parameters Factor AECOPD CAP Heart disease Asthma Other ≥18 years < 18 years N 3,686 234 320 233 1,674 171 Sex (female) 1,944 (52.7%) 144 (61.5%) 171 (53.4%) 162 (69.5%) 875 (52.3%) 73 (42.7%) Age, median (IQR) 74 (66-80) 74 (60-82) 78 (72-84) 45 (26-62) 73 (61-81) 4 (1-11) Length of hospital stay, mean (SD) 1.0 (2.3) 1.1 (2.3) 1.5 (3.1) 0.6 (1.2) 0.7 (2.1) 0.6 (1.1) ICU admission, n (%) 40 (1.1%) 3 (1.3%) 13 (4.1%) 1 (0.4%) 13 (0.8%) 2 (1.2%) Physiological (vital) parameters (initial assessment in the ambulance) Respiratory rate, median (IQR) 30 (24-33) 28 (24-32) 30 (24-34) 28 (22-30) 28 (24-32) 32 (25-42) Systolic blood pressure, median (IQR) 152 (135-174) 150 (133-170) 155 (131-178.5) 148.5 (131-162.5) 150 (131-172) 123 (112-134) Diastolic blood pressure, median (IQR) 86 (74-100) 85 (74-98) 91.5 (75-109) 88.5 (76-98) 87 (74-100) 77 (65-84) Heart rate, median (IQR) 104 (89-117) 105 (88-119) 103 (82-121) 104 (91-118.5) 100 (84-116) 125 (102-143) GCS, median (IQR) 15 (15-15) 15 (15-15) 15 (15-15) 15 (15-15) 15 (15-15) 15 (15-15) SpO2 <88, n (%) 1,337 (36.7%) 83 (35.8%) 131 (41.5%) 27 (11.9%) 501 (30.3%) 15 ( 9.3%) SpO2 88-92%, n (%) 808 (22.2%) 54 (23.3%) 58 (18.4%) 32 (14.1%) 343 (20.8%) 25 (15.4%) SpO2 93-96%, n (%) 894 (24.6%) 57 (24.6%) 79 (25.0%) 75 (33.0%) 396 (24.0%) 38 (23.5%) SpO2 97-100%, n (%) 602 (16.5%) 38 (16.4%) 48 (15.2%) 93 (41.0%) 411 (24.9%) 84 (51.9%) Table 1: Basal characteristics, hospital admission and physiological parameters AECOPD = acute exacerbation of chronic obstructive pulmonary disease, CAP = Community-acquired pneumonia, HD = heart disease, Other ≥18 years = other primary ICD-10 categories, ICU = intensive care unit, GCS = Glasgow Coma Scale; SpO2 = Peripheral Capillary Oxygen Saturation measured by pulse oximeter. Table 2 10-year comorbidity Factor AECOPD CAP Heart Disease Asthma Other ≥18 years <18 years N 3,686 234 320 233 1,674 171 Myocardial infarction 290 (7.9%) 14 ( 6.0%) 56 (17.5%) 4 (1.7%) 117 (7.0%) 0 ( 0.0%) Congestive heart failure 596 (16.2%) 19 (8.1%) 131 (40.9%) 4 (1.7%) 268 (16.0%) 0 (0.0%) Peripheral vascular disease 432 (11.7%) 16 (6.8%) 49 (15.3%) 6 (2.6%) 175 (10.5%) 0 (0.0%) Cerebrovascular disease 469 (12.7%) 31 (13.2%) 47 (14.7%) 5 (2.1%) 232 (13.9%) 1 (0.6%) Hemiplegia 17 (0.5%) 2 (0.9%) 1 (0.3%) 0 (0.0%) 8 (0.5%) 2 (1.2%) Dementia 83 (2.3%) 8 (3.4%) 15 (4.7%) 3 (1.3%) 49 (2.9%) 0 (0.0%) Chronic pulmonary disease * 3,458 (93.8%) 34 (14.5%) 176 (55.0%) 146 (62.7%) 864 (51.6%) 85 (49.7%) Diabetes mellitus (without complications) 215 (5.8%) 12 (5.1%) 25 (7.8%) 4 (1.7%) 100 (6.0%) 1 (0.6%) Diabetes mellitus (with chronic complications) 158 (4.3%) 17 (7.3%) 28 (8.8%) 2 (0.9%) 101 (6.0%) 0 (0.0%) Mild liver disease 63 (1.7%) 3 (1.3%) 2 (0.6%) 0 (0.0%) 40 (2.4%) 0 (0.0%) Moderate/severe liver disease 14 (0.4%) 3 (1.3%) 0 (0.0%) 0 (0.0%) 14 (0.8%) 0 (0.0%) Connective tissue disease 148 (4.0%) 13 (5.6%) 18 (5.6%) 12 (5.2%) 77 (4.6%) 1 (0.6%) Ulcer disease 142 (3.9%) 11 (4.7%) 14 (4.4%) 0 (0.0%) 68 (4.1%) 0 (0.0%) Moderate/severe renal disease 338 (9.2%) 17 (7.3%) 53 (16.6%) 10 (4.3%) 171 (10.2%) 0 (0.0%) Any tumor 496 (13.5%) 37 (15.8%) 49 (15.3%) 5 (2.1%) 242 (14.5%) 0 (0.0%) Leukemia 11 (0.3%) 4 (1.7%) 2 (0.6%) 0 (0.0%) 7 (0.4%) 0 (0.0%) Lymphoma 44 (1.2%) 1 (0.4%) 2 (0.6%) 1 (0.4%) 17 (1.0%) 0 (0.0%) Metastatic solid tumor 52 (1.4%) 8 (3.4%) 7 (2.2%) 2 (0.9%) 41 (2.4%) 0 (0.0%) AIDS 1 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (0.2%) 0 (0.0%) Charlson Comorbidities Score Score 0 3 (0.1%) 18 (7.7%) 0 (0.0%) 46 (19.7%) 126 (7.5%) 84 (49.1%) Score 1 93 (2.5%) 22 (9.4%) 6 (1.9%) 89 (38.2%) 114 (6.8%) 84 (49.1%) Score 2 214 (5.8%) 22 (9.4%) 12 (3.8%) 24 (10.3%) 147 (8.8%) 1 (0.6%) Score 3 543 (14.7%) 30 (12.8%) 30 ( 9.4%) 24 (10.3%) 201 (12.0%) 2 (1.2%) Score 4 796 (21.6%) 53 (22.6%) 54 (16.9%) 29 (12.4%) 288 (17.2%) 0 (0.0%) Score 5 714 (19.4%) 34 (14.5%) 60 (18.8%) 14 (6.0%) 286 (17.1%) 0 (0.0%) Score 6 618 (16.8%) 18 (7.7%) 42 (13.1%) 5 (2.1%) 195 (11.6%) 0 (0.0%) Score 7 343 (9.3%) 10 (4.3%) 47 (14.7%) 0 (0.0%) 120 (7.2%) 0 (0.0%) Score 8 170 (4.6%) 11 (4.7%) 29 (9.1%) 0 (0.0%) 89 (5.3%) 0 (0.0%) Score 9 88 (2.4%) 10 (4.3%) 20 (6.2%) 1 (0.4%) 51 (3.0%) 0 (0.0%) Score 10 48 (1.3%) 4 (1.7%) 7 (2.2%) 1 (0.4%) 28 (1.7%) 0 (0.0%) Score 11 30 (0.8%) 1 (0.4%) 10 (3.1%) 0 (0.0%) 17 (1.0%) 0 (0.0%) Score 12 18 (0.5%) 1 (0.4%) 3 (0.9%) 0 (0.0%) 7 (0.4%) 0 (0.0%) Score 13 8 (0.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 4 (0.2%) 0 (0.0%) Score 16 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (0.1%) 0 (0.0%) Table 2: 10-year Charlson comorbidities based on ICD-10 codes. *AECOPD patients excluded from this category received their first diagnosis of COPD during the current admission. AECOPD = acute exacerbation of chronic obstructive pulmonary disease, CAP = Community-acquired pneumonia, HD = heart disease, Other ≥18 years = other primary ICD-10 categories. AIDS = Acquired Immunodeficiency Syndrome. Within 30 days of hospital admission, 593 patients in the study population died, resulting in a total mortality rate (IR) of 10.7% (95% CI 9.8-11.6). The 30-day mortality rate in the AECOPD group was 10.2% (95% CI 9.1-11.3), lower than the rates in the CAP, HD, and "other ≥18 years" groups, which had 30-day mortality rates of 12.1% (95% CI 7.4-16.8), 15.3% (95% CI 10.6-19.9), and 13.5% (95% CI 11.5-15.4), respectively (Table 3). Notably, in both the asthma and “patients under 18 years” groups, no deaths occurred within 30 days after admission (Table 3). When conducting a relative comparison of 30-day mortality using AECOPD as the reference, the CAP group exhibited an insignificant 18.7% increase in the mortality rate (IRR 1.187 (95% CI 0.792-1.781)), while the HD and "Other ≥18 years" groups demonstrated significant increased rates of 49.5% (IRR 1.495, 95% CI 1.079-2.072) and 32.0% (IRR 1.320, 95% CI 1.103-1.579), respectively (Table 3). Within 1 year of hospital admission, 1255 patients died, resulting in a total 1-year mortality rate (IR) of 32.1% (95% CI 30.2-34.0). Interestingly, when considering the 1-year mortality rates, the differences between groups diminished to insignificant increased mortality rates ranging from 1.2% to 15.2% (IRR 1.012 (95% CI 0.763-1.343) - IRR 1.152 (95% CI 0.905-1.466)) in the CAP, HD, and "Other ≥18 years" groups. The 1-year mortality rates remained very low in both the asthma and “patients under 18 years” groups at 2.5% (95% CI 0.3-4.8) and 0.6% (95% CI 0.0-1.9). The 30-day mortality rates observed among males and females showed differences within the CAP, 'Other ≥18 years', and HD groups. In the CAP group, the 30-day mortality rate (IR) for females was 8.9% (95% CI 3.8-14.0), compared with 17.5% (95% CI 8.1-26.9) for males; in the 'Other ≥18 years' group, the rate was 12.3% (95% CI 9.8-14.8) for females versus 14.7% (95% CI 11.9-17.6) for males. Conversely, in the HD group, females exhibited a higher 30-day mortality rate of 16.8% (95% CI 10.0-23.5) compared to 13.6% (95% CI 7.1-20.0) for males (Table 4). These sex-based disparities also extended to the 1-year mortality rate. In the CAP group, females had a lower mortality rate of 29.8% (95% CI 19.0-40.6) compared to 42.0% (95% CI 24.8-59.3) for males. Similarly, in the 'Other ≥18 years' group, the mortality rate for females was 33.3% (95% CI 28.2-38.3) versus 40.7% (95% CI 34.8-46.6) for males. Meanwhile, in the HD group, females still exhibited the highest 1-year mortality rate at 42.3% (95% CI 29.6-55.0), compared to 35.4% (95% CI 23.0-47.7) for males. Table 3. Absolute and relative 30-day and 1-year mortality Absolute 30-day mortality Groups IR (95% CI) AECOPD 0.102 (0.091-0.113) Community-acquired pneumonia (CAP) 0.121 (0.074-0.168) Heart Disease (HD) 0.153 (0.106-0.199) Astma 0.000 (0.000-0.000) Other ≥18 years 0.135 (0.115-0.154) Patients < 18y 0.000 (0.000-0.000) Total 0.107 (0.098-0.116) Relative 30-day mortality with the AECOPD group as reference Groups IRR (95% CI) AECOPD 1 (ref) Community-acquired pneumonia (CAP) 1.187 (0.792-1.781) Heart Disease (HD) 1.495 (1.079-2.072) Astma n/a Other ≥18 years 1.320 (1.103-1.579) Patients < 18y n/a Absolute 1-year mortality Groups IR (95% CI) AECOPD 0.339 (0.312-0.366) Community-acquired pneumonia (CAP) 0.343 (0.250-0.436) Heart Disease 0.390 (0.302-0.479) Astma 0.025 (0.003-0.048) Other ≥18 years 0.368 (0.329-0.406) Patients < 18y 0.006 (0.000-0.019) Total 0.321 (0.302-0.340) Relative 1-year mortality with the AECOPD group as reference Groups IRR (95% CI) AECOPD 1 (ref) Community-acquired pneumonia (CAP) 1.012 (0.763,1.343) Heart Disease 1.152 (0.905,1.466) Astma 0.075 (0.031,0.180) Other ≥18 years 1.085 (0.951,1.238) Patients < 18y 0.019 (0.003,0.133) Table 3: Absolute and relative 30-day and 1-year mortality presented as incidence rates (IR) and incidence rate ratios (IRR) with 95% confidence intervals (CI). AECOPD = acute exacerbation of chronic obstructive pulmonary disease, Other ≥18 years = other primary ICD-10 categories. Table 4 Absolute and relative 30-day and 1-year mortality stratified by sex Females Males Patients (unique ID) 2293 1968 Ambulance transports, n 3369 2949 Age all groups, median (IQR) 73 (63; 80) 73 (63; 80) Absolute 30-day mortality Groups IR (95% CI) Females IR (95% CI) Males AECOPD 0.104 (0.088-0.120) 0.099 (0.083-0.116) CAP 0.089 (0.038-0.140) 0.175 (0.081-0.269) Heart Disease 0.168 (0.100-0.235) 0.136 (0.071-0.200) Astma 0.000 (0.000-0.000) 0.000 (0.000-0.000) Other ≥18 years 0.123 (0.098-0.148) 0.147 (0.119-0.176) Patients < 18y 0.000 (0.000-0.000) 0.000 (0.000-0.000) Total 0.104 (0.092-0.116) 0.110 (0.097-0.124) Relative 30-day mortality with AECOPD as reference Groups IRR (95% CI) Females IRR (95% CI) Males AECOPD 1 (ref) 1 (ref) CAP 0.853 (0.473,1.539) 1.763 (1.005-3.092) Heart Disease 1.608 (1.046,2.471) 1.363 (0.825-2.253) Astma n/a n/a Other ≥18 years 1.179 (0.914,1.521) 1.483 (1.150-1.913) Patients < 18y n/a n/a Absolute 1-year mortality Groups IR (95% CI) Females IR (95% CI) Males AECOPD 0.334 (0.297,0.370) 0.345 (0.305-0.385) CAP 0.298 (0.190,0.406) 0.420 (0.248-0.593) Heart Disease 0.423 (0.296,0.550) 0.354 (0.230-0.477) Astma 0.037 (0.005,0.070) 0.000 (0.000-0.000) Other ≥18 years 0.333 (0.282,0.383) 0.407 (0.348-0.466) Patients < 18y 0.000 (0.000,0.000) 0.011 (0.000-0.031) Total 0.308 (0.283,0.333) 0.336 (0.308-0.365) Relative 1-year mortality with AECOPD as reference Groups IRR (95% CI) Females IRR (95% CI) Males AECOPD 1 (ref) 1 (ref) CAP 0.894 (0.612-1.305) 1.218 (0.796-1.866) Heart Disease 1.267 (0.921-1.743) 1.025 (0.709-1.482) Astma 0.112 (0.046-0.270) 0.000 (0.000-0.000) Other ≥18 years 0.998 (0.828-1.202) 1.179 (0.979-1.421) Patients < 18y 0.000 (0.000-0.000) 0.031 (0.004-0.217) Table 4: Absolute and relative 30-day and 1-year mortality with the AECOPD group as reference presented as incidence rates (IR) and incidence rate ratios (IRR) with 95% confidence intervals (CI). AECOPD = acute exacerbation of chronic obstructive pulmonary disease, CAP = Community-acquired pneumonia, HD = heart disease, Other ≥18 years = other primary ICD-10 categories. Discussion This study characterizes patients receiving inhaled bronchodilator treatment during the prehospital phase of care. Individuals requiring prehospital inhaled bronchodilators constitute a complex and critically ill cohort with a diverse range of comorbidities and high mortality rates. The 30-day all-cause mortality observed in this study totaled 10.7% - comparable to findings in other studies on prehospital respiratory distress.