Background and Objectives: Although cardiac rehabilitation (CR) is highly recommended in patients with cardiovascular disease (CVD), participation in CR is low mainly due to access barriers. Home-based CR (HBCR) has been recommended to overcome access barriers.Exercise is a core component of CR and should be developed and implemented based on individual characteristics. We aimed to assess physical activity behaviors, exercise preferences, and exercise barriers to understand physical activity characteristics of CVD patients. Methods: Participants were patients between the ages 19 to 75 years with a history of heart failure with reduced ejection fraction (HFrEF) or myocardial infarction (MI). They completed a cross-sectional survey at a tertiary hospital's outpatient clinic from April to June 2021. Survey data included physical activity levels, patterns, preference, and barriers of exercise. Results: Participants (n=189; 143 males, 46 females, 62.1±12.0 years) were diagnosed as either HFrEF (n=160, 84.7%) or a history of MI (n=97, 51.3%). Only 26.5% of patients engaged in moderate to vigorous exercise for more than 150 minutes per week. Participants preferred exercising alone or with families. Walking (65.6%) and resistance exercises (35.4%) were favored, with outdoor (37%) and home-based (30.2%) settings preferred over fitness centers (10.6%) and hospitals (0.5%). Barriers to exercise included fatigue (34.4%), poor health perception (31.7%), and low fitness levels (30.7%). Conclusions The results of this study can be used to develop tailored HBCR programs that consider individual preferences and address specific barriers, facilitating adequate physical activity engagement.

Background and Objectives: Although cardiac rehabilitation (CR) is highly recommended in patients with cardiovascular disease (CVD), participation in CR is low mainly due to access barriers. Home-based CR (HBCR) has been recommended to overcome access barriers.Exercise is a core component of CR and should be developed and implemented based on individual characteristics. We aimed to assess physical activity behaviors, exercise preferences, and exercise barriers to understand physical activity characteristics of CVD patients. Methods: Participants were patients between the ages 19 to 75 years with a history of heart failure with reduced ejection fraction (HFrEF) or myocardial infarction (MI). They completed a cross-sectional survey at a tertiary hospital's outpatient clinic from April to June 2021. Survey data included physical activity levels, patterns, preference, and barriers of exercise. Results: Participants (n=189; 143 males, 46 females, 62.1±12.0 years) were diagnosed as either HFrEF (n=160, 84.7%) or a history of MI (n=97, 51.3%). Only 26.5% of patients engaged in moderate to vigorous exercise for more than 150 minutes per week. Participants preferred exercising alone or with families. Walking (65.6%) and resistance exercises (35.4%) were favored, with outdoor (37%) and home-based (30.2%) settings preferred over fitness centers (10.6%) and hospitals (0.5%). Barriers to exercise included fatigue (34.4%), poor health perception (31.7%), and low fitness levels (30.7%). Conclusions The results of this study can be used to develop tailored HBCR programs that consider individual preferences and address specific barriers, facilitating adequate physical activity engagement.

Background and Objectives: Although cardiac rehabilitation (CR) is highly recommended in patients with cardiovascular disease (CVD), participation in CR is low mainly due to access barriers. Home-based CR (HBCR) has been recommended to overcome access barriers.Exercise is a core component of CR and should be developed and implemented based on individual characteristics. We aimed to assess physical activity behaviors, exercise preferences, and exercise barriers to understand physical activity characteristics of CVD patients. Methods: Participants were patients between the ages 19 to 75 years with a history of heart failure with reduced ejection fraction (HFrEF) or myocardial infarction (MI). They completed a cross-sectional survey at a tertiary hospital's outpatient clinic from April to June 2021. Survey data included physical activity levels, patterns, preference, and barriers of exercise. Results: Participants (n=189; 143 males, 46 females, 62.1±12.0 years) were diagnosed as either HFrEF (n=160, 84.7%) or a history of MI (n=97, 51.3%). Only 26.5% of patients engaged in moderate to vigorous exercise for more than 150 minutes per week. Participants preferred exercising alone or with families. Walking (65.6%) and resistance exercises (35.4%) were favored, with outdoor (37%) and home-based (30.2%) settings preferred over fitness centers (10.6%) and hospitals (0.5%). Barriers to exercise included fatigue (34.4%), poor health perception (31.7%), and low fitness levels (30.7%). Conclusions The results of this study can be used to develop tailored HBCR programs that consider individual preferences and address specific barriers, facilitating adequate physical activity engagement.

Background and Objectives: Although cardiac rehabilitation (CR) is highly recommended in patients with cardiovascular disease (CVD), participation in CR is low mainly due to access barriers. Home-based CR (HBCR) has been recommended to overcome access barriers.Exercise is a core component of CR and should be developed and implemented based on individual characteristics. We aimed to assess physical activity behaviors, exercise preferences, and exercise barriers to understand physical activity characteristics of CVD patients. Methods: Participants were patients between the ages 19 to 75 years with a history of heart failure with reduced ejection fraction (HFrEF) or myocardial infarction (MI). They completed a cross-sectional survey at a tertiary hospital's outpatient clinic from April to June 2021. Survey data included physical activity levels, patterns, preference, and barriers of exercise. Results: Participants (n=189; 143 males, 46 females, 62.1±12.0 years) were diagnosed as either HFrEF (n=160, 84.7%) or a history of MI (n=97, 51.3%). Only 26.5% of patients engaged in moderate to vigorous exercise for more than 150 minutes per week. Participants preferred exercising alone or with families. Walking (65.6%) and resistance exercises (35.4%) were favored, with outdoor (37%) and home-based (30.2%) settings preferred over fitness centers (10.6%) and hospitals (0.5%). Barriers to exercise included fatigue (34.4%), poor health perception (31.7%), and low fitness levels (30.7%). Conclusions The results of this study can be used to develop tailored HBCR programs that consider individual preferences and address specific barriers, facilitating adequate physical activity engagement.

