Background/Aims: Although gastrointestinal endoscopy (GIE) is a major contributor to the carbon footprint of national healthcare, the amount of medical waste generated by GIE procedures is not reported in South Korea. This study aimed to measure the amount of medical waste generated from GIE procedures in South Korea. Methods: We conducted a 5-day audit of medical waste generated during GIEs at seven hospitals. During the study period, medical waste in the endoscopy examination rooms was measured twice daily and documented as mass (kg). To calculate the mean mass of disposable waste generated during one esophagogastroduodenoscopy (EGD) and one colonoscopy, the mean mass of medical waste generated from seven examinations was calculated. The mean mass of medical waste generated during GIEs was calculated by dividing the total mass of medical waste generated by the number of GIE procedures. Results: Overall, 3,922 endoscopies were performed and 4,558 kg of waste was generated. The mean weight of medical waste generated per endoscopy was 1.34 kg. Each EGD and colonoscopy generated a mean of 0.24 kg and 0.43 kg of disposable waste, respectively. Applying the mean waste estimates from this study to annual GIE procedures performed in South Korea in 2022 showed that the total medical waste produced from GIE was 13,704,453 kg. In addition, the total masses of medical waste produced during EGD and colonoscopy procedures were 819,766 kg and 2,889,478 kg, respectively. Conclusions Our quantitative measurement showed that a large amount of medical waste is generated from GIE procedures. However, further research is warranted to reduce medical waste generated during GIE, which is an urgent unmet need.

Background/Aims: Although gastrointestinal endoscopy (GIE) is a major contributor to the carbon footprint of national healthcare, the amount of medical waste generated by GIE procedures is not reported in South Korea. This study aimed to measure the amount of medical waste generated from GIE procedures in South Korea. Methods: We conducted a 5-day audit of medical waste generated during GIEs at seven hospitals. During the study period, medical waste in the endoscopy examination rooms was measured twice daily and documented as mass (kg). To calculate the mean mass of disposable waste generated during one esophagogastroduodenoscopy (EGD) and one colonoscopy, the mean mass of medical waste generated from seven examinations was calculated. The mean mass of medical waste generated during GIEs was calculated by dividing the total mass of medical waste generated by the number of GIE procedures. Results: Overall, 3,922 endoscopies were performed and 4,558 kg of waste was generated. The mean weight of medical waste generated per endoscopy was 1.34 kg. Each EGD and colonoscopy generated a mean of 0.24 kg and 0.43 kg of disposable waste, respectively. Applying the mean waste estimates from this study to annual GIE procedures performed in South Korea in 2022 showed that the total medical waste produced from GIE was 13,704,453 kg. In addition, the total masses of medical waste produced during EGD and colonoscopy procedures were 819,766 kg and 2,889,478 kg, respectively. Conclusions Our quantitative measurement showed that a large amount of medical waste is generated from GIE procedures. However, further research is warranted to reduce medical waste generated during GIE, which is an urgent unmet need.

Background/Aims: Although gastrointestinal endoscopy (GIE) is a major contributor to the carbon footprint of national healthcare, the amount of medical waste generated by GIE procedures is not reported in South Korea. This study aimed to measure the amount of medical waste generated from GIE procedures in South Korea. Methods: We conducted a 5-day audit of medical waste generated during GIEs at seven hospitals. During the study period, medical waste in the endoscopy examination rooms was measured twice daily and documented as mass (kg). To calculate the mean mass of disposable waste generated during one esophagogastroduodenoscopy (EGD) and one colonoscopy, the mean mass of medical waste generated from seven examinations was calculated. The mean mass of medical waste generated during GIEs was calculated by dividing the total mass of medical waste generated by the number of GIE procedures. Results: Overall, 3,922 endoscopies were performed and 4,558 kg of waste was generated. The mean weight of medical waste generated per endoscopy was 1.34 kg. Each EGD and colonoscopy generated a mean of 0.24 kg and 0.43 kg of disposable waste, respectively. Applying the mean waste estimates from this study to annual GIE procedures performed in South Korea in 2022 showed that the total medical waste produced from GIE was 13,704,453 kg. In addition, the total masses of medical waste produced during EGD and colonoscopy procedures were 819,766 kg and 2,889,478 kg, respectively. Conclusions Our quantitative measurement showed that a large amount of medical waste is generated from GIE procedures. However, further research is warranted to reduce medical waste generated during GIE, which is an urgent unmet need.