[ 1 , 2 , 7 , 19 , 28 ] A 1-year mortality rate of 32.1% was identified in the total study cohort, a figure also confirmed by Bøtker et al.[ 2 ] The 1-year mortality rate showed relatively limited variations between groups (33.9–39.0%), except for adults with asthma and the group of patients under 18 years where very low mortality rates were observed. Except for these two patient groups, this study's findings underscore that respiratory distress necessitating inhaled bronchodilator treatment in the ambulance represents an exceptionally life-threatening condition. Although AECOPD is typically associated with high 30-day mortality rates [ 11 , 29 , 30 ], it unexpectedly had the lowest mortality rate among the studied groups once asthma and patients younger than 18 were excluded. The HD group experienced a significantly higher mortality rate, with a 49.5% increase in 30-day mortality compared to the AECOPD group. This disparity may stem from the study's inclusion criteria, which likely selected more severe HD cases needing bronchodilator treatment for conditions such as pulmonary edema. Additionally, the HD group had a higher incidence of comorbidities than the other groups (AECOPD, CAP, and "Other ≥ 18 years"), as well as the lowest initial oxygen saturations in the ambulance, a factor independently linked to a high mortality rate. [ 31 , 32 ] Furthermore, HD patients experienced longer hospital stays and were more frequently admitted to the ICU, indicating a greater severity of their condition. However, when focusing on 1-year mortality rates, the differences between groups became less pronounced. Nevertheless, all groups, except for those with asthma and those younger than 18, exhibited extremely high mortality rates, with the HD group at 39.0%. Research has shown that distinguishing between cardiac-triggered dyspnea and lung-triggered dyspnea in the prehospital setting is difficult [ 20 , 33 ], which might delay targeted treatments, such as diuretics. Moreover, the efficacy of inhaled bronchodilator treatment in patients with heart disease, who do not have COPD, remains uncertain and has been subject to debate.[ 34 ] Point-of-care ultrasound could help paramedics to perform more accurate diagnostics in the prehospital phase.[ 35 , 36 ] Two distinct groups were included in this study: adults with asthma and individuals aged 18 years and younger. These groups stand out from the rest of the cohort, even though they present with respiratory distress requiring inhaled bronchodilator treatment. Both the asthma group and those 18 years and younger have significantly fewer comorbidities and the lowest mortality rates. Notably, the asthma group comprises a significant majority of female participants, at 69.5%. This may indicate a higher prevalence and severity of asthma in women, a phenomenon previously documented in literature.[ 37 , 38 ] Patients in this study were exclusively identified by a clear prehospital marker: the need for inhaled bronchodilator treatments in ambulances, indicating respiratory distress. This approach contrasts with previous studies that utilized various methods to identify prehospital respiratory distress, such as retrospective analysis post-hospital admission [ 28 , 39 ], dispatch reference work codes from Emergency Medical Dispatch Centers [ 2 ], or subjective impressions of respiratory distress by EMS providers.[ 1 , 20 , 40 ] The diversity in identification methods highlights the diagnostic challenges of prehospital respiratory distress.[ 19 , 20 , 28 , 41 ] A reliable and straightforward prehospital identifier is essential not only for facilitating timely interventions [ 7 , 11 , 42 , 43 ] but also for ensuring accurate identification of patients for research purposes.[ 43 , 44 ] The need for inhaled bronchodilator treatment serves as an effective prehospital marker for significant respiratory distress. Furthermore, our study categorized patients into the same four primary groups identified in previous studies - heart failure, COPD, community-acquired pneumonia, and mixed diagnoses. This categorization might account for the relatively similar mortality rates observed across studies among patients admitted to hospital.[ 7 , 19 , 28 , 33 ] When compared to previously applied definitions of respiratory distress [ 1 , 19 ], the need for inhaled bronchodilator treatment almost exclusively identifies patients bound for hospital admission. This group of patients is most likely to benefit from early interventions. The combination of inhaled bronchodilator treatment and point-of-care ultrasound examinations could assist paramedics in assessing the severity and potentially the cause of respiratory distress, enabling rapid and tailored prehospital treatment.[ 7 , 11 , 42 ] However, further research is necessary to evaluate the effectiveness of multimodal approaches in identifying respiratory distress in the prehospital setting. One limitation of this study on respiratory distress is the exclusive inclusion of patients who required prehospital bronchodilator treatment, potentially introducing selection bias if the goal was to encompass all individuals experiencing respiratory distress. Nonetheless, this criterion also constitutes a strength, as it ensured the easy identification of all participants, specifically including those with moderate to severe distress—individuals for whom early intervention might be particularly beneficial. Additionally, the Danish Prehospital Patient Record (PPJ) stands out for its high-quality data, encompassing each patient's unique civil registration number, thereby facilitating nearly complete follow-up.[ 45 , 46 ] Another limitation is the unavailability of arterial gas measurements at hospital admission, precluding any comparison of hypercapnia and respiratory acidosis across different groups. In conclusion, patients who require inhaled bronchodilator treatment for respiratory distress while in the ambulance face notably high mortality rates at both 30 days and 1 year, with the exception of adults with asthma and those aged 18 and under. The need for prehospital inhaled bronchodilator treatment could serve as a clear and easily identifiable prehospital marker of severe respiratory distress, allowing for early interventions. Abbreviations AECOPD = acute exacerbation of chronic obstructive pulmonary disease CAP = community-acquired pneumonia HD = heart disease other ≥18 years = various other primary ICD-10 diagnoses EMS = emergency medical service ICU = intensive care unit EMDC = Emergency Medical Dispatch Center ePPR = Prehospital Patient Record IR = incidence rates IRR = incidence rate ratios Declarations Acknowledgement Not applicable. Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships. The authors have no conflict of interest. Funding This study has not received any funding. Data availability statement The datasets are available through the corresponding author upon reasonable request and permissions according to Danish legislation. Author contribution All authors have made significant contributions to this article by critically reviewing and commenting on the manuscript and by approving the final manuscript. VH and MFG undertook the drafting of the manuscript, while the study's design and conceptualization were accomplished collaboratively by all authors. Data collection was a collective effort involving MFG, VH, MGM, and ASRJ. The statistical analysis was executed by MFG, VH, and JV. MFG has been authorized by all co-authors to submit this research article and assumes primary responsibility for the paper. Ethics approval and consent to participate The study received approval from the Legal Department of the Central Denmark Region (file no. 1-45-70-53-22), and patient consent requirements were formally waived. Storage of the data was approved by the Danish Data Protection Agency (file no. 1-16-02-231-22). Human and animal rights statement and Informed consent The study adhered to the ethical standards outlined in the 1964 Declaration of Helsinki and its subsequent revisions. References Prekker ME, Feemster LC, Hough CL, Carlbom D, Crothers K, Au DH, Rea TD, Seymour CW. 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Treasure Island (FL): StatPearls Publishing; 2023 [cited 2023 Sep 30]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK559069/ Supples M, Jelden K, Pallansch J, Russell FM. Prehospital Diagnosis and Treatment of Patients With Acute Heart Failure. Cureus. 2022 Jun;14(6):e25866. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet Lond Engl. 2007 Oct 20;370(9596):1453–7. Gude MF, Blauenfeldt RA, Behrndtz AB, Nielsen CN, Speiser L, Simonsen CZ, Johnsen SP, Kirkegaard H, Andersen G. The Prehospital Stroke Score and telephone conference: A prospective validation. Acta Neurol Scand. 2022 May;145(5):541–50. Ambulances [Internet]. The Prehospital Emergency Medical Services, Central Denmark Region. [cited 2023 Aug 31]. Available from: https://www.ph.rm.dk/Omraader/ambulancer/ Liew CQ, Hsu SH, Ko CH, Chou EH, Herrala J, Lu TC, Wang CH, Huang CH, Tsai CL. Acute exacerbation of chronic obstructive pulmonary disease in United States emergency departments, 2010–2018. BMC Pulm Med. 2023 Jun 20;23:217. Thygesen SK, Christiansen CF, Christensen S, Lash TL, Sørensen HT. The predictive value of ICD-10 diagnostic coding used to assess Charlson comorbidity index conditions in the population-based Danish National Registry of Patients. BMC Med Res Methodol. 