Changes of neural coupling between cognitive and motor networks associated with dual-task performance in Parkinson's disease.

BACKGOUND: Although cognitive control is essential for efficient gait, the associations between cognitive and motor networks regarding gait in individuals with Parkinson's disease (PD) remain to be determined. Herein, we enrolled 28 PD and 28 controls to compare internetwork coupling among cognitive and motor networks and examine its relationship with single- and dual-task gait performance in PD. METHODS: The dorsal attention network (DAN), left and right frontoparietal control networks (FPNs), sensorimotor network, and lateral motor network were identified using resting-state functional magnetic resonance imaging data. The time taken to complete a 10-m walk test during cognitive or physical dual-tasks in PD was calculated representing gait performance. RESULTS: We observed that the internetwork couplings between the DAN and motor networks and between the motor networks decreased whereas those between the left FPN and DAN and motor networks increased in PD compared to controls using a permutation test. There was no significant correlation between the internetwork couplings and single- and dual-task gait performance in PD. Nevertheless, improved cognitive dual-task performance showed a positive correlation with the DAN and left FPN coupling and a negative correlation with the DAN and lateral motor network coupling in a good performance group. The opposite relationship was observed in the poor cognitive dual-task performance group. CONCLUSION: Our findings suggest a neural mechanism of cognitive control on gait to compensate for reduced goal-directed attention in PD who maintain cognitive dual-task performance.

Digital Literacy and Associated Factors in Older Adults Living in Urban South Korea: A Qualitative Study.

This study aimed to explore digital literacy among community-dwelling older adults in urban South Korea. A semistructured interview guide was developed using the Digital Competence ( 2.0 framework, which emphasizes the competencies for full digital participation in five categories: information and data literacy, communication and collaboration, content creation, safety, and problem-solving. The data were analyzed using combined inductive and deductive content analysis. Inductive analysis identified three main categories: perceived ability to use digital technology, responses to digital technology, and contextual factors. In the results of deductive analysis, participants reported varying abilities in using digital technologies for information and data literacy, communication or collaboration, and problem-solving. However, their abilities were limited in handling the safety or security of digital technology and lacked in creating digital content. Responses to digital technology contain subcategories of perception (positive or negative) and behavior (trying or avoidance). Regarding contextual factors, aging-related physical and cognitive changes were identified as barriers to digital literacy. The influence of families or peers was viewed as both a facilitator and a barrier. Our participants recognized the importance of using digital devices to keep up with the trend of digitalization, but their digital literacy was mostly limited to relatively simple levels.

How are new nurses satisfied with their jobs? From the work value perspective of Generations Y and Z nurses.

BACKGROUND: Job satisfaction has garnered significant interest across multiple disciplines as it plays a vital role in shaping human resource strategies. In the field of nursing, enhancing job satisfaction can help prevent workforce shortages. Work values and job-related characteristics are significant predictors of job satisfaction. However, the influence of factors may change as younger generations join the nursing workforce. Although research on generational commonalities and differences in work values is increasing, there is insufficient information on generational differences in the interplay between work values and job satisfaction. This study investigated the factors associated with job satisfaction of new nurses in each generational group based on a work value perspective. METHODS: A total of 280 new nurses (151 from Generation Y and 129 from Generation Z) were selected from the Graduates Occupational Mobility Survey. Multiple linear regression analyses were performed to determine the factors associated with job satisfaction in both groups. RESULTS: Most participants graduated with a diploma (61.1%), were paid less than the average salary of each group (60.4%), and conducted shift (72.9%) and overtime work (64.3%). Work values and job satisfaction levels were not significantly different between the two groups. Multiple linear regression analyses showed that career growth and task work values were associated with job satisfaction for Generation Z, while task, reputation, and environment work values were associated with job satisfaction for Generation Y. Among the job-related characteristics, nurses' job tenure was associated with job satisfaction in both groups; salary and overtime had varying relationships with job satisfaction between the two generations. CONCLUSIONS: Understanding generational differences is crucial for improving the effective management of new generational nurses. Our study findings support that different work value dimensions and job-related characteristics were associated with job satisfaction in each generation. Accordingly, it is essential to develop distinct initiatives, such as a well-structured program, to support the continued career growth of the new Generation Z nurses, thereby enhancing their job satisfaction. Furthermore, providing a conducive working environment that helps new-generation nurses overcome challenges and ensures personal lives should be considered.

