This study investigated the plaque removal efficacy of a suction-type sonic toothbrush compared to a conventional manual toothbrush in preschool children aged 30 to 59 months. Using a randomized, double-blind, crossover design with a 2-week washout period, 20 pediatric participants were allocated to two study phases, each using either the suction-type sonic toothbrush or the manual toothbrush with caregiver assistance. The plaque removal effectiveness was assessed through the Silness and Löe plaque index and quantitative light-induced fluorescence values, including ΔR30 and ΔR120 indicators of plaque index. The result showed no statistically significant differences in plaque removal efficacy between the two toothbrushes, although both showed similar improvements. Caregiver feedback revealed high acceptability of the suction-type sonic toothbrush due to its convenience and engaging features, such as a light and suction function, which enhanced the tooth brushing experience. Although limited by the short follow-up period and small sample size, the findings suggest that suction-type sonic toothbrushes may offer practical benefits for young children requiring caregiver assistance.

Mammography is the standard screening method for breast cancer, proven to reduce mortality. However, its diagnostic performance varies depending on patient characteristics and radiologist expertise. Dense breast tissue, present in approximately 70% of Korean women aged 40 to 59, limits detection by obscuring malignancies. Additionally, optimal interpretation requires extensive training, which is not always achievable. Artificial intelligence-based computer-aided diagnosis (AI-CAD) has emerged as a promising tool for enhancing mammographic accuracy and efficiency.Current Concepts: AI-CAD has shown diagnostic performance comparable to that of experienced radiologists while addressing the limitations of traditional CAD systems, particularly excessive false positives. Studies suggest AI-CAD improves radiologists' accuracy, particularly among those with limited breast imaging experience. In Europe, AI-assisted reading is increasingly recognized as a viable alternative to traditional double reading. In Korea, adoption of AI-CAD is expanding, with systems approved by the Korean Food and Drug Administration currently in clinical use. Recently, one AI-CAD system received conditional non-reimbursement designation, allowing hospitals to use it for up to 5 years while collecting clinical evidence to support future insurance coverage decisions.Discussion and Conclusion: AI-CAD has significant potential to enhance early breast cancer detection while maintaining acceptable false-positive rates, making it a valuable adjunct in screening programs. Beyond improved detection, AI-CAD may optimize workflow efficiency by triaging cases and prioritizing high-risk examinations. However, its integration into clinical practice necessitates standardized guidelines, regulatory oversight, and further validation through large-scale prospective studies. As AI technology continues to advance, ongoing investigation into its role in personalized breast cancer screening is essential.

Accessory breast tissue can appear along the mammary ridge, extending from the axilla to the groin, with the axilla being the most common site. Malignancies arising in accessory breast tissue are rare, representing approximately 0.3%–0.6% of all breast cancer cases.When evaluating accessory breasts, it is essential to apply the same management strategies used for conventionally positioned breasts. This report presents a case of ductal carcinoma in situ originating from accessory breast tissue in the axilla of a 55-year-old woman. The diagnosis was established through a comprehensive assessment involving mammography, ultrasound, and magnetic resonance imaging. Since the axillary accessory breast tissue wasn’t initially included in the routine mammography, we added an axillary tail view to evaluate the extent and morphology of malignant microcalcifications.

Purpose: This concept analysis aimed to deepen the understanding of Quiet Quitting among nurses by identifying its antecedents, defining attributes, and consequences. Methods: This study employed Walker and Avant’s conceptual analysis framework. Results: Quiet Quitting among nurses is defined as “a state in which individuals pursue harmony between their work and personal lives by performing only the minimum required tasks, rejecting workplace initiatives, and expressing passive resistance to organizational and job dissatisfaction.” Key antecedents include “fatigue resulting from changes in the healthcare environment”, “lack of managerial competence”, “role stress”, “toxic organizational culture”, “financial problem” and “Generation Z’s evolving perspective on work”. The analysis highlight five primary concerns: a decline in nursing care quality, increased likelihood of job turnover, conflicts with colleagues and supervisors, reduced job satisfaction, and a diminished personal competency. Conclusion This study provides a clear definition of Quiet Quitting among nurses and establishes a theoretical basis for addressing the issue.Additionally, it underscores the need for further research, including the development of measurement tools, to better understand and mitigate this phenomenon.