2011 May 28;11:83. Kelly AM, Holdgate A, Keijzers G, Klim S, Graham CA, Craig S, Kuan WS, Jones P, Lawoko C, Laribi S, AANZDEM study group. Epidemiology, prehospital care and outcomes of patients arriving by ambulance with dyspnoea: an observational study. Scand J Trauma Resusc Emerg Med. 2016 Sep 22;24(1):113. Hillas G, Perlikos F, Tzanakis N. Acute exacerbation of COPD: is it the ‘stroke of the lungs’? Int J Chron Obstruct Pulmon Dis. 2016;11:1579–86. Mantero M, Rogliani P, Di Pasquale M, Polverino E, Crisafulli E, Guerrero M, Gramegna A, Cazzola M, Blasi F. Acute exacerbations of COPD: risk factors for failure and relapse. Int J Chron Obstruct Pulmon Dis. 2017 Sep 8;12:2687–93. Sittichanbuncha Y, Savatmongkorngul S, Jawroongrit P, Sawanyawisuth K. Low oxygen saturation is associated with pre-hospital mortality among non-traumatic patients using emergency medical services: A national database of Thailand. Turk J Emerg Med. 2015 Sep;15(3):113–5. Vold ML, Aasebø U, Wilsgaard T, Melbye H. Low oxygen saturation and mortality in an adult cohort: the Tromsø study. BMC Pulm Med. 2015 Feb 12;15:9. Spörl P, Beckers SK, Rossaint R, Felzen M, Schröder H. Shedding light into the black box of out-of-hospital respiratory distress—A retrospective cohort analysis of discharge diagnoses, prehospital diagnostic accuracy, and predictors of mortality. Veldhuizen RA, editor. PLOS ONE. 2022 Aug 3;17(8):e0271982. Singer AJ, Emerman C, Char DM, Heywood JT, Kirk JD, Hollander JE, Summers R, Lee CC, Wynne J, Kellerman L, Peacock WF. Bronchodilator therapy in acute decompensated heart failure patients without a history of chronic obstructive pulmonary disease. Ann Emerg Med. 2008 Jan;51(1):25–34. Bøtker MT, Jacobsen L, Rudolph SS, Knudsen L. The role of point of care ultrasound in prehospital critical care: a systematic review. Scand J Trauma Resusc Emerg Med. 2018 Jun 26;26(1):51. Laursen CB, Sloth E, Lassen AT, Christensen R dePont, Lambrechtsen J, Madsen PH, Henriksen DP, Davidsen JR, Rasmussen F. Point-of-care ultrasonography in patients admitted with respiratory symptoms: a single-blind, randomised controlled trial. Lancet Respir Med. 2014 Aug;2(8):638–46. Zein JG, Erzurum SC. Asthma is Different in Women. Curr Allergy Asthma Rep. 2015 Jun;15(6):28. Fuseini H, Newcomb DC. Mechanisms Driving Gender Differences in Asthma. Curr Allergy Asthma Rep. 2017 Mar;17(3):19. Ringbaek TJ, Terkelsen J, Lange P. Outcomes of acute exacerbations in COPD in relation to pre-hospital oxygen therapy. Eur Clin Respir J. 2015;2. Sporer KA, Tabas JA, Tam RK, Sellers KL, Rosenson J, Barton CW, Pletcher MJ. Do medications affect vital signs in the prehospital treatment of acute decompensated heart failure? Prehosp Emerg Care. 2006;10(1):41–5. Hodroge SS, Glenn M, Breyre A, Lee B, Aldridge NR, Sporer KA, Koenig KL, Gausche-Hill M, Salvucci AA, Rudnick EM, Brown JF, Gilbert GH. Adult Patients with Respiratory Distress: Current Evidence-based Recommendations for Prehospital Care. West J Emerg Med. 2020 Jun 25;21(4):849–57. Pandor A, Thokala P, Goodacre S, Poku E, Stevens JW, Ren S, Cantrell A, Perkins GD, Ward M, Penn-Ashman J. Pre-hospital non-invasive ventilation for acute respiratory failure: a systematic review and cost-effectiveness evaluation. Health Technol Assess Winch Engl. 2015 Jun;19(42):v–vi, 1–102. Jensen ASR, Valentin JB, Mulvad MG, Hagenau V, Skaarup SH, Johnsen SP, Væggemose U, Gude MF. Standard vs. targeted oxygen therapy prehospitally for chronic obstructive pulmonary disease (STOP-COPD): study protocol for a randomised controlled trial. Trials. 2024 Jan 25;25(1):85. Emerman L, Shade B, Kubincanek J. A ControlledTrial of Nebulizedlsoetharinein the PrehospitaTlreatmentof AcuteAsthma. Lindskou TA, Mikkelsen S, Christensen EF, Hansen PA, Jørgensen G, Hendriksen OM, Kirkegaard H, Berlac PA, Søvsø MB. The Danish prehospital emergency healthcare system and research possibilities. Scand J Trauma Resusc Emerg Med. 2019 Nov 4;27(1):100. Kjær J, Milling L, Wittrock D, Nielsen LB, Mikkelsen S. The data quality and applicability of a Danish prehospital electronic health record: A mixed-methods study. PLOS ONE. 2023 Oct 26;18(10):e0293577. Supplementary Files SupplementalMaterialMartinFGude.docx Cite Share Download PDF Status: Published Journal Publication published 11 Nov, 2024 Read the published version in Internal and Emergency Medicine → Version 1 posted Reviewers agreed at journal 26 Apr, 2024 Reviewers invited by journal 25 Apr, 2024 Editor assigned by journal 28 Mar, 2024 First submitted to journal 27 Mar, 2024 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4177535","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":295587292,"identity":"45f109a9-2254-466e-9d9d-f64760c268b7","order_by":0,"name":"Victor Hagenau","email":"","orcid":"","institution":"Central Denmark Region: Region Midtjylland","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"","lastName":"Hagenau","suffix":""},{"id":295587293,"identity":"99e8096e-ea4e-4fec-aaaa-1028a2490c19","order_by":1,"name":"Mathilde Gundgaard Mulvad","email":"","orcid":"","institution":"Central Denmark Region: Region Midtjylland","correspondingAuthor":false,"prefix":"","firstName":"Mathilde","middleName":"Gundgaard","lastName":"Mulvad","suffix":""},{"id":295587294,"identity":"ab80e7f6-ab28-46e4-9b1d-fbf6c3bbe9d9","order_by":2,"name":"Jan Brink Valentin","email":"","orcid":"","institution":"Aalborg University: Aalborg Universitet","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"Brink","lastName":"Valentin","suffix":""},{"id":295587295,"identity":"08740617-ed93-4eb1-aed6-673fe24859cf","order_by":3,"name":"Arne Sylvester Rønde Jensen","email":"","orcid":"","institution":"Central Denmark Region: Region Midtjylland","correspondingAuthor":false,"prefix":"","firstName":"Arne","middleName":"Sylvester Rønde","lastName":"Jensen","suffix":""},{"id":295587296,"identity":"408fc208-515f-43c7-b44b-ed56f5203945","order_by":4,"name":"Martin Faurholdt Gude","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYHACA4YPbAyMfWA2WwJxWhhnALW0MTAwNhCthZmHJC3yEckbH9uU2cm2STcff8BQlkZYi+GNtGLjnHPJxm0yxxIbGM7lEKFlRo6ZdG4bc2KbRI5hA2NbBVFazH9bttUDteR/JE6LvESOGTNj22GQLYxALUQ4zIDnWbFkz7njxm0SaYYzEs4R4X359uSNH36UVcv2SyQ/+PChLJkIWw4g8xIIawDa0kCMqlEwCkbBKBjZAAA+hjlatse14QAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-2888-1842","institution":"Central Denmark Region: Region Midtjylland","correspondingAuthor":true,"prefix":"","firstName":"Martin","middleName":"Faurholdt","lastName":"Gude","suffix":""}],"badges":[],"createdAt":"2024-03-27 16:46:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4177535/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4177535/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11739-024-03795-1","type":"published","date":"2024-11-11T15:58:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":55761784,"identity":"e638d4d9-fdfc-4b64-9d3b-a923bf8842e7","added_by":"auto","created_at":"2024-05-02 19:03:54","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138610,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart\u003c/p\u003e\n\u003cp\u003eAECOPD = acute exacerbation of chronic obstructive pulmonary disease,\u003c/p\u003e\n\u003cp\u003eCAP = Community-acquired pneumonia, HD = heart disease, Other ≥18 years = other primary ICD-10 categories.\u003c/p\u003e","description":"","filename":"Figure1MartinFGude.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4177535/v1/7a82dd56756970c5cd50a3b5.jpeg"},{"id":69285377,"identity":"4d54a54e-a797-4be4-b5eb-a856a33a99ec","added_by":"auto","created_at":"2024-11-18 19:25:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":854530,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4177535/v1/87de196c-8ae9-44e6-901c-53fead26f827.pdf"},{"id":55761785,"identity":"5ba291ed-ca1d-438a-95f4-1f330283cedc","added_by":"auto","created_at":"2024-05-02 19:03:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27390,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterialMartinFGude.docx","url":"https://assets-eu.researchsquare.com/files/rs-4177535/v1/2ab6551f2d618c846b2f70e3.docx"}],"financialInterests":"","formattedTitle":"Final Diagnoses and Mortality Rates Among Patients Receiving Inhaled Bronchodilators During Ambulance Transportation","fulltext":[{"header":"Background","content":"\u003cp\u003eRespiratory distress frequently leads to prehospital contact, accounting for 6-12% of total hospital admissions facilitated by the emergency medical service (EMS).[1\u0026ndash;6] Of these patients, up to 40% receive a non-pulmonary diagnosis upon discharge [1,3], because a multitude of illnesses can result in respiratory distress. Community-acquired pneumonia (CAP), congestive heart failure (CHF), acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and acute asthma are the predominant prehospital conditions associated with this state.[3,7] Among hospitalized patients, CAP, CHF, and AECOPD collectively exhibit a similar 30-day mortality rate of approximately 10%. To specify, CHF presents a range of 7.8% to 15% [7\u0026ndash;9], AECOPD from 5% to 11.5% [7,10\u0026ndash;13], and for CAP, the range varies from 7% to 13% in hospitalized patients [14\u0026ndash;16] and increases to 15.6-27% in intensive care unit (ICU) cases.[17,18] In contrast, asthma patients transported by ambulance experience exceptionally low mortality.[7]\u003c/p\u003e\n\u003cp\u003eEarlier research has used diverse definitions to characterize respiratory distress in the prehospital setting. At the milder end of this spectrum, this condition has often been identified based on the EMS providers\u0026apos; impression that the initial EMS contact was for a respiratory-related reason.[1,19] Notably, in the studies conducted by Prekker et al. and Lindskou et al., only 50% and 63% of the identified patients, respectively, were subsequently admitted to a hospital. Alternatively, respiratory distress has been characterized based on the dispatch code assigned by the Emergency Medical Dispatch Center,[2,4,5] and it has also been defined only as dyspnea necessitating admission to an Emergency Department.[3,20] In the study conducted by Pozner et al., eligible patients for inclusion were those who required both hospitalization and treatment for respiratory distress, including medications, advanced airway management, or cardiac monitoring.[20] A method to identify a group of patients with respiratory distress in the prehospital setting might include treatment targeting respiratory difficulties directly such as inhaled bronchodilators. Prehospital treatment with inhaled bronchodilators stimulates \u0026beta;2-receptors in bronchial smooth muscles, promoting airway relaxation and improved airflow, alleviating respiratory distress due to bronchoconstriction.[21] Not all patients experiencing respiratory distress receive treatment with inhaled bronchodilators; the utilization rate for these medications in cases of respiratory distress varies between 20% and 55%.[3,7,22] However, in the Central Denmark Region, it is recommended to administer inhaled bronchodilators to all patients having symptoms of prolonged expiration and respiratory distress. Inhaled bronchodilator treatment may serve as an identifier for a homogeneous group of patients with moderate to severe respiratory distress in the prehospital setting - an unambiguously easy identifiable patient cohort not previously examined.