Deciphering Functional Connectivity Differences Between Motor Imagery and Execution of Target-Oriented Grasping.

This study aimed to delineate overlapping and distinctive functional connectivity in visual motor imagery, kinesthetic motor imagery, and motor execution of target-oriented grasping action of the right hand. Functional magnetic resonance imaging data were obtained from 18 right-handed healthy individuals during each condition. Seed-based connectivity and multi-voxel pattern analyses were employed after selecting seed regions with the left primary motor cortex and supplementary motor area. There was equivalent seed-based connectivity during the three conditions in the bilateral frontoparietal and temporal areas. When the seed region was the left primary motor cortex, increased connectivity was observed in the left cuneus and superior frontal area during visual and kinesthetic motor imageries, respectively, compared with that during motor execution. Multi-voxel pattern analyses revealed that each condition was differentiated by spatially distributed connectivity patterns of the left primary motor cortex within the right cerebellum VI, cerebellum crus II, and left lingual area. When the seed region was the left supplementary motor area, the connectivity patterns within the right putamen, thalamus, cerebellar areas IV-V, and left superior parietal lobule were significantly classified above chance level across the three conditions. The present findings improve our understanding of the spatial representation of functional connectivity and its specific patterns among motor imagery and motor execution. The strength and fine-grained connectivity patterns of the brain areas can discriminate between motor imagery and motor execution.

Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea.

BACKGROUND: In 2011, Korean Neuropsychiatric Association renamed schizophrenia from 'mind split disorder' ('Jungshinbunyeolbyung' in Korean) to 'attunement disorder' ('Johyeonbyung' in Korean), in a strategic way to reduce social stigma toward people with schizophrenia. However, there remains an elusive consensus that how the renaming effort has contributed to changes in the social perception of schizophrenia in Korea. METHODS: With this regard, we explored whether media frames alter the social perception, in ways of respecting or disrespecting schizophrenia patients before and after the renaming. This study extensively investigated media keywords related to schizophrenia across the time by applying both language and epidemiologic analyses. RESULTS: In results, the media keywords have been negatively described for schizophrenia patients both before and after the renaming. Further, from an analysis using the regression model, a significant correlation was observed between the frequency of negative keywords and the hospitalization frequency of schizophrenia patients. CONCLUSIONS: These findings suggest that the social perception of schizophrenia has been scarcely changed, but rather remained negatively biased against schizophrenia patients, in spite of the renaming effort. Notably, the biased media frames have been demonstrated to negatively impact on the social perception, and even on the medical use patterns of general schizophrenia patients. In conclusion, we suggest that the unbiased media frames along with the renaming effort may collectively help reduce the negative social perception of schizophrenia. TRIAL REGISTRATION: This study was approved from the Institute of Review Board (IRB) of the Yoing-In Mental Hospital (IRB No. YIMH-IRB-2019-02).

Anthocyanin oligomer (grape skin extract) administration improves dry eye disease: A randomised, double-blind, placebo-controlled study.

BACKGROUND: Dry eye disease is a chronic, progressive ocular disease characterised by ocular discomfort and is one of the most common ophthalmological disorders that affects people's lives. METHODS: This study investigated the clinical efficacy of anthocyanin oligomers (grape skin extract) for the treatment of dry eye. One hundred and eight patients with dry eye were randomly divided into placebo and treatment groups, each with 54 cases. The placebo group received maltodextrin (800 mg/day) and the treatment group received anthocyanin oligomers (800 mg/day). Clinical efficacy, clinical indices, and occurrence of adverse reactions were compared between the two groups. RESULTS: Anthocyanin oligomers were safe and effective in mild-to-moderate dry eye disease, improving the tear break-up time, intraocular pressure, ocular surface disease, and patient symptomatology. CONCLUSIONS: The use of oral anthocyanin oligomers in the treatment of dry eye patients can enhance the therapeutic effect and improve the quality of life of patients while ensuring the safety of treatment, making this therapeutic option suitable for wider application.

Efficient Collaboration Between Radiologists Using the PACS-Integrated Refer Function to Reduce Communication Times.

