Purpose: To evaluate the compatibility and usability of test results obtained from the IDRA and Keratograph 5M in clinical settings by comparing their performance in patients with dry eye disease. Methods: From December 27 to 30, 2022, a study was conducted on 30 patients diagnosed with dry eye utilizing both the Keratograph 5M and IDRA devices. The parameters compared and analyzed included lipid layer thickness, tear meniscus height, tear film break-up time, and meibography. A paired t-test was used for statistical comparison. The lipid layer thickness in the Keratograph 5M was graded on a scale from 0 to 4 based on thickness. Results: No significant differences were found between the two devices in tear film break-up time, tear meniscus height, and meibography (p = 0.148, 0.072, 0.124, respectively). However, the tear lipid layer thickness measured by IDRA showed a proportional relationship with the grade assigned by the Keratograph 5M (Kendall R = 0.217, p = 0.037; Spearman R = 0.260, p = 0.045). Conclusions The IDRA device offers the advantage of performing multiple dry eye tests; simultaneously, thereby saving time compared to the Keratograph 5M. Both devices can be used compatibly with IDRA particularly advantageous for providing a numerical value for tear lipid layer thickness which enhances the convenience of dry eye diagnosis and treatment.

This study aimed to derive insights into professional self-concept, teamwork, and job satisfaction among emergency department (ED) nurses and to prepare basic data for improving job satisfaction among ED nurses. Methods: The study was conducted between October 2023 and April 2024 at two certified tertiary hospitals and one general hospital in Gyeonggi-do, Korea, among 124 ED nurses. Data were analyzed using SPSS version 26.0, and the analysis included descriptive statistics, the t-test, Pearson correlation, and multiple regression. Results: The factors affecting job satisfaction in ED nurses were professional self-concept (β = .66, p < .001), teamwork (β = .17, p = .003), and ED work satisfaction (β = .17, p = .003), and the overall explanatory power of the model was 67.7%. Conclusion: This study makes a significant contribution by demonstrating that professional self-concept and teamwork can increase job satisfaction in ED nurses. Therefore, as a strategy to increase job satisfaction through improving ED nurses’ professional self-concept and teamwork, effort should be made to apply team simulation programs that provide education and self-improvement opportunities for frequent diseases and situations encountered in the ED, and to communicate effectively about patient treatment strategies.

Background: The diagnosis of tuberculous pleural effusion (TPE) often relies on pleural fluid adenosine deaminase (ADA) levels. The diagnostic utility of ADA, however, is influenced by the prevalence of tuberculosis (TB) in local populations. Malignant pleural effusion (MPE) cases can exhibit moderately elevated ADA levels comparable to those seen in TPE. As population aging potentially impacts ADA levels, global TB incidence is decreasing whereas the burden of malignancy is on the rise. Consequently, epidemiological shifts and temporal changes in ADA distribution complicate the differential diagnosis between TPE and MPE when ADA levels are within the 40–70 IU/L range. Nonetheless, data specific to this subset are scarce. Methods: This retrospective study included consecutive patients aged > 18 years with confirmed TPE and MPE, spanning from 2012 to 2023. ADA levels in pleural fluid were categorized into three groups: < 40 IU/L, 40–70 IU/L, and > 70 IU/L. The study examined annual trends in the frequency of new cases and ADA level distributions over time and identified discriminating factors between TPE and MPE in cases with ADA levels of 40–70 IU/L. Results: In total, 297 TPE and 369 MPE cases were included in this study. Over the study period, the frequency of TPE progressively declined, while that of MPE increased. In the most recent four-year period, new TPE and MPE cases with ADA levels of 40–70 IU/L occurred at comparable numbers. Multivariable analysis identified pleural fluid carcinoembryonic antigen (CEA) levels and the number of focal pleural nodules as independent predictors for MPE. Specifically, the presence of either CEA levels > 15.7 ng/mL or more than eight pleural nodules yielded the highest diagnostic accuracy with a sensitivity of 88%, specificity of 100%, and an area under the curve of 0.95. Conclusion The differential diagnosis between TPE and MPE with pleural ADA levels of 40–70 IU/L has become increasingly critical due to evolving epidemiological patterns and ADA distribution changes over time. Pleural fluid CEA levels and the characteristics of pleural nodules may offer valuable guidance in distinguishing between TPE and MPE within this diagnostic gray zone.