Background/Aims: Although gastrointestinal endoscopy (GIE) is a major contributor to the carbon footprint of national healthcare, the amount of medical waste generated by GIE procedures is not reported in South Korea. This study aimed to measure the amount of medical waste generated from GIE procedures in South Korea. Methods: We conducted a 5-day audit of medical waste generated during GIEs at seven hospitals. During the study period, medical waste in the endoscopy examination rooms was measured twice daily and documented as mass (kg). To calculate the mean mass of disposable waste generated during one esophagogastroduodenoscopy (EGD) and one colonoscopy, the mean mass of medical waste generated from seven examinations was calculated. The mean mass of medical waste generated during GIEs was calculated by dividing the total mass of medical waste generated by the number of GIE procedures. Results: Overall, 3,922 endoscopies were performed and 4,558 kg of waste was generated. The mean weight of medical waste generated per endoscopy was 1.34 kg. Each EGD and colonoscopy generated a mean of 0.24 kg and 0.43 kg of disposable waste, respectively. Applying the mean waste estimates from this study to annual GIE procedures performed in South Korea in 2022 showed that the total medical waste produced from GIE was 13,704,453 kg. In addition, the total masses of medical waste produced during EGD and colonoscopy procedures were 819,766 kg and 2,889,478 kg, respectively. Conclusions Our quantitative measurement showed that a large amount of medical waste is generated from GIE procedures. However, further research is warranted to reduce medical waste generated during GIE, which is an urgent unmet need.

Objective: To compare the outcomes of digital breast tomosynthesis (DBT) screening combined with ultrasound (US) with those of digital mammography (DM) combined with US in women with dense breasts. Materials and Methods: A retrospective database search identified consecutive asymptomatic women with dense breasts who underwent breast cancer screening with DBT or DM and whole-breast US simultaneously between June 2016 and July 2019. Women who underwent DBT + US (DBT cohort) and DM + US (DM cohort) were matched using 1:2 ratio according to mammographic density, age, menopausal status, hormone replacement therapy, and a family history of breast cancer. The cancer detection rate (CDR) per 1000 screening examinations, abnormal interpretation rate (AIR), sensitivity, and specificity were compared. Results: A total of 863 women in the DBT cohort were matched with 1726 women in the DM cohort (median age, 53 years; interquartile range, 40–78 years) and 26 breast cancers (9 in the DBT cohort and 17 in the DM cohort) were identified. The DBT and DM cohorts showed comparable CDR (10.4 [9 of 863; 95% confidence interval {CI}: 4.8–19.7] vs. 9.8 [17 of 1726;95% CI: 5.7–15.7] per 1000 examinations, respectively; P = 0.889). DBT cohort showed a higher AIR than the DM cohort (31.6% [273 of 863; 95% CI: 28.5%–34.9%] vs. 22.4% [387 of 1726; 95% CI: 20.5%–24.5%]; P < 0.001). The sensitivity for both cohorts was 100%. In women with negative findings on DBT or DM, supplemental US yielded similar CDRs in both DBT and DM cohorts (4.0 vs. 3.3 per 1000 examinations, respectively; P = 0.803) and higher AIR in the DBT cohort (24.8% [188 of 758; 95% CI: 21.8%–28.0%] vs. 16.9% [257 of 1516; 95% CI: 15.1%–18.9%; P < 0.001). Conclusion DBT screening combined with US showed comparable CDR but lower specificity than DM screening combined with US in women with dense breasts.

Objective: To conduct a simulation study to determine whether artificial intelligence (AI)-aided mammography reading can reduce unnecessary recalls while maintaining cancer detection ability in women recalled after mammography screening. Materials and Methods: A retrospective reader study was performed by screening mammographies of 793 women (mean age ± standard deviation, 50 ± 9 years) recalled to obtain supplemental mammographic views regarding screening mammographydetected abnormalities between January 2016 and December 2019 at two screening centers. Initial screening mammography examinations were interpreted by three dedicated breast radiologists sequentially, case by case, with and without AI aid, in a single session. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and recall rate for breast cancer diagnosis were obtained and compared between the two reading modes. Results: Fifty-four mammograms with cancer (35 invasive cancers and 19 ductal carcinomas in situ) and 739 mammograms with benign or negative findings were included. The reader-averaged AUC improved after AI aid, from 0.79 (95% confidence interval [CI], 0.74–0.85) to 0.89 (95% CI, 0.85–0.94) (p < 0.001). The reader-averaged specificities before and after AI aid were 41.9% (95% CI, 39.3%–44.5%) and 53.9% (95% CI, 50.9%–56.9%), respectively (p < 0.001). The reader-averaged sensitivity was not statistically different between AI-unaided and AI-aided readings: 89.5% (95% CI, 83.1%–95.9%) vs.92.6% (95% CI, 86.2%–99.0%) (p = 0.053), although the sensitivities of the least experienced radiologists before and after AI aid were 79.6% (43 of 54 [95% CI, 66.5%–89.4%]) and 90.7% (49 of 54 [95% CI, 79.7%–96.9%]), respectively (p = 0.031). With AI aid, the reader-averaged recall rate decreased by from 60.4% (95% CI, 57.8%–62.9%) to 49.5% (95% CI, 46.5%–52.4%) (p < 0.001). Conclusion AI-aided reading reduced the number of recalls and improved the diagnostic performance in our simulation using women initially recalled for supplemental mammographic views after mammography screening.