The purpose of this study was to assess the utility of a picture archiving and communication systems (PACS)-integrated refer function for improving collaboration between radiologists and radiographers during daily reading sessions. Retrospective analysis was conducted on refers sent by radiologists using a PACS-integrated refer system from March 2020 to December 2021. Refers were categorized according to receiver: radiologists in the same division (intra-division), radiologists in a different division (inter-division), and radiographers. The proportions of answered refers, content of refers, and timing of refer posts were evaluated. Additionally, time intervals in minutes from initial refer post to refer response were assessed to assess the efficiency of the refer system and compared according to receivers using the Mann-Whitney U test. Among a total of 691 refers posted by radiologists, 579 (83.8%) were answered directly using the refer function in PACS. Of the answered refers, 346 refers (59.8%) were made between radiologists, and 173 (50%) were intra-division refers. About the content of refers, about 82.6% of radiologists' refers were about imaging interpretation consultation, and about 98.9% of refers from radiologists to radiographers were for image quality control. The median time interval until refer response was 9 min, and this response time did not differ between intra-division and inter-division refers (p = 0.998). Of the refers that got responses, 74.3% (257/346) were sent among radiologists before official reports were made, and the median time until refer response was 9-10 min. The proportion of refers answered by radiographers was 85.7% (233/272). The median time interval until refer response by radiographers was 87 min for all refers, and 63% were made within 6 h. Therefore, the PACS-integrated refer function can facilitate communication between radiologists for image interpretation and quality control.

Consistency of Artificial Intelligence (AI)-based Diagnostic Support Software in Short-term Digital Mammography Reimaging After Core Needle Biopsy.

To evaluate the consistency in the performance of Artificial Intelligence (AI)-based diagnostic support software in short-term digital mammography reimaging after core needle biopsy. Of 276 women who underwent short-term (<3 mo) serial digital mammograms followed by breast cancer surgery from Jan. to Dec. 2017, 550 breasts were included. All core needle biopsies for breast lesions were performed between serial exams. All mammography images were analyzed using a commercially available AI-based software providing an abnormality score (0-100). Demographic data for age, interval between serial exams, biopsy, and final diagnosis were compiled. Mammograms were reviewed for mammographic density and finding. Statistical analysis was performed to evaluate the distribution of variables according to biopsy and to test the interaction effects of variables with the difference in AI-based score according to biopsy. AI-based score of 550 exams (benign or normal in 263 and malignant in 287) showed significant difference between malignant and benign/normal exams (0.48 vs. 91.97 in first exam and 0.62 vs. 87.13 in second exam, P<0.0001). In comparison of serial exams, no significant difference was found in AI-based score. AI-based score difference between serial exams was significantly different according to biopsy performed or not (-0.25 vs. 0.07, P = 0.035). In linear regression analysis, there was no significant interaction effect of all clinical and mammographic characteristics with mammographic examinations performed after biopsy or not. The results from AI-based diagnostic support software for digital mammography was relatively consistent in short-term reimaging even after core needle biopsy.

Associations among leadership, resources, and nurses' work engagement: findings from the fifth korean Working Conditions Survey.

BACKGROUND: Nurses' work engagement has received extensive attention due to its positive impacts on individual and organizational outcomes, including patient safety and quality care in healthcare organizations. Although nurse managers' leadership and a variety of resources have been identified as important factors of nurses' work engagement, these relationships have not been well understood in Korean nursing contexts. The purpose of this study was to examine the associations among nurse managers' leadership, resources, and work engagement among Korean nurses after controlling for nurses' demographic and work-related characteristics. METHODS: This is a cross-sectional study using data from the fifth Korean Working Conditions Survey. Using a sample of 477 registered nurses, we employed hierarchical linear regression analyses. Nurse managers' leadership, job resources (organizational justice and support from peers), professional resources (employee involvement), and personal resources (meaning of work) were examined as potential predictors of nurses' work engagement. RESULTS: We found that nurse managers' leadership (ß = 0.26, 95% confidence interval [CI] = 0.17-0.41) was the strongest predictor of nurses' work engagement, followed by meaning of work (ß = 0.20, 95% CI = 0.07-0.18), organizational justice (ß = 0.19, 95% CI = 0.10-0.32), and support from peers (ß = 0.14, 95% CI = 0.04-0.23). Employee involvement was not a statistically significant predictor of nurses' work engagement (ß = -0.07, 95% CI = -0.11-0.01). CONCLUSIONS: Our findings suggest that comprehensive approaches are required to promote nurses' work engagement. Considering that nurse managers' leadership was the strongest predictor of nurses' work engagement, nurse managers should demonstrate supportive leadership behaviors such as acknowledging and praising their unit nurses' work performance. Furthermore, both individual- and organizational-level strategies are necessary for nurses to be engaged at work.