\u003c/p\u003e\n\u003cp\u003eThis study aims to determine the final diagnoses and mortality rates (30-day and 1-year) among patients treated with inhaled bronchodilators in the prehospital setting and admitted to the hospital. \u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eStudy design and setting \u003c/h3\u003e\n\u003cp\u003eThis study was an observational cohort study including patients treated with inhaled bronchodilators in the prehospital setting in the Central Denmark Region in 2018-2019. \u003c/p\u003e\n\u003cp\u003eThis study adhered to the STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology).[23]\u003c/p\u003e\n\u003ch3\u003eThe regional Emergency Medical Service \u003c/h3\u003e\n\u003cp\u003eThe region is populated by 1.3 million inhabitants, constituting 23% of the entire Danish population. Within the region there are 8 hospitals differing in size and specialization, with five of them equipped with an emergency department. \u003c/p\u003e\n\u003cp\u003eThe Central Denmark Region has contracted three distinct ambulance services, with a combined workforce of about 650 EMS providers operating 70 ambulances.[24,25] Ambulances are deployed through the Emergency Medical Dispatch Center (EMDC) when responding to calls received via the national emergency number (112) or calls received directly from the patient\u0026rsquo;s primary care physician. Each ambulance is staffed by two EMS providers, consisting of either emergency medical technicians or paramedics. Furthermore, the EMDC can dispatch a medical emergency care unit staffed by a prehospital anesthesiologist and a paramedic. Patient transportation primarily prioritizes the nearest hospital, occasionally taking into account the specific medical condition.[25]\u003c/p\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003ePatients were included in the study if they received treatment with an inhaled \u0026beta;2 bronchodilator medication (specifically salbutamol) either at the prehospital scene or while being transported by ambulance between January 2018 and December 2019. COVID-19 did not influence EMS management in the study period. We excluded patients with unknown Civil Registration Numbers, and patients that were not admitted to a hospital in the Central Denmark Region. The latter applied to cases where treatment was completed at the scene or when patients were admitted to hospitals located outside the region.\u003c/p\u003e\n\u003ch3\u003eExposure\u003c/h3\u003e\n\u003cp\u003eIncluded patients were divided into six groups based on the main diagnosis established at the hospital. Using the ICD-10 classification system, we identified the following groups: patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), community-acquired pneumonia (CAP), any heart-related disease (HD), asthma, patients with another primary ICD-10 (other \u0026ge;18 years) and patients under the age of 18 (patients \u0026lt;18 years) (Supplemental Table S3)\u003c/p\u003e\n\u003cp\u003eFor patients to be classified as having AECOPD, it was necessary for their primary diagnosis to be COPD or for COPD to be listed as a secondary diagnosis alongside a primary diagnosis indicating a lung infection or displaying airway-related symptoms suggestive of a COPD exacerbation (Supplemental Table S3). COPD was defined as the ICD-10 codes J40-J44.[26] \u003c/p\u003e\n\u003cp\u003eSupplemental Table S3 contains comprehensive lists of primary ICD-10 diagnoses for the different patient groups.\u003c/p\u003e\n\u003ch3\u003eOutcome\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was all-cause 30 day mortality and secondary outcome was all-cause 1-year mortality.\u003c/p\u003e\n\u003ch3\u003eData Sources \u003c/h3\u003e\n\u003cp\u003eData from the electronic Prehospital Patient Record (ePPR) utilized by EMS providers were used to identify patients who received inhaled bronchodilator treatment (Salbutamol) during the prehospital phase of care. Vital sign data were also obtained from the ePPR. Prehospital transport data were retrieved from the dispatch system Logis used in the Emergency Medical Dispatch Center. Additionally, data on 30-day and 1-year mortality, length of stay, primary discharge diagnosis, and 10 years of historical diagnoses to determine comorbidity were extracted from the electronic patient record used in hospitals within the Central Denmark Region\u003c/p\u003e\n\u003ch3\u003eStatistics \u003c/h3\u003e\n\u003cp\u003eBasal characteristics, vital sign, comorbidities, readmission rate, length of hospital stay and in-hospital treatment were compared between exposure groups as frequencies and percentages or median and interquartile range (IQR) where appropriate. These numbers were presented for all observations as well as unique patients, where in the latter case we used the last observation in chronological order. Comorbidities were categorized according to the Charlson Comorbidity Index based on the ICD-10 diagnostic coding method as specified by Thygesen et al.[27]\u003c/p\u003e\n\u003cp\u003eOutcomes were presented as incidence rates (IR) and incidence rate ratios (IRR) with 95% confidence intervals (CI) using Poisson regression analysis with the AECOPD group as reference. We used cluster-robust variance to alleviate the assumption of independent observations for patients with multiple observations. In addition, patients with multiple observations were censored at the time of readmission if this occurred within the follow-up period. All analyses were stratified by sex, however, since the exposure group definitions were inherently associated with age and comorbidities, we did not adjust for these. Statistical analyses were performed using Stata 18.0 (StataCorp. 2023. \u003cem\u003eStata Statistical Software: Release 18\u003c/em\u003e. College Station, TX: StataCorp LLC.).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn 2018 and 2019, a total of 4,261 patients received prehospital inhaled bronchodilator treatment during 6,318 ambulance transports in the Central Denmark Region. The final study cohort was reached after the exclusion of 330 cases lacking primary outcome data, 15 due to hospital admissions outside the region, 62 from home treatment without hospitalization, and 253 having unaccountable missing data (Figure 1). Within the study cohort, there were 6,147 adults (18 years and older) and 171 patients under 18. Among adults, 3,686 cases were diagnosed with acute COPD exacerbation, 234 with CAP, 320 with heart disease, and 233 adults with asthma. Additionally, 1,674 cases fell under other primary ICD-10 categories (other \u0026ge;18 years). Moreover, 889 cases had established COPD without acute exacerbation, including 165 in the heart disease group, 718 in the \u0026ldquo;other \u0026ge;18 years\u0026rdquo; group, and 6 in the under-18 age category.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong the 6,318 ambulance transports analyzed, 2,057 cases involved readmissions within the study period, resulting in a readmission rate of 32.6% (95% CI 31.4-33.7). The readmission rate showed no significant difference between sexes (data not shown). During the two-year study period, the distribution of readmissions was as follows: 588 patients were readmitted once, 228 patients twice, 166 patients between three and five times, 34 patients more than five times, and 11 patients more than ten times.\u003c/p\u003e\n\u003cp\u003eIn all patient groups, except for the under-18 years category, there was a slight to moderate predominance of female participants, ranging from 52.3% to 69.5%. In the under-18 years category, the proportion of females was only 42.7% (Table 1). In terms of age, the AECOPD, CAP, HD, and \u0026ldquo;other ICD-10 \u0026ge;18 years\u0026rdquo; groups displayed a comparable median age, ranging from 73 to 78 years. Participants in the asthma group had a notably lower median age of 45 years, while for patients under 18 years of age, the median age was 4.\u003c/p\u003e\n\u003cp\u003eThe prevalence and distribution of comorbidities showed significant similarities between the AECOPD and the \u0026ldquo;other ICD-10 \u0026ge;18 years\u0026rdquo; group, possibly influenced by a relatively large proportion of known COPD patients in the latter. Similarly, comorbidity patterns between the asthma and under-18 groups were comparably infrequent, with a consistently higher prevalence of comorbidities in the asthma group, likely due to its higher median age. The HD group displayed a distinct comorbidity profile with a notably high prevalence of prior myocardial infarction and congestive heart disease, along with the highest rates of hypertension, diabetes mellitus, renal disease, and atherosclerosis-related comorbidities such as peripheral vascular disease, cerebrovascular disease, and dementia (Table 2). These findings were further correlated with the Charlson Comorbidity Score, revealing that the asthma and under-18 groups exhibited the lowest scores, while the remaining groups demonstrated relatively similar scores, with the highest scores observed in the HD group (Table 2).\u003c/p\u003e\n\u003cp\u003eIn assessing vital signs, comparable values were observed across the groups in terms of respiratory rate, heart rate, systolic, and diastolic blood pressures, except for individuals under the age of 18. This subgroup displayed lower blood pressure and a higher pulse rate, aligning with expected physiological variances in this age category. Notably, oxygen saturation levels exhibited variations among the groups. The asthma group and individuals under 18 demonstrated the highest oxygen saturation levels, whereas the AECOPD, CAP, and HD categories manifested the lowest levels within the study cohort (Table 1).\u003c/p\u003e\n\u003cp\u003eExclusively considering unique patient IDs did not alter baseline characteristics, comorbidity, and physiological parameters (supplemental Table S1 and S2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe length of hospital stay varied little among all groups (0.6-1.5 days). The HD group had the highest proportion of cases admitted to the ICU (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Basal characteristics, hospital admission and physiological parameters \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eCAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eHeart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e3,686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1,674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSex (female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1,944 (52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e144 (61.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e171 (53.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e162 (69.