Purpose: This study was conducted to update the practice guidelines for intravenous infusion therapy published in 2017, focusing on the most recent evidence for peripheral intravenous infusion therapy. Methods: The guideline update was conducted using the 22-step methodology. Results: The updated guidelines consist of 17 domains and 235 recommendations (including 284 sub-recommendations). The domains are as follows: general instructions (5 items), peripheral catheter selection (7), catheter insertion site selection (11), management during peripheral catheter insertion (10), post-insertion management (30), perfusion and locking (17), blood sampling via peripheral catheters(6), exchange and removal of peripheral catheters (6), infusion set management (14), add-on devices (32), complications (25), chemotherapy infusions (10), PCA infusions (7), parenteral nutrition (20), transfusion therapy (23), education (5), and documentation and reporting (7). The evidence levels for these recommendations are as follows: 27(9.5%) at level I, 3 (1.1%) at level I A/P, 118 (41.5%) at level II, and 136 (47.9%) at level III.Recommendation grades are categorized as follows: 30 (10.6%) at level A, 118 (41.5%) at level B, and 136(47.9%) at level C. Of these, 73 (25.7%) recommendations were newly developed, 49 (17.3%) underwent major revisions, and 147 (51.7%) underwent minor revisions. Conclusion The updated practice guideline, based on the latest evidence, is anticipated to enhance nursing practice related to peripheral intravenous infusion therapy.

Purpose: This study was conducted to update the practice guidelines for intravenous infusion therapy published in 2017, focusing on the most recent evidence for peripheral intravenous infusion therapy. Methods: The guideline update was conducted using the 22-step methodology. Results: The updated guidelines consist of 17 domains and 235 recommendations (including 284 sub-recommendations). The domains are as follows: general instructions (5 items), peripheral catheter selection (7), catheter insertion site selection (11), management during peripheral catheter insertion (10), post-insertion management (30), perfusion and locking (17), blood sampling via peripheral catheters(6), exchange and removal of peripheral catheters (6), infusion set management (14), add-on devices (32), complications (25), chemotherapy infusions (10), PCA infusions (7), parenteral nutrition (20), transfusion therapy (23), education (5), and documentation and reporting (7). The evidence levels for these recommendations are as follows: 27(9.5%) at level I, 3 (1.1%) at level I A/P, 118 (41.5%) at level II, and 136 (47.9%) at level III.Recommendation grades are categorized as follows: 30 (10.6%) at level A, 118 (41.5%) at level B, and 136(47.9%) at level C. Of these, 73 (25.7%) recommendations were newly developed, 49 (17.3%) underwent major revisions, and 147 (51.7%) underwent minor revisions. Conclusion The updated practice guideline, based on the latest evidence, is anticipated to enhance nursing practice related to peripheral intravenous infusion therapy.

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.

Background/Aims: Studies on the clinical outcomes after detecting low-grade dysplasia (LGD) in patients with inflammatory bowel disease (IBD) are insufficient. This study evaluated the clinical features, frequency, and risk factors for advanced neoplasia in patients with IBD after an LGD diagnosis. Methods: The medical records of 166 patients with IBD from six university hospitals in Korea from 2010 to 2019 were reviewed retrospectively. LGD was diagnosed in all patients during surveillance. The frequency and risk factors for advanced neoplasia were evaluated, and the clinical features of patients with and without advanced neoplasia were compared. Results: Advanced neoplasia developed in 12 patients (six with large LGD, three with tubulovillous adenoma, and three with high-grade dysplasia), and all cases developed from UC. Patients with advanced neoplasia had significantly higher Mayo scores, and colitis-associated dysplasia was more common than sporadic lesions (83.3% vs. 29.9%; p<0.001). Multivariate analysis showed that colitis-associated LGD significantly increased the risk of developing advanced neoplasia (odds ratio [OR], 10.516; 95% confidence interval [CI], 2.064–53.577). Among patients with colitis-associated lesions, a significant risk factor for advanced neoplasia was a prior history of LGD (OR, 9.429; 95% CI, 1.330–66.863). Conclusions Advanced neoplasia developed in 7.2% of patients with IBD and LGD. Most advanced neoplasms developed from colitis-associated lesions, and the risk was higher in patients with a history of LGD before index colonoscopy.