US, Mammography, and Histopathologic Evaluation to Identify Low Nuclear Grade Ductal Carcinoma in Situ.

Background Low nuclear grade ductal carcinoma in situ (DCIS) identified at biopsy can be upgraded to intermediate to high nuclear grade DCIS at surgery. Methods that confirm low nuclear grade are needed to consider nonsurgical approaches for these patients. Purpose To develop a preoperative model to identify low nuclear grade DCIS and to evaluate factors associated with low nuclear grade DCIS at biopsy that was not upgraded to intermediate to high nuclear grade DCIS at surgery. Materials and Methods In this retrospective study, 470 women (median age, 50 years; interquartile range, 44-58 years) with 477 pure DCIS lesions at surgical histopathologic evaluation were included (January 2010 to December 2015). Patients were divided into the training set (n = 330) or validation set (n = 147) to develop a preoperative model to identify low nuclear grade DCIS. Features at US (mass, nonmass) and at mammography (morphologic characteristics, distribution of microcalcification) were reviewed. The upgrade rate of low nuclear grade DCIS was calculated, and multivariable regression was used to evaluate factors for associations with low nuclear grade DCIS that was not upgraded later. Results A preoperative model that included lesions manifesting as a mass at US without microcalcification and no comedonecrosis at biopsy was used to identify low nuclear grade DCIS, with a high area under the receiver operating characteristic curve of 0.97 (95% CI: 0.94, 1.00) in the validation set. The upgrade rate of low nuclear grade DCIS at biopsy was 38.8% (50 of 129). Ki-67 positivity (odds ratio, 0.04; 95% CI: 0.0003, 0.43; P = .005) was inversely associated with constant low nuclear grade DCIS. Conclusion The upgrade rate of low nuclear grade ductal carcinoma in situ (DCIS) at biopsy to intermediate to high nuclear grade DCIS at surgery occurred in more than a third of patients; low nuclear grade DCIS at final histopathologic evaluation could be identified if the mass was viewed at US without microcalcifications and had no comedonecrosis at histopathologic evaluation of biopsy. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Rahbar in this issue. An earlier incorrect version appeared online. This article was corrected on April 14, 2022.

Multi-omics analysis revealed TEK and AXIN2 are potential biomarkers in multifocal papillary thyroid cancer.

BACKGROUND: Papillary thyroid carcinoma (PTC), the most common endocrine cancer, accounts for 80-85% of all malignant thyroid tumors. This study focused on identifying targets that affect the multifocality of PTC. In a previous study, we determined 158 mRNAs related to multifocality in BRAF-mutated PTC using The Cancer Genome Atlas. METHODS: We used multi-omics data (miRNAs and mRNAs) to identify the regulatory mechanisms of the investigated mRNAs. miRNA inhibitors were used to determine the relationship between mRNAs and miRNAs. We analyzed the target protein levels in patient sera using ELISA and immunohistochemical staining of patients' tissues. RESULTS: We identified 44 miRNAs that showed a negative correlation with mRNA expression. Using in vitro experiments, we identified four miRNAs that inhibit TEK and/or AXIN2 among the target mRNAs. We also showed that the downregulation of TEK and AXIN2 decreased the proliferation and migration of BRAF ( +) PTC cells. To evaluate the diagnostic ability of multifocal PTC, we examined serum TEK or AXIN2 in unifocal and multifocal PTC patients using ELISA, and showed that the serum TEK in multifocal PTC patients was higher than that in the unifocal PTC patients. The immunohistochemical study showed higher TEK and AXIN2 expression in multifocal PTC than unifocal PTC. CONCLUSIONS: Both TEK and AXIN2 play a potential role in the multifocality of PTC, and serum TEK may be a diagnostic marker for multifocal PTC.

Depiction of breast cancers on digital mammograms by artificial intelligence-based computer-assisted diagnosis according to cancer characteristics.

