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 The pain lateralization in cluster headache (CH) may be related to the asymmetry in the functions of the brain hemispheres. The right-sided dominance of pain in CH has been found inconsistently across studies, and so we aimed to characterize this and identify the factors influencing pain lateralization during current and previous bouts. Methods: This study enrolled 227 patients from the Korean Cluster Headache Registry between October 2018 and December 2020. We evaluated the side of pain during current and previous bouts, demographic features, and clinical characteristics, including handedness. Multivariable logistic regression analyses were performed to identify factors associated with the side of pain. Results: The 227 patients with CH included 131 (57.7%) with right-sided pain and 86 (37.9%) with left-sided pain during the current bout (p<0.001). The 189 patients with previous bouts of CH included 86.8% who consistently reported the same side of pain throughout multiple bouts (side-locked pain), with a higher prevalence of pain on the right than the left side (55.0% vs. 31.7%, p<0.001). Multivariable analyses revealed that higher age at diagnosis (odds ratio [OR]=1.045, p=0.031) and shorter CH attacks (OR=0.992, p=0.017) were associated with left-side-locked pain. However, handedness was not associated with the lateralization of leftside-locked pain. Conclusions This study has confirmed the predominance of right-sided pain throughout multiple CH bouts. We found that higher age at diagnosis and shorter CH attacks were associated with left-side-locked pain, suggesting that certain clinical factors are associated with the pain laterality. However, the underlying mechanisms linking these factors to lateralized pain remain unclear and therefore require further investigation.

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 The pain lateralization in cluster headache (CH) may be related to the asymmetry in the functions of the brain hemispheres. The right-sided dominance of pain in CH has been found inconsistently across studies, and so we aimed to characterize this and identify the factors influencing pain lateralization during current and previous bouts. Methods: This study enrolled 227 patients from the Korean Cluster Headache Registry between October 2018 and December 2020. We evaluated the side of pain during current and previous bouts, demographic features, and clinical characteristics, including handedness. Multivariable logistic regression analyses were performed to identify factors associated with the side of pain. Results: The 227 patients with CH included 131 (57.7%) with right-sided pain and 86 (37.9%) with left-sided pain during the current bout (p<0.001). The 189 patients with previous bouts of CH included 86.8% who consistently reported the same side of pain throughout multiple bouts (side-locked pain), with a higher prevalence of pain on the right than the left side (55.0% vs. 31.7%, p<0.001). Multivariable analyses revealed that higher age at diagnosis (odds ratio [OR]=1.045, p=0.031) and shorter CH attacks (OR=0.992, p=0.017) were associated with left-side-locked pain. However, handedness was not associated with the lateralization of leftside-locked pain. Conclusions This study has confirmed the predominance of right-sided pain throughout multiple CH bouts. We found that higher age at diagnosis and shorter CH attacks were associated with left-side-locked pain, suggesting that certain clinical factors are associated with the pain laterality. However, the underlying mechanisms linking these factors to lateralized pain remain unclear and therefore require further investigation.

Background: and Purpose The pain lateralization in cluster headache (CH) may be related to the asymmetry in the functions of the brain hemispheres. The right-sided dominance of pain in CH has been found inconsistently across studies, and so we aimed to characterize this and identify the factors influencing pain lateralization during current and previous bouts. Methods: This study enrolled 227 patients from the Korean Cluster Headache Registry between October 2018 and December 2020. We evaluated the side of pain during current and previous bouts, demographic features, and clinical characteristics, including handedness. Multivariable logistic regression analyses were performed to identify factors associated with the side of pain. Results: The 227 patients with CH included 131 (57.7%) with right-sided pain and 86 (37.9%) with left-sided pain during the current bout (p<0.001). The 189 patients with previous bouts of CH included 86.8% who consistently reported the same side of pain throughout multiple bouts (side-locked pain), with a higher prevalence of pain on the right than the left side (55.0% vs. 31.7%, p<0.001). Multivariable analyses revealed that higher age at diagnosis (odds ratio [OR]=1.045, p=0.031) and shorter CH attacks (OR=0.992, p=0.017) were associated with left-side-locked pain. However, handedness was not associated with the lateralization of leftside-locked pain. Conclusions This study has confirmed the predominance of right-sided pain throughout multiple CH bouts. We found that higher age at diagnosis and shorter CH attacks were associated with left-side-locked pain, suggesting that certain clinical factors are associated with the pain laterality. However, the underlying mechanisms linking these factors to lateralized pain remain unclear and therefore require further investigation.