Background and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

Background/Aims: The Korean guidelines for Helicobacter pylori treatment were revised in 2020, however, the extent of adherence to these guidelines in clinical practice remains unclear. Herein, we initiated a prospective, nationwide, multicenter registry study in 2021 to evaluate the current management of H.pylori infection in Korea. Methods: This interim report describes the adherence to the revised guidelines and their impact on firstline eradication rates. Data on patient demographics, diagnoses, treatments, and eradication outcomes were collected using a web-based electronic case report form. Results: A total of 7,261 patients from 66 hospitals who received first-line treatment were analyzed.The modified intention-to-treat eradication rate for first-line treatment was 81.0%, with 80.4% of the prescriptions adhering to the revised guidelines. The most commonly prescribed regimen was the 14-day clarithromycin-based triple therapy (CTT; 42.0%), followed by tailored therapy (TT; 21.2%), 7-day CTT (14.1%), and 10-day concomitant therapy (CT; 10.1%). Time-trend analysis demonstrated significant increases in guideline adherence and the use of 10-day CT and TT, along with a decrease in the use of 7-day CTT (all p<0.001). Multivariate logistic regression analysis revealed that guideline adherence was significantly associated with first-line eradication success (odds ratio, 2.03; 95% confidence interval, 1.61 to 2.56; p<0.001). Conclusions The revised guidelines for the treatment of H. pylori infection have been increasingly adopted in routine clinical practice in Korea, which may have contributed to improved first-line eradication rates. Notably, the 14-day CTT, 10-day CT, and TT regimens are emerging as the preferred first-line treatment options among Korean physicians.

Objective: Several miRNAs have been identified as differentially expressed in patients with poor ovarian response (POR) compared to those with normal responses. This study aims to assess the potential of serum miR-329-3p as a biomarker for diagnosing POR. Methods: We conducted a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to confirm the target genes of miR-329-3p. KGN cells were transfected with both miR-329-3p mimic and inhibitor to assess the differential expression of these target genes. In accordance with the Bologna criteria, we enrolled 16 control patients and 16 patients with POR. We collected patient samples, including serum from day 2 and the human chorionic gonadotropin (hCG) day, as well as granulosa and cumulus cells, to validate the expression of miR-329-3p using quantitative real-time polymerase chain reaction. Results: KEGG pathway analysis revealed that miR-329-3p targeted adenylyl cyclase 9 (ADCY9) and protein kinase A subunit beta (PRKACB), both of which are involved in ovarian steroidogenesis. In KGN cells treated with a miR-329-3p mimic, ADCY9 and PRKACB expression levels were significantly reduced (p<0.05). Elevated levels of miR-329-3p suppressed aromatase expression and 17β-estradiol production by modulating ADCY9 and PRKACB in KGN cells. These effects were also observed in POR patients. Follicle-stimulating hormone receptor (FSHR) expression was diminished in the granulosa cells of POR patients. On day 2, on hCG day, and in granulosa cells, miR-329-3p exhibited high expression levels in the serum of POR patients. Conclusion miR-329-3p exhibited increased expression in granulosa cells and in the sera of POR patients. Consequently, we propose that miR-329-3p may be a potential biomarker for the diagnosis of POR.

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.

Background/Aims: Studies on the clinical outcomes after detecting low-grade dysplasia (LGD) in patients with inflammatory bowel disease (IBD) are insufficient. This study evaluated the clinical features, frequency, and risk factors for advanced neoplasia in patients with IBD after an LGD diagnosis. Methods: The medical records of 166 patients with IBD from six university hospitals in Korea from 2010 to 2019 were reviewed retrospectively. LGD was diagnosed in all patients during surveillance. The frequency and risk factors for advanced neoplasia were evaluated, and the clinical features of patients with and without advanced neoplasia were compared. Results: Advanced neoplasia developed in 12 patients (six with large LGD, three with tubulovillous adenoma, and three with high-grade dysplasia), and all cases developed from UC. Patients with advanced neoplasia had significantly higher Mayo scores, and colitis-associated dysplasia was more common than sporadic lesions (83.3% vs. 29.9%; p<0.001). Multivariate analysis showed that colitis-associated LGD significantly increased the risk of developing advanced neoplasia (odds ratio [OR], 10.516; 95% confidence interval [CI], 2.064–53.577). Among patients with colitis-associated lesions, a significant risk factor for advanced neoplasia was a prior history of LGD (OR, 9.429; 95% CI, 1.330–66.863). Conclusions Advanced neoplasia developed in 7.2% of patients with IBD and LGD. Most advanced neoplasms developed from colitis-associated lesions, and the risk was higher in patients with a history of LGD before index colonoscopy.

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.