OBJECTIVE: To evaluate how breast cancers are depicted by artificial intelligence-based computer-assisted diagnosis (AI-CAD) according to clinical, radiological, and pathological factors. MATERIALS AND METHODS: From January 2017 to December 2017, 896 patients diagnosed with 930 breast cancers were enrolled in this retrospective study. Commercial AI-CAD was applied to digital mammograms and abnormality scores were obtained. We evaluated the abnormality score according to clinical, radiological, and pathological characteristics. False-negative results were defined by abnormality scores less than 10. RESULTS: The median abnormality score of 930 breasts was 87.4 (range 0-99). The false-negative rate of AI-CAD was 19.4% (180/930). Cancers with an abnormality score of more than 90 showed a high proportion of palpable lesions, BI-RADS 4c and 5 lesions, cancers presenting as mass with or without microcalcifications and invasive cancers compared with low-scored cancers (all p < 0.001). False-negative cancers were more likely to develop in asymptomatic patients and extremely dense breasts and to be diagnosed as occult breast cancers and DCIS compared to detected cancers. CONCLUSION: Breast cancers depicted with high abnormality scores by AI-CAD are associated with higher BI-RADS category, invasive pathology, and higher cancer stage. KEY POINTS: • High-scored cancers by AI-CAD included a high proportion of BI-RADS 4c and 5 lesions, masses with or without microcalcifications, and cancers with invasive pathology. • Among invasive cancers, cancers with higher T and N stage and HER2-enriched subtype were depicted with higher abnormality scores by AI-CAD. • Cancers missed by AI-CAD tended to be in asymptomatic patients and extremely dense breasts and to be diagnosed as occult breast cancers by radiologists.

AI-CAD for differentiating lesions presenting as calcifications only on mammography: outcome analysis incorporating the ACR BI-RADS descriptors for calcifications.

OBJECTIVES: To evaluate how AI-CAD triages calcifications and to compare its performance to an experienced breast radiologist. METHODS: Among routine mammography performed between June 2016 and May 2018, 535 lesions detected as calcifications only on mammography in 500 women (mean age, 48.8 years) that were additionally interpreted with additional magnification views were included in this study. One dedicated breast radiologist retrospectively reviewed the magnification mammograms to assess morphology, distribution, and final assessment category according to ACR BI-RADS. AI-CAD analyzed routine mammograms providing AI-CAD marks and corresponding AI-CAD scores (ranging from 0 to 100%), for which values ≥ 10% were considered positive. Ground truth in terms of malignancy or benignity was confirmed with a histopathologic diagnosis or at least 1 year of imaging follow - up. RESULTS: Of the 535 calcifications, 215 (40.2%) were malignant. Calcifications with positive AI-CAD scores showed significantly higher PPVs compared to calcifications with negative scores for all morphology (all p < 0.05). PPVs were significantly higher in calcifications with positive AI-CAD scores compared to those with negative scores for BI-RADS 3, 4a, or 4b assessments (all p < 0.05). AI-CAD and the experienced radiologist did not show significant difference in diagnostic performance; sensitivity 92.1% vs 95.4% (p = 0.125), specificity 71.9% vs 72.5% (p = 0.842), and accuracy 80.0% vs 81.7% (p = 0.413). CONCLUSION: Among calcifications with same morphology or BI-RADS assessment, those with positive AI-CAD scores had significantly higher PPVs. AI-CAD showed similar diagnostic performances to the experienced radiologist for calcifications detected on mammography. KEY POINTS: • Among calcifications with same morphology or BI-RADS assessment, those with positive AI-CAD scores had significantly higher PPVs. • AI-CAD showed similar diagnostic performance to an experienced radiologist in assessing lesions detected as calcifications only on mammography. • Among malignant calcifications, calcifications with positive AI-CAD scores showed higher rates of invasive cancers than calcifications with negative scores (all p > 0.05).

Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer using tumor heterogeneity and angiogenesis properties on MRI.