Background: This study was performed to evaluate etiologies and secular trends in primary amenorrhea in South Korea. Methods: This retrospective multi-center study analyzed 856 women who were diagnosed with primary amenorrhea between 2000 and 2016. Clinical characteristics were compared according to categories of amenorrhea (hypergonadotropic/hypogonadotropic hypogonadism, eugonadism, disorders of sex development) or specific causes of primary amenorrhea. In addition, we assessed secular trends of etiology and developmental status based on the year of diagnosis. Results: The most frequent etiology was eugonadism (39.8%). Among specific causes, Müllerian agenesis was most common (26.2%), followed by gonadal dysgenesis (22.4%). Women with hypergonadotropic hypogonadism were more likely to have lower height and weight, compared to other categories. In addition, the proportion of cases with iatrogenic or unknown causes increased significantly in hypergonadotropic hypogonadism category, but overall, no significant secular trends were detected according to etiology. The proportion of anovulation including polycystic ovarian syndrome increased with time, but the change did not reach statistical significance. Conclusion The results of this study provide useful clinical insight on the etiology and secular trends of primary amenorrhea. Further large-scale, prospective studies are necessary.

Objective: This study was to evaluate the effectiveness of an individually tailored program based on self-measurement of blood glucose on health behavior and HbA1c in diabetes and pre-diabetes patients. Methods: The program consisted of seven sessions for 12 weeks which were carried out every two weeks. Almost all sessions were progressed on untact method except for the first and last session. The 71 subjects were assessed for their knowledge of diabetes, health behavior, the experience of self-measurement of blood glucose, body mass Index (BMI) and hemoglobin A1c (HbA1c) at before and after the program. They were also evaluated on their degree of utilization of blood glucose measurements after the program. Results: Each mean score on their knowledge of diabetes, health behavior and the experience of self-measurement of blood glucose was significantly increased from 14.77, 25.50, and 2.70 to 15.41, 28.40, and 4.81, respectively. Each mean score on both BMI and HbA1c (n=53) was significantly decreased from 24.47kg/m2 and 7.27% to 24.01kg/m2 and 6.67%, respectively. The post-HbA1c had a significant negative correlation(r=-0.415) with the degree of utilization of blood glucose measurements. The degree of utilization of blood glucose measurements had a significant positive correlation(r=0.581) with post-health behavior. Conclusions The program shows effectiveness in improving HbA1c in Type 2 diabetes and pre-diabetes patients. The post-HbA1c might be related to the degree of utilization of blood glucose measurements which might be related to the health behavior.

Background: Remdesivir is widely used for the treatment of coronavirus disease 2019 (COVID-19), but controversies regarding its efficacy still remain. Methods: A retrospective cohort study was conducted to evaluate the effect of remdesivir on clinical and virologic outcomes of severe COVID-19 patients from June to July 2020. Primary clinical endpoints included clinical recovery, additional mechanical ventilator (MV) support, and duration of oxygen or MV support. Viral load reduction by hospital day (HD) 15 was evaluated by calculating changes in cycle threshold (Ct) values. Results: A total of 86 severe COVID-19 patients were evaluated including 48 remdesivirtreated patients. Baseline characteristics were not significantly different between the two groups. Remdesivir was administered an average of 7.42 days from symptom onset. The proportions of clinical recovery of the remdesivir and supportive care group at HD 14 (56.3% and 39.5%) and HD 28 (87.5% and 78.9%) were not statistically different. The proportion of patients requiring MV support by HD 28 was significantly lower in the remdesivir group than in the supportive care group (22.9% vs. 44.7%, P = 0.032), and MV duration was significantly shorter in the remdesivir group (average, 1.97 vs. 5.37 days; P = 0.017). Analysis of upper respiratory tract specimens demonstrated that increases of Ct value from HD 1–5 to 11–15 were significantly greater in the remdesivir group than the supportive care group (average, 10.19 vs. 5.36; P = 0.007), and the slope of the Ct value increase was also significantly steeper in the remdesivir group (average, 5.10 vs. 2.68; P = 0.007). Conclusion The remdesivir group showed clinical and virologic benefit in terms of MV requirement and viral load reduction, supporting remdesivir treatment for severe COVID-19.

Purpose: To compare the recurrence pattern, disease-free survival (DFS), and overall survival (OS) after curative surgery for pancreatic ductal adenocarcinoma (PDAC) in patients who underwent preoperative evaluation with CT alone or in combination with MRI, and to compare the prognosis according to the first recurrence site. Materials and Methods: We retrospectively evaluated 152 patients who underwent R0 resection of PDAC. Preoperative CT or combined CT and MRI were performed for 103 and 49 patients, respectively. Two radiologists recorded the location and date of the first recurrence in consensus. The recurrence pattern, DFS, and OS were compared between the two groups. OS was analyzed according to the first recurrence site. Results: In both groups, liver metastasis was the most common recurrence pattern. DFS (p = 0.247) or OS (p = 0.067) showed no significant difference between the two groups. OS according to the first recurrence site was the lowest for liver metastasis, followed by locoregional recurrence (p < 0.001). Conclusion There were no significant differences in the recurrence pattern, DFS, or OS between patients evaluated with preoperative CT alone or with CT and MRI after curative resection of PDAC. Liver metastasis was the most common tumor recurrence pattern with the lowest OS.