This study aimed to identify factors influencing treatment compliance in Korean patients undergoing percutaneous coronary intervention. Methods: The study included 130 patients who underwent percutaneous coronary intervention at St. Carollo Hospital. Data were collected using self-administered questionnaires from March 21, 2022 to May 30, 2023, and analyzed using descriptive statistics, the t-test, analysis of variance, the Scheffé test, Pearson correlation coefficients, and multiple regression in SPSS version 26.0. Results: Resilience (β = .59, p < .001), alcohol drinking (β = −.18, p = .005), and the diagnosis (β = .13, p = .040) accounted for 45.0% of the variance in treatment compliance in patients undergoing percutaneous coronary intervention. Conclusion: These results indicate that it is necessary to explore strategies for developing and implementing programs that can effectively enhance resilience in patients who have undergone percutaneous coronary intervention.

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 aimed to perform a genome characterization of Streptococcus mitis KHUD 011, a strain isolated from the oral microbiome of a healthy Korean individual, and to compare its genomic features with other S. mitis strains. Materials and Methods: The strain was identified through 16S rRNA gene sequencing, and its genome was sequenced using the PacBio Sequel II platform. De novo assembly and annotation were performed, followed by comparative genomic analysis with three additional strains (S. mitis NCTC 12261, S022-V3-A4, and B6). Pan-genome and phylogenetic analyses were conducted to identify strain-specific genes and assess inter-strain genomic diversity. Results: The genome of S. mitis KHUD 011 consisted of 1,782 protein-coding genes, with a G+C content of 40.24%. Pan-genome analysis identified 1,263 core gene clusters (50.0%), 496 dispensable clusters (19.7%), and 763 strain-specific clusters (30.3%). KHUD 011 displayed 88 strain-specific genes, particularly associated with cell wall/membrane biogenesis, transcriptional regulation, and carbohydrate metabolism. Phylogenetic analysis placed KHUD 011 closely with NCTC 12261, forming a distinct cluster apart from other strains. Conclusion The genome characterization of S. mitis KHUD 011 underscores substantial inter-strain genomic diversity influenced by host interactions, ecological niches, and health status. The identified strain-specific genes, particularly those associated with cell wall/ membrane biogenesis, transcriptional regulation, and carbohydrate metabolism, suggest adaptations to the oral microbiome and its interaction with the host. These findings highlight the ecological versatility of S. mitis and the importance of exploring strains from diverse environments to better understand their role within the host and the broader microbiome.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Purpose: This concept analysis aimed to deepen the understanding of Quiet Quitting among nurses by identifying its antecedents, defining attributes, and consequences. Methods: This study employed Walker and Avant’s conceptual analysis framework. Results: Quiet Quitting among nurses is defined as “a state in which individuals pursue harmony between their work and personal lives by performing only the minimum required tasks, rejecting workplace initiatives, and expressing passive resistance to organizational and job dissatisfaction.” Key antecedents include “fatigue resulting from changes in the healthcare environment”, “lack of managerial competence”, “role stress”, “toxic organizational culture”, “financial problem” and “Generation Z’s evolving perspective on work”. The analysis highlight five primary concerns: a decline in nursing care quality, increased likelihood of job turnover, conflicts with colleagues and supervisors, reduced job satisfaction, and a diminished personal competency. Conclusion This study provides a clear definition of Quiet Quitting among nurses and establishes a theoretical basis for addressing the issue.Additionally, it underscores the need for further research, including the development of measurement tools, to better understand and mitigate this phenomenon.