OBJECTIVES: To investigate machine learning approaches for radiomics-based prediction of prognostic biomarkers and molecular subtypes of breast cancer using quantification of tumor heterogeneity and angiogenesis properties on magnetic resonance imaging (MRI). METHODS: This prospective study examined 291 invasive cancers in 288 patients who underwent breast MRI at 3 T before treatment between May 2017 and July 2019. Texture and perfusion analyses were performed and a total of 160 parameters for each cancer were extracted. Relationships between MRI parameters and prognostic biomarkers were analyzed using five machine learning algorithms. Each model was built using only texture features, only perfusion features, or both. Model performance was compared using the area under the receiver-operating characteristic curve (AUC) and the DeLong method, and the importance of MRI parameters in prediction was derived. RESULTS: Texture parameters were associated with the status of hormone receptors, human epidermal growth factor receptor 2, and Ki67, tumor size, grade, and molecular subtypes (p < 0.002). Perfusion parameters were associated with the status of hormone receptors and Ki67, grade, and molecular subtypes (p < 0.003). The random forest model integrating texture and perfusion parameters showed the highest performance (AUC = 0.75). The performance of the random forest model was the best with a special scale filter of 0 (AUC = 0.80). The important parameters for prediction were texture irregularity (entropy) and relative extracellular extravascular space (Ve). CONCLUSIONS: Radiomic machine learning that integrates tumor heterogeneity and angiogenesis properties on MRI has the potential to noninvasively predict prognostic factors of breast cancer. KEY POINTS: • Machine learning, integrating tumor heterogeneity and angiogenesis properties on MRI, can be applied to predict prognostic biomarkers and molecular subtypes in breast cancer. • The random forest model showed the best predictive performance among the five machine learning models (logistic regression, decision tree, naïve Bayes, random forest, and artificial neural network). • The most important MRI parameters for predicting prognostic factors in breast cancer were texture irregularity (entropy) among texture parameters and relative extracellular extravascular space (Ve) among perfusion parameters.

Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence-Based Computer-Aided Detection.

BACKGROUND. Postoperative mammograms present interpretive challenges due to postoperative distortion and hematomas. The application of digital breast tomosyn-thesis (DBT) and artificial intelligence-based computer-aided detection (AI-CAD) after breast-conserving therapy (BCT) has not been widely investigated. OBJECTIVE. The purpose of our study was to assess the impact of additional DBT or AI-CAD on recall rate and diagnostic performance in women undergoing mammographic surveillance after BCT. METHODS. This retrospective study included 314 women (mean age, 53.3 ± 10.6 [SD] years; four with bilateral breast cancer) who underwent BCT followed by DBT (mean interval from surgery to DBT, 15.2 ± 15.4 months). Three breast radiologists independently reviewed images in three sessions: digital mammography (DM), DM with DBT (DM plus DBT), and DM with AI-CAD (DM plus AI-CAD). Recall rates and diagnostic performance were compared between DM, DM plus DBT, and DM plus AI-CAD using the readers' mean results. RESULTS. Of the 314 women, six breast recurrences (three ipsilateral and three contralateral) had developed at the time of surveillance mammography. The ipsilateral breast recall rate was lower for DM plus AI-CAD (1.9%) than for DM (11.2%) or DM plus DBT (4.1%) (p < .001). The contralateral breast recall rate was significantly lower for DM plus AI-CAD (1.5%, p < .001) than for DM (6.6%) but for not DM plus DBT (2.7%, p = .08). In the ipsilateral breast, accuracy was higher for DM plus AI-CAD (97.0%) than for DM (88.5%) or DM plus DBT (94.8%) (p < .05); specificity was higher for DM plus AI-CAD (98.3%) than for DM (89.3%) or DM plus DBT (96.1%) (p < .05); sensitivity was significantly lower for DM plus AI-CAD (22.2%) than for DM (66.7%, p = .03) but not DM plus DBT (22.2%, p > .99). In the contralateral breast, accuracy was significantly higher for DM plus AI-CAD (97.1%) than for DM (92.5%, p < .001) but not DM plus DBT (96.1%, p = .25); specificity was significantly higher for DM plus AI-CAD (98.6%) than for DM (93.7%, p < .001) but not DM plus DBT (97.5%) (p = .09); sensitivity was not different between DM (33.3%), DM plus DBT (22.2%), and DM plus AI-CAD (11.1%) (p > .05). CONCLUSION. After BCT, adjunct DBT or AI-CAD reduced recall rates and improved accuracy in the ipsilateral and contralateral breasts compared with DM. In the ipsilateral breast, the addition of AI-CAD resulted in a lower recall rate and higher accuracy than the addition of DBT. CLINICAL IMPACT. AI-CAD may help address the challenges of interpreting post-BCT surveillance mammograms.

Risks of complicated acute appendicitis in patients with psychiatric disorders.