Purpose: To evaluate the compatibility and usability of test results obtained from the IDRA and Keratograph 5M in clinical settings by comparing their performance in patients with dry eye disease. Methods: From December 27 to 30, 2022, a study was conducted on 30 patients diagnosed with dry eye utilizing both the Keratograph 5M and IDRA devices. The parameters compared and analyzed included lipid layer thickness, tear meniscus height, tear film break-up time, and meibography. A paired t-test was used for statistical comparison. The lipid layer thickness in the Keratograph 5M was graded on a scale from 0 to 4 based on thickness. Results: No significant differences were found between the two devices in tear film break-up time, tear meniscus height, and meibography (p = 0.148, 0.072, 0.124, respectively). However, the tear lipid layer thickness measured by IDRA showed a proportional relationship with the grade assigned by the Keratograph 5M (Kendall R = 0.217, p = 0.037; Spearman R = 0.260, p = 0.045). Conclusions The IDRA device offers the advantage of performing multiple dry eye tests; simultaneously, thereby saving time compared to the Keratograph 5M. Both devices can be used compatibly with IDRA particularly advantageous for providing a numerical value for tear lipid layer thickness which enhances the convenience of dry eye diagnosis and treatment.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Purpose: In Korea, the Act on Hospice and Palliative Care and Decisions on Life-Sustaining Treatment (LST) was implemented on February 4, 2018. We aimed to investigate relevant factors and clinical changes associated with LST decisions after law enforcement. Materials and Methods: This single-center retrospective study included patients who completed LST documents using legal forms at Asan Medical Center from February 5, 2018, to June 30, 2020. Results: 5,896 patients completed LST documents, of which 2,704 (45.8%) signed the documents in person, while family members of 3,192 (54%) wrote the documents on behalf of the patients. Comparing first year and following year of implementation of the act, the self-documentation rate increased (43.9% to 47.2%, p=0.014). Moreover, the number of LST decisions made during or after intensive care unit admission decreased (37.8% vs. 35.2%, p=0.045), and the completion rate of LST documents during chemotherapy increased (6.6% vs. 8.9%, p=0.001). In multivariate analysis, age < 65 (odds ratio [OR], 1.724; 95% confidence interval [CI], 1.538 to 1.933; p < 0.001), unmarried status (OR, 1.309; 95% CI, 1.097 to 1.561; p=0.003), palliative care consultation (OR, 1.538; 95% CI, 1.340 to 1.765; p < 0.001), malignancy (OR, 1.864; 95% CI, 1.628 to 2.133; p < 0.001), and changes in timing on the first year versus following year (OR, 1.124; 95% CI, 1.003 to 1.260; p=0.045) were related to a higher self-documentation rate. Conclusion Age < 65 years, unmarried status, malignancy, and referral to a palliative care team were associated with patients making LST decisions themselves. Furthermore, the subject and timing of LST decisions have changed with the LST act.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

This study aimed to derive insights into professional self-concept, teamwork, and job satisfaction among emergency department (ED) nurses and to prepare basic data for improving job satisfaction among ED nurses. Methods: The study was conducted between October 2023 and April 2024 at two certified tertiary hospitals and one general hospital in Gyeonggi-do, Korea, among 124 ED nurses. Data were analyzed using SPSS version 26.0, and the analysis included descriptive statistics, the t-test, Pearson correlation, and multiple regression. Results: The factors affecting job satisfaction in ED nurses were professional self-concept (β = .66, p < .001), teamwork (β = .17, p = .003), and ED work satisfaction (β = .17, p = .003), and the overall explanatory power of the model was 67.7%. Conclusion: This study makes a significant contribution by demonstrating that professional self-concept and teamwork can increase job satisfaction in ED nurses. Therefore, as a strategy to increase job satisfaction through improving ED nurses’ professional self-concept and teamwork, effort should be made to apply team simulation programs that provide education and self-improvement opportunities for frequent diseases and situations encountered in the ED, and to communicate effectively about patient treatment strategies.

Background: The diagnosis of tuberculous pleural effusion (TPE) often relies on pleural fluid adenosine deaminase (ADA) levels. The diagnostic utility of ADA, however, is influenced by the prevalence of tuberculosis (TB) in local populations. Malignant pleural effusion (MPE) cases can exhibit moderately elevated ADA levels comparable to those seen in TPE. As population aging potentially impacts ADA levels, global TB incidence is decreasing whereas the burden of malignancy is on the rise. Consequently, epidemiological shifts and temporal changes in ADA distribution complicate the differential diagnosis between TPE and MPE when ADA levels are within the 40–70 IU/L range. Nonetheless, data specific to this subset are scarce. Methods: This retrospective study included consecutive patients aged > 18 years with confirmed TPE and MPE, spanning from 2012 to 2023. ADA levels in pleural fluid were categorized into three groups: < 40 IU/L, 40–70 IU/L, and > 70 IU/L. The study examined annual trends in the frequency of new cases and ADA level distributions over time and identified discriminating factors between TPE and MPE in cases with ADA levels of 40–70 IU/L. Results: In total, 297 TPE and 369 MPE cases were included in this study. Over the study period, the frequency of TPE progressively declined, while that of MPE increased. In the most recent four-year period, new TPE and MPE cases with ADA levels of 40–70 IU/L occurred at comparable numbers. Multivariable analysis identified pleural fluid carcinoembryonic antigen (CEA) levels and the number of focal pleural nodules as independent predictors for MPE. Specifically, the presence of either CEA levels > 15.7 ng/mL or more than eight pleural nodules yielded the highest diagnostic accuracy with a sensitivity of 88%, specificity of 100%, and an area under the curve of 0.95. Conclusion The differential diagnosis between TPE and MPE with pleural ADA levels of 40–70 IU/L has become increasingly critical due to evolving epidemiological patterns and ADA distribution changes over time. Pleural fluid CEA levels and the characteristics of pleural nodules may offer valuable guidance in distinguishing between TPE and MPE within this diagnostic gray zone.