Background: and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Background: and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Background: and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.

Background: Atrial fibrillation (AF) is associated with increased risks of adverse events including stroke and all-cause death. Understanding the pattern of causes of death (COD) with the relative risks in patients with AF compared to the non-AF population is essential in planning optimal care for patients with AF. We aimed to analyze the COD and its relative risks in patients with AF, using a nationwide population-based cohort. Methods: Using the Korean nationwide claims database, people aged 40 or older who received health examinations in 2009 were included if they had no missing values (n = 6,877,929).In total the study included 40,585 people with AF and 6,837,344 without AF. COD was defined by International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic codes. Comparison between the AF and non-AF groups was performed with Multivariate Cox proportional regression model. Results: In the AF group, cardiovascular diseases were the most common COD, causing 39.8% of all deaths, compared with 19.0% for non-AF subjects. The AF group was associated with a higher risk of death from cardiovascular and cerebrovascular diseases by almost 3-fold than the matched non-AF group (hazard ratios [HR], 3.082; 95% confidence intervals [CIs], 2.963–3.205 for cardiovascular diseases; HR, 2.981; 95% CI, 2.799–3.175 for cerebrovascular diseases, all P < 0.001). Among patients with AF, the risks of all-cause, cardiovascular, and cerebrovascular death were well-stratified by CHA2DS2 -VASc scores. The risk of cerebrovascular death was 11 times higher among patients with a CHA2DS2 -VASc score ≥ 7. Conclusion Compared to non-AF individuals, patients with AF had a higher risk of death from cardiovascular and cerebrovascular diseases, and the mortality risks were wellstratified by the CHA2DS2 -VASc score. Integrated care management of cardiovascular and cerebrovascular diseases for patients with AF might help mitigate mortality.

Background: Atrial fibrillation (AF) is associated with increased risks of adverse events including stroke and all-cause death. Understanding the pattern of causes of death (COD) with the relative risks in patients with AF compared to the non-AF population is essential in planning optimal care for patients with AF. We aimed to analyze the COD and its relative risks in patients with AF, using a nationwide population-based cohort. Methods: Using the Korean nationwide claims database, people aged 40 or older who received health examinations in 2009 were included if they had no missing values (n = 6,877,929).In total the study included 40,585 people with AF and 6,837,344 without AF. COD was defined by International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic codes. Comparison between the AF and non-AF groups was performed with Multivariate Cox proportional regression model. Results: In the AF group, cardiovascular diseases were the most common COD, causing 39.8% of all deaths, compared with 19.0% for non-AF subjects. The AF group was associated with a higher risk of death from cardiovascular and cerebrovascular diseases by almost 3-fold than the matched non-AF group (hazard ratios [HR], 3.082; 95% confidence intervals [CIs], 2.963–3.205 for cardiovascular diseases; HR, 2.981; 95% CI, 2.799–3.175 for cerebrovascular diseases, all P < 0.001). Among patients with AF, the risks of all-cause, cardiovascular, and cerebrovascular death were well-stratified by CHA2DS2 -VASc scores. The risk of cerebrovascular death was 11 times higher among patients with a CHA2DS2 -VASc score ≥ 7. Conclusion Compared to non-AF individuals, patients with AF had a higher risk of death from cardiovascular and cerebrovascular diseases, and the mortality risks were wellstratified by the CHA2DS2 -VASc score. Integrated care management of cardiovascular and cerebrovascular diseases for patients with AF might help mitigate mortality.

Background: Atrial fibrillation (AF) is associated with increased risks of adverse events including stroke and all-cause death. Understanding the pattern of causes of death (COD) with the relative risks in patients with AF compared to the non-AF population is essential in planning optimal care for patients with AF. We aimed to analyze the COD and its relative risks in patients with AF, using a nationwide population-based cohort. Methods: Using the Korean nationwide claims database, people aged 40 or older who received health examinations in 2009 were included if they had no missing values (n = 6,877,929).In total the study included 40,585 people with AF and 6,837,344 without AF. COD was defined by International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic codes. Comparison between the AF and non-AF groups was performed with Multivariate Cox proportional regression model. Results: In the AF group, cardiovascular diseases were the most common COD, causing 39.8% of all deaths, compared with 19.0% for non-AF subjects. The AF group was associated with a higher risk of death from cardiovascular and cerebrovascular diseases by almost 3-fold than the matched non-AF group (hazard ratios [HR], 3.082; 95% confidence intervals [CIs], 2.963–3.205 for cardiovascular diseases; HR, 2.981; 95% CI, 2.799–3.175 for cerebrovascular diseases, all P < 0.001). Among patients with AF, the risks of all-cause, cardiovascular, and cerebrovascular death were well-stratified by CHA2DS2 -VASc scores. The risk of cerebrovascular death was 11 times higher among patients with a CHA2DS2 -VASc score ≥ 7. Conclusion Compared to non-AF individuals, patients with AF had a higher risk of death from cardiovascular and cerebrovascular diseases, and the mortality risks were wellstratified by the CHA2DS2 -VASc score. Integrated care management of cardiovascular and cerebrovascular diseases for patients with AF might help mitigate mortality.

Background: Atrial fibrillation (AF) is associated with increased risks of adverse events including stroke and all-cause death. Understanding the pattern of causes of death (COD) with the relative risks in patients with AF compared to the non-AF population is essential in planning optimal care for patients with AF. We aimed to analyze the COD and its relative risks in patients with AF, using a nationwide population-based cohort. Methods: Using the Korean nationwide claims database, people aged 40 or older who received health examinations in 2009 were included if they had no missing values (n = 6,877,929).In total the study included 40,585 people with AF and 6,837,344 without AF. COD was defined by International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic codes. Comparison between the AF and non-AF groups was performed with Multivariate Cox proportional regression model. Results: In the AF group, cardiovascular diseases were the most common COD, causing 39.8% of all deaths, compared with 19.0% for non-AF subjects. The AF group was associated with a higher risk of death from cardiovascular and cerebrovascular diseases by almost 3-fold than the matched non-AF group (hazard ratios [HR], 3.082; 95% confidence intervals [CIs], 2.963–3.205 for cardiovascular diseases; HR, 2.981; 95% CI, 2.799–3.175 for cerebrovascular diseases, all P < 0.001). Among patients with AF, the risks of all-cause, cardiovascular, and cerebrovascular death were well-stratified by CHA2DS2 -VASc scores. The risk of cerebrovascular death was 11 times higher among patients with a CHA2DS2 -VASc score ≥ 7. Conclusion Compared to non-AF individuals, patients with AF had a higher risk of death from cardiovascular and cerebrovascular diseases, and the mortality risks were wellstratified by the CHA2DS2 -VASc score. Integrated care management of cardiovascular and cerebrovascular diseases for patients with AF might help mitigate mortality.