BACKGROUND: Acute appendicitis often presents with vague abdominal pain, which fosters diagnostic challenges to clinicians regarding early detection and proper intervention. This is even more problematic with individuals with severe psychiatric disorders who have reduced sensitivity to pain due to long-term or excessive medication use or disturbed bodily sensation perceptions. This study aimed to determine whether psychiatric disorder, psychotropic prescription, and treatment compliance increase the risks of complicated acute appendicitis. METHODS: The diagnosis records of acute appendicitis from four university hospitals in Korea were investigated from 2002 to 2020. A total of 47,500 acute appendicitis-affected participants were divided into groups with complicated and uncomplicated appendicitis to determine whether any of the groups had more cases of psychiatric disorder diagnoses. Further, the ratio of complicated compared to uncomplicated appendicitis in the mentally ill group was calculated regarding psychotropic dose, prescription duration, and treatment compliance. RESULTS: After adjusting for age and sex, presence of psychotic disorder (odds ratio [OR]: 1.951; 95% confidence interval [CI]: 1.218-3.125), and bipolar disorder (OR: 2.323; 95% CI: 1.194-4.520) was associated with a higher risk of having complicated appendicitis compared with absence of psychiatric disorders. Patients who are taking high-daily-dose antipsychotics, regardless of prescription duration, show high complicated appendicitis risks; High-dose antipsychotics for < 1 year (OR: 1.896, 95% CI: 1.077-3.338), high-dose antipsychotics for 1-5 years (OR: 1.930, 95% CI: 1.144-3.256). Poor psychiatric outpatient compliance was associated with a high risk of complicated appendicitis (OR: 1.664, 95% CI: 1.014-2.732). CONCLUSIONS: This study revealed a close relationship in the possibility of complicated appendicitis in patients with severe psychiatric disorders, including psychotic and bipolar disorders. The effect on complicated appendicitis was more remarkable by the psychiatric disease entity itself than by psychotropic prescription patterns. Good treatment compliance and regular visit may reduce the morbidity of complicated appendicitis in patients with psychiatric disorders.

Incidence and predictors of multimorbidity among older adults in Korea: a 10-year cohort study.

BACKGROUND: Due to the rapid growth of the older adult population, multimorbidity has become a global concern for an aging society. Multimorbidity has been associated with poor health outcomes, including low quality of life and a high risk of mortality, resulting in an overload of healthcare systems. However, multimorbidity incidence and its related factors are poorly understood among older adults. This study aimed to determine whether sociodemographic characteristics, lifestyle, and psychosocial factors predict multimorbidity incidence among older adults in Korea. METHODS: This longitudinal study used the Korean Longitudinal Study of Aging (KLoSA) dataset from 2008 to 2018. The KLoSA is a panel survey of nationally representative samples aimed at providing data for developing socioeconomic policies for the increasing aging population in Korea. The study sample included 1967 older adults aged 65 years and over who had none or one of the chronic diseases at the baseline in 2008. Multimorbidity incidence was defined as the co-existence of two or more chronic diseases among 12 doctor-diagnosed diseases based on self-reports. Cox's proportional hazards models were used to identify significant predictors of multimorbidity incidence over a 10-year follow-up period. RESULTS: Among 1967 respondents (female 54.5%, mean age 72.94), 625 (31.8%) incidents of multimorbidity were reported, contributing to 47.5 incidents per 1000 people after 10 years of follow-up. Low levels of social interaction, obesity, past smoking habits, and current or past drinking habits were identified as significant predictors of multimorbidity incidence among older adults in Korea. CONCLUSIONS: This study identified older adults at high risk for multimorbidity incidence. These groups require more attention from health care providers in the course of chronic disease monitoring and management. Specific interventions and health policies to promote social interaction and a healthy lifestyle are essential to delay multimorbidity incidence. This longitudinal approach will contribute to developing preventive strategies to reduce the incidence of multimorbidity among older adults.

Motivators and inhibitors of nurses' speaking up behaviours: A descriptive qualitative study.

