Objective: The purpose of this study was to investigate the related factors of elderly depression among Korean adults aged 60 years and above. Methods: From the database of Korea National Health and Nutrition Examination Survey conducted in 2018, data of 2,288 adults over age 60 who responded to the questionnaires of health interview were included in this study. We analyzed the data using logistic regression analysis. Results: According to our results, the number of chronic diseases seemed to be associated with depression in elderly people, es-pecially when they have more than 4 chronic diseases. Poorer self-rated health was identified as a significant factor and the odd ratio was the highest among all independent variables in our study. Walking over 10 minutes more than 4 times a week was considered as a protective factor for elderly depression. The association between education level and depression was inconsistent. Variables such as female gender, single status, smoking showed statistically insignificant results. Older age itself was not identified as a risk factor as odd ratios of all groups (over age 65) compared to reference group (age 60-64) were below 1. Conclusion This study confirms several related factors for elderly depression. Having more than 4 chronic diseases, poorer self-rated health were identified as a significant risk factor for depression. Regular walking was considered as a protective factor for elderly depression. The knowledge of these factors might help to manage risks of elderly depression and devise early intervention approaches.

BACKGROUND: We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system. METHODS: A 5-step retinal fundus image reading tool was developed that rates image quality, presence of abnormality, findings with location information, diagnoses, and clinical significance. Each image was evaluated by 3 different graders. Agreements among graders for each decision were evaluated. RESULTS: The 234,242 readings of 79,458 images were collected from 55 licensed ophthalmologists during 6 months. The 34,364 images were graded as abnormal by at-least one rater. Of these, all three raters agreed in 46.6% in abnormality, while 69.9% of the images were rated as abnormal by two or more raters. Agreement rate of at-least two raters on a certain finding was 26.7%–65.2%, and complete agreement rate of all-three raters was 5.7%–43.3%. As for diagnoses, agreement of at-least two raters was 35.6%–65.6%, and complete agreement rate was 11.0%–40.0%. Agreement of findings and diagnoses were higher when restricted to images with prior complete agreement on abnormality. Retinal/glaucoma specialists showed higher agreements on findings and diagnoses of their corresponding subspecialties. CONCLUSION: This novel reading tool for retinal fundus images generated a large-scale dataset with high level of information, which can be utilized in future development of machine learning-based algorithms for automated identification of abnormal conditions and clinical decision supporting system. These results emphasize the importance of addressing grader variability in algorithm developments.
Dataset ; Decision Support Systems, Clinical ; Diagnosis ; Machine Learning* ; Reading ; Retinaldehyde ; Specialization

PURPOSE: The SPAN, which is acronym standing for its four components: Startle, Physiological arousal, Anger, and Numbness, is a short post-traumatic stress disorder (PTSD) screening scale. This study sought to develop and validate a Korean version of the SPAN (SPAN-K). MATERIALS AND METHODS: Ninety-three PTSD patients (PTSD group), 73 patients with non-psychotic psychiatric disorders (psychiatric control group), and 88 healthy participants (normal control group) were recruited for this study. Participants completed a variety of psychiatric assessments including the SPAN-K, the Davidson Trauma Scale (DTS), the Clinician-Administered PTSD Scale (CAPS), and the State-Trait Anxiety Inventory (STAI). RESULTS: Cronbach's alpha and test-retest reliability values for the SPAN-K were both 0.80. Mean SPAN-K scores were 10.06 for the PTSD group, 4.94 for the psychiatric control group, and 1.42 for the normal control group. With respect to concurrent validity, correlation coefficients were 0.87 for SPAN-K vs. CAPS total scores (p<0.001) and 0.86 for SPAN-K vs. DTS scores (p<0.001). Additionally, correlation coefficients were 0.31 and 0.42 for SPAN-K vs. STAI-S and STAI-T, respectively. Receiver operating characteristic analysis of SPAN-K showed good diagnostic accuracy with an area under the curve (AUC) of 0.87. The SPAN-K showed the highest efficiency at a cutoff score of 7, with a sensitivity of 0.83, a specificity of 0.81, positive predictive value (PPV) of 0.88, and negative predictive value (NPV) of 0.73. CONCLUSION: These results suggest that the SPAN-K had good psychometric properties and may be a useful instrument for rapid screening of PTSD patients.
Humans ; *Psychological Techniques ; Republic of Korea ; Sensitivity and Specificity ; Stress Disorders, Post-Traumatic/*diagnosis/psychology

Two new azaphilone derivatives containing 1,3-dioxolane moiety, penidioxolanes A (1) and B (2), were isolated from marine-derived fungus Penicillium sp. KCB12C078, together with four known compounds (3-6) by chemical investigation. Compounds 1 - 6 were isolated by combination of silica gel, ODS column chromatography and preparative HPLC. Their structures were determined by analysis of spectroscopic data including 1D-, 2D-NMR, and MS techniques. The isolates were evaluated against cancer cell growth inhibition effects and antimicrobial activity.
Chromatography ; Chromatography, High Pressure Liquid ; Fungi ; Penicillium* ; Silica Gel