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 The wearing-off (WO) phenomenon is the most common motor complication in advanced Parkinson’s disease (PD), but its identification remains challenging. The 9- and 19-item Wearing-off Questionnaires (WOQ-9 and WOQ-19) are self-assessment tools for motor and nonmotor symptoms that are widely used for WO screening. We produced Korean versions of the WOQ-19 and WOQ-9 (K-WOQ-19 and K-WOQ-9) and investigated their validity and reliability. Methods: We used the translation–back translation method to produce K-WOQ-19 and KWOQ-9, which were self-administered by 124 patients with PD. We conducted in-depth 10-minute interviews for confirming the presence of the WO phenomenon, and then stratified the participants into groups with and without WO. Diagnostic accuracy was assessed by analyzing receiver operating characteristic curves. Concurrent validity was assessed using the Movement Disorder Society–Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) and the Hoehn and Yahr stage with Spearman’s rank correlation analysis. Reliability was assessed based on test–retest Cohen’s kappa (κ) values and intraclass correlation coefficients (ICCs). Results: The optimal cutoff scores on the K-WOQ-19 and K-WOQ-9 for WO screening were 4 and 2, respectively. The test–retest ICCs of K-WOQ-19 and K-WOQ-9 were 0.943 and 0.938, respectively. Nineteen of the combined 20 items in K-WOQ-19 and K-WOQ-9 showed moderate-to-substantial agreement (κ=0.412–0.771, p<0.001). The scores on the translated scales were significantly correlated with MDS-UPDRS IV scores. Conclusions K-WOQ-19 and K-WOQ-9 are reliable and valid tools for detecting WO, with optimal cutoff scores of 4 and 2, respectively.

A chiral derivatization strategy with phenylglycine methyl ester (PGME) was employed to develop a straightforward method to determine the absolute configurations of N,N-dimethyl amino acids. The PGME derivatives were analyzed using liquid chromatography-mass spectrometry to identify the absolute configurations of various N,N-dimethyl amino acids based on their elution time and order. The established method was applied to assign the absolute configuration of the N,N-dimethyl phenylalanine in sanjoinine A (4), a cyclopeptide alkaloid isolated from Zizyphi Spinosi Semen widely used as herbal medicine for insomnia. Sanjoinine A displayed production of nitric oxide (NO) in LPS-activated RAW 264.7 cells.

Background: There is insufficient data on the benefits of empiric antibiotic combinations for hospital-acquired pneumonia (HAP). We aimed to investigate whether empiric antipseudomonal combination therapy with fluoroquinolones decreases mortality in patients with HAP. Methods: This multicenter, retrospective cohort study included adult patients admitted to 16 tertiary and general hospitals in Korea between January 1 and December 31, 2019.Patients with risk factors for combination therapy were divided into anti-pseudomonal non-carbapenem β-lactam monotherapy and fluoroquinolone combination therapy groups.Primary outcome was 30-day mortality. Propensity score matching (PSM) was used to reduce selection bias. Results: In total, 631 patients with HAP were enrolled. Monotherapy was prescribed in 54.7% (n = 345) of the patients, and combination therapy was prescribed in 45.3% (n = 286).There was no significant difference in 30-day mortality between the two groups (16.8% vs.18.2%, P = 0.729) or even after the PSM (17.5% vs. 18.2%, P = 0.913). After the PSM, adjusted hazard ratio for 30-day mortality from the combination therapy was 1.646 (95% confidence interval, 0.782–3.461; P = 0.189) in the Cox proportional hazards model. Moreover, there was no significant difference in the appropriateness of initial empiric antibiotics between the two groups (55.0% vs. 56.8%, P = 0.898). The proportion of multidrug-resistant (MDR) pathogens was high in both groups. Conclusion Empiric anti-pseudomonal fluoroquinolone combination therapy showed no survival benefit compared to β-lactam monotherapy in patients with HAP. Caution is needed regarding the routine combination of fluoroquinolones in the empiric treatment of HAP patients with a high risk of MDR.