AIMS: To identify factors that motivate or inhibit nurses' speaking up for patient safety. DESIGN: A descriptive qualitative study. METHODS: We conducted semi-structured interviews with 15 nurses from four Korean hospitals between December 2020 and January 2021. Data were analysed using inductive content analysis. RESULTS: We identified safety culture, supportive unit managers and role models, positive reactions from or familiarity with others, high-risk situations and personal characteristics and beliefs as motivators of nurses' speaking up. Hierarchies and power differentials, seniority and unit tenure, concerns about relationships, and heavy workloads inhibited nurses' speaking up. CONCLUSION: Individual, organizational and cultural characteristics influence nurses' decisions on whether or not to voice their concerns, suggestions or ideas. Certain characteristics of Korean culture, such as strong hierarchies and the valuing of good relationships, play an important role in nurses' speaking up behaviours. Our findings can be used to inform educational interventions and management expectations about interpersonal behaviours, especially in a culture where age- and seniority-based hierarchies and collectivism are prevalent. IMPACT: Nurses perceived speaking up as a challenging behaviour, and they sometimes withhold their voices even when speaking up is needed for patient safety. We found that individual, organizational, and contextual factors affect the speaking up behaviours of nurses. Nurse managers can create environments that are more supportive of nurses' speaking up behaviours by using inclusive leadership to create psychological safety, by inviting and showing appreciation for staff input, and by helping physicians and senior nurses understand the importance of all nurses' voices. NO PATIENT OR PUBLIC CONTRIBUTION: Patient or public contribution does not apply to this study as its purpose was to explore the speaking up experiences of nurses themselves.

Fabrication and evaluation of bilateral Helmholtz radiofrequency coil for thermo-stable breast image with reduced artifacts.

PURPOSE: The positron emission tomography (PET)-magnetic resonance (MR) system is a newly emerging technique that yields hybrid images with high-resolution anatomical and metabolic information. With PET-MR imaging, a definitive diagnosis of breast abnormalities will be possible with high spatial accuracy and images will be acquired for the optimal fusion of anatomic locations. Therefore, we propose a PET-compatible two-channel breast MR coil with minimal disturbance to image acquisition which can be used for simultaneous PET-MR imaging in patients with breast cancer. MATERIALS AND METHODS: For coil design and construction, the conductor loops of the Helmholtz coil were tuned, matched, and subdivided with nonmagnetic components. Element values were optimized with an electromagnetic field simulation. Images were acquired on a GE 600 PET-computed tomography (CT) and GE 3.0 T MR system. For this study, we used the T1-weighted image (volunteer; repetition time (TR), 694 ms; echo time (TE), 9.6 ms) and T2-weighted image (phantom; TR, 8742 ms; TE, 104 ms) with the fast spin-echo sequence. RESULTS: The results of measuring image factors with the proposed radiofrequency (RF) coil and standard conventional RF coil were as follows: signal-to-noise ratio (breast; 207.7 vs. 175.2), percent image uniformity (phantom; 89.22%-91.27% vs. 94.63%-94.77%), and Hounsfield units (phantom; -4.51 vs. 2.38). CONCLUSIONS: Our study focused on the feasibility of proposed two-channel Helmholtz loops (by minimizing metallic components and soldering) for PET-MR imaging and found the comparable image quality to the standard conventional coil. We believe our work will help significantly to improve image quality with the development of a less metallic breast MR coil.

Mammographic Density Assessment by Artificial Intelligence-Based Computer-Assisted Diagnosis: A Comparison with Automated Volumetric Assessment.

We evaluated and compared the mammographic density assessment of an artificial intelligence-based computer-assisted diagnosis (AI-CAD) program using inter-rater agreements between radiologists and an automated density assessment program. Between March and May 2020, 488 consecutive mammograms of 488 patients (56.2 ± 10.9 years) were collected from a single institution. We assigned four classes of mammographic density based on BI-RADS (Breast Imaging Reporting and Data System) using commercial AI-CAD (Lunit INSIGHT MMG), and compared inter-rater agreements between radiologists, AI-CAD, and another commercial automated density assessment program (Volpara®). The inter-rater agreement between AI-CAD and the reader consensus was 0.52 with a matched rate of 68.2% (333/488). The inter-rater agreement between Volpara® and the reader consensus was similar to AI-CAD at 0.50 with a matched rate of 62.7% (306/488). The inter-rater agreement between AI-CAD and Volpara® was 0.54 with a matched rate of 61.5% (300/488). In conclusion, density assessments by AI-CAD showed fair agreement with those of radiologists, similar to the agreement between the commercial automated density assessment program and radiologists.