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e875 (52.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e73 (42.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eAge, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e74 (66-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e74 (60-82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e78 (72-84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e45 (26-62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e73 (61-81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1-11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eLength of hospital stay, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.0 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.5 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e0.7 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eICU admission, n (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e40 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e13 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e13 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003ePhysiological (vital) parameters (initial assessment in the ambulance)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory rate,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003emedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e30 (24-33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e28 (24-32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e30 (24-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e28 (22-30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e28 (24-32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e32 (25-42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSystolic blood pressure, \u0026nbsp;median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e152 (135-174)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e150 (133-170)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e155 (131-178.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e148.5 (131-162.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e150 (131-172)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e123 (112-134)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eDiastolic blood pressure, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e86 (74-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e85 (74-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e91.5 (75-109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e88.5 (76-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e87 (74-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e77 (65-84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eHeart rate, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e104 (89-117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e105 (88-119)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e103 (82-121)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e104 (91-118.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e100 (84-116)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e125 (102-143)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eGCS, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e15 (15-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e15 (15-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e15 (15-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e15 (15-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e15 (15-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e15 (15-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSpO2 \u0026lt;88, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1,337 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e83 (35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e131 (41.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e27 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e501 (30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e15 ( 9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSpO2 88-92%, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e808 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e54 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e58 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e32 (14.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e343 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e25 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSpO2 93-96%, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e894 (24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e57 (24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e79 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e75 (33.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e396 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e38 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSpO2 97-100%, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e602 (16.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e38 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e48 (15.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e93 (41.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e411 (24.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e84 (51.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 1: Basal characteristics, hospital admission and physiological parameters AECOPD = acute exacerbation of chronic obstructive pulmonary disease, CAP = Community-acquired pneumonia, HD = heart disease, Other \u0026ge;18 years = other primary ICD-10 categories, ICU = intensive care unit, GCS = Glasgow Coma Scale; SpO2 = Peripheral Capillary Oxygen Saturation measured by pulse oximeter.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 10-year comorbidity\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"597\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003eCAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3,686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1,674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eMyocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e290 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e14 ( 6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e56 (17.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e117 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 ( 0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eCongestive heart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e596 (16.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e19 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e131 (40.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e268 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003ePeripheral vascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e432 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e16 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e49 (15.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e6 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e175 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eCerebrovascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e469 (12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e31 (13.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e47 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e5 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e232 (13.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eHemiplegia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e17 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e8 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e83 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e8 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e15 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e49 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eChronic pulmonary disease *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3,458 (93.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e34 (14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e176 (55.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e146 (62.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e864 (51.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e85 (49.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes mellitus (without complications)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e215 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e12 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e25 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e100 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes mellitus (with chronic complications)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e158 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e17 (7.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e28 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e101 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eMild liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e63 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e40 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eModerate/severe liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e14 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e14 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eConnective tissue disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e148 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e13 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e18 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e12 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e77 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eUlcer disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e142 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e11 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e14 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e68 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eModerate/severe renal disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e338 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e17 (7.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e53 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e10 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e171 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eAny tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e496 (13.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e37 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e49 (15.