Purpose: Smoking cessation intervention is one of the key components of successful lung cancer screening program. We investigated the effectiveness and related factors of smoking cessation services provided to the participants in a population-based lung cancer screening trial. Materials and Methods: The Korean Lung Cancer Screening Project (K-LUCAS) is a nationwide, multi-center lung cancer screening trial that evaluates the feasibility of implementing population-based lung cancer screening. All 5,144 current smokers who participated in the K-LUCAS received a mandatory smoking cessation counseling. Changes in smoking status were followed up using a telephone survey in 6 months after lung cancer screening participation. The lung cancer screening’s impact on smoking cessation is analyzed by variations in the smoking cessation interventions provided in screening units. Results: Among 4,136 survey responders, participant’s motivation to quit smoking increased by 9.4% on average after lung cancer screening. After 6 months from the initial screening, 24.3% of participants stopped smoking, and 10.6% of participants had not smoked continuously for at least 6 months after screening. Over 80% of quitters stated that participation in lung cancer screening motivated them to quit smoking. Low-cost public smoking cessation program combined with lung cancer screening increased the abstinence rates. The smokers were three times more likely to quit smoking when the smoking cessation counseling was provided simultaneously with low-dose computed tomography screening results than when provided separately. Conclusion A mandatory smoking cessation intervention integrated with screening result counselling by a physician after participation in lung cancer screening could be effective for increasing smoking cessation attempts.

Objective: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical practice. We aimed to compare the accuracy of CR interpretation assisted by AI-CAD to that of conventional interpretation in patients who presented to the emergency department (ED) with acute respiratory symptoms using a pragmatic randomized controlled trial. Materials and Methods: Patients who underwent CRs for acute respiratory symptoms at the ED of a tertiary referral institution were randomly assigned to intervention group (with assistance from an AI-CAD for CR interpretation) or control group (without AI assistance). Using a commercial AI-CAD system (Lunit INSIGHT CXR, version 2.0.2.0; Lunit Inc.). Other clinical practices were consistent with standard procedures. Sensitivity and false-positive rates of CR interpretation by duty trainee radiologists for identifying acute thoracic diseases were the primary and secondary outcomes, respectively. The reference standards for acute thoracic disease were established based on a review of the patient’s medical record at least 30 days after the ED visit. Results: We randomly assigned 3576 participants to either the intervention group (1761 participants; mean age ± standard deviation, 65 ± 17 years; 978 males; acute thoracic disease in 472 participants) or the control group (1815 participants; 64 ± 17 years; 988 males; acute thoracic disease in 491 participants). The sensitivity (67.2% [317/472] in the intervention group vs. 66.0% [324/491] in the control group; odds ratio, 1.02 [95% confidence interval, 0.70–1.49]; P = 0.917) and false-positive rate (19.3% [249/1289] vs. 18.5% [245/1324]; odds ratio, 1.00 [95% confidence interval, 0.79–1.26]; P = 0.985) of CR interpretation by duty radiologists were not associated with the use of AI-CAD. Conclusion AI-CAD did not improve the sensitivity and false-positive rate of CR interpretation for diagnosing acute thoracic disease in patients with acute respiratory symptoms who presented to the ED.

Objective: The clinical impact of artificial intelligence-based computer-aided detection (AI-CAD) beyond diagnostic accuracy remains uncertain. We aimed to investigate the influence of the clinical implementation of AI-CAD for chest radiograph (CR) interpretation in daily practice on the rate of referral for chest computed tomography (CT). Materials and Methods: AI-CAD was implemented in clinical practice at the Seoul National University Hospital. CRs obtained from patients who visited the pulmonology outpatient clinics before (January–December 2019) and after (January–December 2020) implementation were included in this study. After implementation, the referring pulmonologist requested CRs with or without AI-CAD analysis. We conducted multivariable logistic regression analyses to evaluate the associations between using AI-CAD and the following study outcomes: the rate of chest CT referral, defined as request and actual acquisition of chest CT within 30 days after CR acquisition, and the CT referral rates separately for subsequent positive and negative CT results.Multivariable analyses included various covariates such as patient age and sex, time of CR acquisition (before versus after AICAD implementation), referring pulmonologist, nature of the CR examination (baseline versus follow-up examination), and radiology reports presence at the time of the pulmonology visit. Results: A total of 28546 CRs from 14565 patients (mean age: 67 years; 7130 males) and 25888 CRs from 12929 patients (mean age: 67 years; 6435 males) before and after AI-CAD implementation were included. The use of AI-CAD was independently associated with increased chest CT referrals (odds ratio [OR], 1.33; P = 0.008) and referrals with subsequent negative chest CT results (OR, 1.46; P = 0.005). Meanwhile, referrals with positive chest CT results were not significantly associated with AI-CAD use (OR, 1.08; P = 0.647). Conclusion The use of AI-CAD for CR interpretation in pulmonology outpatients was independently associated with an increased frequency of overall referrals for chest CT scans and referrals with subsequent negative results.