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e5 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e242 (14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eLeukemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e11 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e7 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eLymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e44 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e17 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eMetastatic solid tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e52 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e8 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e7 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e41 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eAIDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003eCharlson Comorbidities Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e18 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e46 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e126 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e84 (49.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e93 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e22 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e6 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e89 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e114 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e84 (49.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e214 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e22 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e12 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e24 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e147 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e543 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e30 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e30 ( 9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e24 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e201 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e796 (21.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e53 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e54 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e29 (12.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e288 (17.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e714 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e34 (14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e60 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e14 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e286 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e618 (16.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e18 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e42 (13.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e5 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e195 (11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e343 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e10 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e47 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e120 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e170 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e11 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e29 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e89 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e88 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e10 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e20 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e51 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e48 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e7 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e28 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e30 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e10 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e17 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e18 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e3 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e7 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e8 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e4 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003eScore 16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.468013468013469%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2: 10-year Charlson comorbidities based on ICD-10 codes. *AECOPD patients excluded from this category received their first diagnosis of COPD during the current admission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAECOPD = acute exacerbation of chronic obstructive pulmonary disease, CAP = Community-acquired pneumonia, HD = heart disease, Other \u0026ge;18 years = other primary ICD-10 categories. AIDS = Acquired Immunodeficiency Syndrome.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWithin 30 days of hospital admission, 593 patients in the study population died, resulting in a total mortality rate (IR) of 10.7% (95% CI 9.8-11.6). The 30-day mortality rate in the AECOPD group was 10.2% (95% CI 9.1-11.3), lower than the rates in the CAP, HD, and \u0026quot;other \u0026ge;18 years\u0026quot; groups, which had 30-day mortality rates of 12.1% (95% CI 7.4-16.8), 15.3% (95% CI 10.6-19.9), and 13.5% (95% CI 11.5-15.4), respectively (Table 3). Notably, in both the asthma and \u0026ldquo;patients under 18 years\u0026rdquo; groups, no deaths occurred within 30 days after admission (Table 3).\u003c/p\u003e\n\u003cp\u003eWhen conducting a relative comparison of 30-day mortality using AECOPD as the reference, the CAP group exhibited an insignificant 18.7% increase in the mortality rate (IRR 1.187 (95% CI 0.792-1.781)), while the HD and \u0026quot;Other \u0026ge;18 years\u0026quot; groups demonstrated significant increased rates of 49.5% (IRR 1.495, 95% CI 1.079-2.072) and 32.0% (IRR 1.320, 95% CI 1.103-1.579), respectively (Table 3).\u003c/p\u003e\n\u003cp\u003eWithin 1 year of hospital admission, 1255 patients died, resulting in a total 1-year mortality rate (IR) of 32.1% (95% CI 30.2-34.0). Interestingly, when considering the 1-year mortality rates, the differences between groups diminished to insignificant increased mortality rates ranging from 1.2% to 15.2% (IRR 1.012 (95% CI 0.763-1.343) - IRR 1.152 (95% CI 0.905-1.466)) in the CAP, HD, and \u0026quot;Other \u0026ge;18 years\u0026quot; groups. The 1-year mortality rates remained very low in both the asthma and \u0026ldquo;patients under 18 years\u0026rdquo; groups at 2.5% (95% CI 0.3-4.8) and 0.6% (95% CI 0.0-1.9).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe 30-day mortality rates observed among males and females showed differences within the CAP, \u0026apos;Other \u0026ge;18 years\u0026apos;, and HD groups. In the CAP group, the 30-day mortality rate (IR) for females was 8.9% (95% CI 3.8-14.0), compared with 17.5% (95% CI 8.1-26.9) for males; in the \u0026apos;Other \u0026ge;18 years\u0026apos; group, the rate was 12.3% (95% CI 9.8-14.8) for females versus 14.7% (95% CI 11.9-17.6) for males. Conversely, in the HD group, females exhibited a higher 30-day mortality rate of 16.8% (95% CI 10.0-23.5) compared to 13.6% (95% CI 7.1-20.0) for males (Table 4).\u003c/p\u003e\n\u003cp\u003eThese sex-based disparities also extended to the 1-year mortality rate. In the CAP group, females had a lower mortality rate of 29.8% (95% CI 19.0-40.6) compared to 42.0% (95% CI 24.8-59.3) for males. Similarly, in the \u0026apos;Other \u0026ge;18 years\u0026apos; group, the mortality rate for females was 33.3% (95% CI 28.2-38.3) versus 40.7% (95% CI 34.8-46.6) for males. Meanwhile, in the HD group, females still exhibited the highest 1-year mortality rate at 42.3% (95% CI 29.6-55.0), compared to 35.4% (95% CI 23.0-47.7) for males.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Absolute and relative 30-day and 1-year mortality\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAbsolute 30-day mortality\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eIR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.102 (0.091-0.113)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCommunity-acquired pneumonia (CAP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.121 (0.074-0.168)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease (HD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.153 (0.106-0.199)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.135 (0.115-0.154)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.107 (0.098-0.116)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRelative 30-day mortality with the AECOPD group as reference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eIRR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCommunity-acquired pneumonia (CAP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.187 (0.792-1.781)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease (HD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.495 (1.079-2.072)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.320 (1.103-1.579)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAbsolute 1-year mortality\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eIR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.339 (0.312-0.366)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCommunity-acquired pneumonia (CAP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.343 (0.250-0.436)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.390 (0.302-0.479)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.025 (0.003-0.048)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.368 (0.329-0.406)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.006 (0.000-0.019)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.321 (0.302-0.340)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRelative 1-year mortality with the AECOPD group as reference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eIRR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCommunity-acquired pneumonia (CAP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.012 (0.763,1.343)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.152 (0.905,1.466)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.075 (0.031,0.180)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.085 (0.951,1.238)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0.019 (0.003,0.133)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3: Absolute and relative 30-day and 1-year mortality presented as incidence rates (IR) and incidence rate ratios (IRR) with 95% confidence intervals (CI). AECOPD = acute exacerbation of chronic obstructive pulmonary disease, Other \u0026ge;18 years = other primary ICD-10 categories.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 Absolute and relative 30-day and 1-year mortality stratified by sex\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ePatients (unique ID)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e2293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1968\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAmbulance transports, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e3369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e2949\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAge all groups, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e73 (63; 80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e73 (63; 80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eAbsolute 30-day mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIR (95% CI)\u003c/p\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIR (95% CI)\u003c/p\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.104 (0.088-0.120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.099 (0.083-0.116)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eCAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.089 (0.038-0.140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.175 (0.081-0.269)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.168 (0.100-0.235)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.136 (0.071-0.200)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.123 (0.098-0.148)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.147 (0.119-0.176)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.104 (0.092-0.116)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.110 (0.097-0.124)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eRelative 30-day mortality with AECOPD as reference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIRR (95% CI) Females\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIRR (95% CI) Males\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eCAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.853 (0.473,1.539)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.763 (1.005-3.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.608 (1.046,2.471)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.363 (0.825-2.253)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.179 (0.914,1.521)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.483 (1.150-1.913)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eAbsolute 1-year mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIR (95% CI)\u003c/p\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIR (95% CI)\u003c/p\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.334 (0.297,0.370)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.345 (0.305-0.385)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eCAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.298 (0.190,0.406)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.420 (0.248-0.593)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.423 (0.296,0.550)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.354 (0.230-0.477)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.037 (0.005,0.070)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.333 (0.282,0.383)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.407 (0.348-0.466)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000,0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.011 (0.000-0.031)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.308 (0.283,0.333)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.336 (0.308-0.365)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eRelative 1-year mortality with AECOPD as reference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIRR (95% CI) Females\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eIRR (95% CI) Males\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAECOPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eCAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.894 (0.612-1.305)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.218 (0.796-1.866)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eHeart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.267 (0.921-1.743)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.025 (0.709-1.482)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAstma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.112 (0.046-0.270)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eOther \u0026ge;18 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.998 (0.828-1.202)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e1.179 (0.979-1.421)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ePatients \u0026lt; 18y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.031 (0.004-0.217)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4: Absolute \u0026nbsp;and relative 30-day and 1-year mortality with the AECOPD group as reference presented as incidence rates (IR) and incidence rate ratios (IRR) with 95% confidence intervals (CI). AECOPD = acute exacerbation of chronic obstructive pulmonary disease, CAP = Community-acquired pneumonia, HD = heart disease, Other \u0026ge;18 years = other primary ICD-10 categories.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study characterizes patients receiving inhaled bronchodilator treatment during the prehospital phase of care. Individuals requiring prehospital inhaled bronchodilators constitute a complex and critically ill cohort with a diverse range of comorbidities and high mortality rates. The 30-day all-cause mortality observed in this study totaled 10.7% - comparable to findings in other studies on prehospital respiratory distress.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] A 1-year mortality rate of 32.1% was identified in the total study cohort, a figure also confirmed by B\u0026oslash;tker et al.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] The 1-year mortality rate showed relatively limited variations between groups (33.9\u0026ndash;39.0%), except for adults with asthma and the group of patients under 18 years where very low mortality rates were observed. Except for these two patient groups, this study's findings underscore that respiratory distress necessitating inhaled bronchodilator treatment in the ambulance represents an exceptionally life-threatening condition.\u003c/p\u003e \u003cp\u003eAlthough AECOPD is typically associated with high 30-day mortality rates [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], it unexpectedly had the lowest mortality rate among the studied groups once asthma and patients younger than 18 were excluded. The HD group experienced a significantly higher mortality rate, with a 49.5% increase in 30-day mortality compared to the AECOPD group. This disparity may stem from the study's inclusion criteria, which likely selected more severe HD cases needing bronchodilator treatment for conditions such as pulmonary edema. Additionally, the HD group had a higher incidence of comorbidities than the other groups (AECOPD, CAP, and \"Other\u0026thinsp;\u0026ge;\u0026thinsp;18 years\"), as well as the lowest initial oxygen saturations in the ambulance, a factor independently linked to a high mortality rate. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] Furthermore, HD patients experienced longer hospital stays and were more frequently admitted to the ICU, indicating a greater severity of their condition. However, when focusing on 1-year mortality rates, the differences between groups became less pronounced. Nevertheless, all groups, except for those with asthma and those younger than 18, exhibited extremely high mortality rates, with the HD group at 39.0%. Research has shown that distinguishing between cardiac-triggered dyspnea and lung-triggered dyspnea in the prehospital setting is difficult [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], which might delay targeted treatments, such as diuretics. Moreover, the efficacy of inhaled bronchodilator treatment in patients with heart disease, who do not have COPD, remains uncertain and has been subject to debate.[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] Point-of-care ultrasound could help paramedics to perform more accurate diagnostics in the prehospital phase.[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTwo distinct groups were included in this study: adults with asthma and individuals aged 18 years and younger. These groups stand out from the rest of the cohort, even though they present with respiratory distress requiring inhaled bronchodilator treatment. Both the asthma group and those 18 years and younger have significantly fewer comorbidities and the lowest mortality rates. Notably, the asthma group comprises a significant majority of female participants, at 69.5%. This may indicate a higher prevalence and severity of asthma in women, a phenomenon previously documented in literature.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e \u003cp\u003ePatients in this study were exclusively identified by a clear prehospital marker: the need for inhaled bronchodilator treatments in ambulances, indicating respiratory distress. This approach contrasts with previous studies that utilized various methods to identify prehospital respiratory distress, such as retrospective analysis post-hospital admission [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], dispatch reference work codes from Emergency Medical Dispatch Centers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], or subjective impressions of respiratory distress by EMS providers.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] The diversity in identification methods highlights the diagnostic challenges of prehospital respiratory distress.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] A reliable and straightforward prehospital identifier is essential not only for facilitating timely interventions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] but also for ensuring accurate identification of patients for research purposes.[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] The need for inhaled bronchodilator treatment serves as an effective prehospital marker for significant respiratory distress. Furthermore, our study categorized patients into the same four primary groups identified in previous studies - heart failure, COPD, community-acquired pneumonia, and mixed diagnoses. This categorization might account for the relatively similar mortality rates observed across studies among patients admitted to hospital.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] When compared to previously applied definitions of respiratory distress [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], the need for inhaled bronchodilator treatment almost exclusively identifies patients bound for hospital admission. This group of patients is most likely to benefit from early interventions.\u003c/p\u003e \u003cp\u003eThe combination of inhaled bronchodilator treatment and point-of-care ultrasound examinations could assist paramedics in assessing the severity and potentially the cause of respiratory distress, enabling rapid and tailored prehospital treatment.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] However, further research is necessary to evaluate the effectiveness of multimodal approaches in identifying respiratory distress in the prehospital setting.\u003c/p\u003e \u003cp\u003eOne limitation of this study on respiratory distress is the exclusive inclusion of patients who required prehospital bronchodilator treatment, potentially introducing selection bias if the goal was to encompass all individuals experiencing respiratory distress. Nonetheless, this criterion also constitutes a strength, as it ensured the easy identification of all participants, specifically including those with moderate to severe distress\u0026mdash;individuals for whom early intervention might be particularly beneficial. Additionally, the Danish Prehospital Patient Record (PPJ) stands out for its high-quality data, encompassing each patient's unique civil registration number, thereby facilitating nearly complete follow-up.[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] Another limitation is the unavailability of arterial gas measurements at hospital admission, precluding any comparison of hypercapnia and respiratory acidosis across different groups.\u003c/p\u003e \u003cp\u003eIn conclusion, patients who require inhaled bronchodilator treatment for respiratory distress while in the ambulance face notably high mortality rates at both 30 days and 1 year, with the exception of adults with asthma and those aged 18 and under. The need for prehospital inhaled bronchodilator treatment could serve as a clear and easily identifiable prehospital marker of severe respiratory distress, allowing for early interventions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAECOPD = acute exacerbation of chronic obstructive pulmonary disease\u003c/p\u003e\n\u003cp\u003eCAP = community-acquired pneumonia\u003c/p\u003e\n\u003cp\u003eHD = heart disease\u003c/p\u003e\n\u003cp\u003eother \u0026ge;18 years = various other primary ICD-10 diagnoses\u003c/p\u003e\n\u003cp\u003eEMS = emergency medical service\u003c/p\u003e\n\u003cp\u003eICU = intensive care unit\u003c/p\u003e\n\u003cp\u003eEMDC = Emergency Medical Dispatch Center\u003c/p\u003e\n\u003cp\u003eePPR = Prehospital Patient Record\u003c/p\u003e\n\u003cp\u003eIR = incidence rates\u003c/p\u003e\n\u003cp\u003eIRR = incidence rate ratios\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAcknowledgement\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003eConflict of Interest\u003c/h3\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships. The authors have no conflict of interest.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis study has not received any funding.\u003c/p\u003e\n\u003ch3\u003eData availability statement\u003c/h3\u003e\n\u003cp\u003eThe datasets are available through the corresponding author upon reasonable request and permissions according to Danish legislation.\u003c/p\u003e\n\u003ch3\u003eAuthor contribution\u003c/h3\u003e\n\u003cp\u003eAll authors have made significant contributions to this article by critically reviewing and commenting on the manuscript and by approving the final manuscript. VH and MFG undertook the drafting of the manuscript, while the study\u0026apos;s design and conceptualization were accomplished collaboratively by all authors. Data collection was a collective effort involving MFG, VH, MGM, and ASRJ. The statistical analysis was executed by MFG, VH, \u0026nbsp;and JV. MFG has been authorized by all co-authors to submit this research article and assumes primary responsibility for the paper.\u003c/p\u003e\n\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eThe study received approval from the Legal Department of the Central Denmark Region (file no. 1-45-70-53-22), and patient consent requirements were formally waived. Storage of the data was approved by the Danish Data Protection Agency (file no. 1-16-02-231-22).\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eHuman and animal rights statement and Informed consent\u003c/h3\u003e\n\u003cp\u003eThe study adhered to the ethical standards outlined in the 1964 Declaration of Helsinki and its subsequent revisions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePrekker ME, Feemster LC, Hough CL, Carlbom D, Crothers K, Au DH, Rea TD, Seymour CW. The epidemiology and outcome of prehospital respiratory distress. 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Curr Allergy Asthma Rep. 2017 Mar;17(3):19.\u003c/li\u003e\n\u003cli\u003eRingbaek TJ, Terkelsen J, Lange P. Outcomes of acute exacerbations in COPD in relation to pre-hospital oxygen therapy. Eur Clin Respir J. 2015;2.\u003c/li\u003e\n\u003cli\u003eSporer KA, Tabas JA, Tam RK, Sellers KL, Rosenson J, Barton CW, Pletcher MJ. Do medications affect vital signs in the prehospital treatment of acute decompensated heart failure? Prehosp Emerg Care. 2006;10(1):41\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eHodroge SS, Glenn M, Breyre A, Lee B, Aldridge NR, Sporer KA, Koenig KL, Gausche-Hill M, Salvucci AA, Rudnick EM, Brown JF, Gilbert GH. Adult Patients with Respiratory Distress: Current Evidence-based Recommendations for Prehospital Care. West J Emerg Med. 2020 Jun 25;21(4):849\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003ePandor A, Thokala P, Goodacre S, Poku E, Stevens JW, Ren S, Cantrell A, Perkins GD, Ward M, Penn-Ashman J. Pre-hospital non-invasive ventilation for acute respiratory failure: a systematic review and cost-effectiveness evaluation. Health Technol Assess Winch Engl. 2015 Jun;19(42):v\u0026ndash;vi, 1\u0026ndash;102.\u003c/li\u003e\n\u003cli\u003eJensen ASR, Valentin JB, Mulvad MG, Hagenau V, Skaarup SH, Johnsen SP, V\u0026aelig;ggemose U, Gude MF. Standard vs. targeted oxygen therapy prehospitally for chronic obstructive pulmonary disease (STOP-COPD): study protocol for a randomised controlled trial. Trials. 2024 Jan 25;25(1):85.\u003c/li\u003e\n\u003cli\u003eEmerman L, Shade B, Kubincanek J. A ControlledTrial of Nebulizedlsoetharinein the PrehospitaTlreatmentof AcuteAsthma.\u003c/li\u003e\n\u003cli\u003eLindskou TA, Mikkelsen S, Christensen EF, Hansen PA, J\u0026oslash;rgensen G, Hendriksen OM, Kirkegaard H, Berlac PA, S\u0026oslash;vs\u0026oslash; MB. The Danish prehospital emergency healthcare system and research possibilities. Scand J Trauma Resusc Emerg Med. 2019 Nov 4;27(1):100.\u003c/li\u003e\n\u003cli\u003eKj\u0026aelig;r J, Milling L, Wittrock D, Nielsen LB, Mikkelsen S. The data quality and applicability of a Danish prehospital electronic health record: A mixed-methods study. PLOS ONE. 2023 Oct 26;18(10):e0293577.\u003c/li\u003e\n\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"internal-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iaem","sideBox":"Learn more about [Internal and Emergency Medicine](http://link.springer.com/journal/11739)","snPcode":"11739","submissionUrl":"https://www.editorialmanager.com/iaem/default.aspx","title":"Internal and Emergency Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Emergency Medical Services, Lung Diseases, Bronchodilator Agents, Respiratory Insufficiency","lastPublishedDoi":"10.21203/rs.3.rs-4177535/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4177535/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: To assess final diagnoses and mortality rates (30-day and 1-year) in patients requiring inhaled bronchodilators administered by ambulance personnel.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: In a retrospective observational cohort study, patients experiencing respiratory distress and treated with inhaled bronchodilators in the prehospital setting within the Central Denmark Region during 2018-2019 were included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The study included 6,318 ambulance transports, comprising 3,686 cases of acute exacerbation of chronic obstructive pulmonary disease (AECOPD), 234 with community-acquired pneumonia (CAP), 320 with heart disease (HD), 233 adults with asthma, 1,674 with various other primary ICD-10 diagnoses (other ≥18 years), and 171 patients under 18 years. The 30-day mortality rate for all patients was 10.7% (95% CI 9.8-11.6), with zero deaths within 30 days among adults with asthma and those under 18. Excluding low mortality groups, AECOPD patients had the lowest 30-day mortality at 10.2% (95% CI 9.1-11.3), and HD patients the highest at 15.3% (95% CI 10.6-19.9). The 1-year overall mortality rate increased to 32.1% (95% CI 30.2-34.0), with mortality staying low for asthma and under-18 groups, while differences between other groups lessened and became insignificant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Patients requiring inhaled bronchodilator treatment in ambulances exhibit notably high mortality rates at 30 days and 1 year, except for those with asthma or under 18. The need for prehospital bronchodilators could serve as a clear and unmistakable marker for moderate to severe respiratory distress, enabling early intervention.\u003c/p\u003e","manuscriptTitle":"Final Diagnoses and Mortality Rates Among Patients Receiving Inhaled Bronchodilators During Ambulance Transportation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 19:03:46","doi":"10.21203/rs.3.rs-4177535/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-04-26T05:56:12+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-25T22:15:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-28T15:24:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Internal and Emergency Medicine","date":"2024-03-27T12:45:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"internal-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iaem","sideBox":"Learn more about [Internal and Emergency Medicine](http://link.springer.com/journal/11739)","snPcode":"11739","submissionUrl":"https://www.editorialmanager.com/iaem/default.aspx","title":"Internal and Emergency Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0f4efe56-ed8f-4739-b1c0-234ff571077e","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-18T19:19:04+00:00","versionOfRecord":{"articleIdentity":"rs-4177535","link":"https://doi.org/10.1007/s11739-024-03795-1","journal":{"identity":"internal-and-emergency-medicine","isVorOnly":false,"title":"Internal and Emergency Medicine"},"publishedOn":"2024-11-11 15:58:24","publishedOnDateReadable":"November 11th, 2024"},"versionCreatedAt":"2024-05-02 19:03:46","video":"","vorDoi":"10.1007/s11739-024-03795-1","vorDoiUrl":"https://doi.org/10.1007/s11739-024-03795-1","workflowStages":[]},"version":"v1","identity":"rs-4177535","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4177535","identity":"rs-4177535","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}