https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/930 Sat, 04 Jul 2026 04:00:01 GMT 2026-07-04T04:00:01Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213094 Title: Effects of nursing interventions for pressure injury prevention using real-time pressure mapping: a randomized controlled trial Authors: Shin, Yong-Soon; Kyung, Do-Eun; Park, So-Seul Abstract: Background Despite preventive nursing efforts, pressure injuries remain a significant clinical challenge, with a high incidence. The adoption of advanced technologies is therefore essential for more effective prevention. Aims To evaluate the effectiveness of real-time pressure mapping-based nursing interventions in preventing pressure injuries and improving caregiver outcomes. Methods A randomized controlled trial was conducted in which the intervention group received seven days of nursing care using real-time pressure mapping, allowing for safe, minimal repositioning based on real-time visual pressure distribution data and a nursing protocol.The control group received standard care. Skin condition was assessed three times daily, and caregiver burden and satisfaction were evaluated before and after the intervention. Results Sixty-eight participants completed the study. The intervention group demonstrated significantly lower pressure injury incidence and caregiver burden than the control group. Conclusions The findings support the use of real-time pressure mapping as an effective tool for preventing pressure injuries and suggest its broader applicability in intervention programs. Tue, 01 Dec 2026 00:00:00 GMT https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213094 2026-12-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212479 Title: Predictors and clinical outcomes associated with prolonged mechanical ventilation following major cardiac surgery Authors: Kang, Young Ae; Shin, Yong Soon Abstract: Background: Prolonged mechanical ventilation (PMV) after major cardiac surgery is associated with increased morbidity, mortality, and healthcare utilization. Objectives: To determine independent perioperative predictors of PMV and assess its impact on postoperative outcomes in cardiac surgical patients. Methods: This retrospective case-control study analyzed 1437 adults undergoing major cardiac surgery in 2022. PMV was defined as ventilation >24 h postoperatively. Multivariable logistic regression identified independent predictors; outcomes were adjusted using inverse probability of treatment weighting. Results: PMV occurred in 167 patients (11.6%). Independent preoperative predictors were mechanical ventilation (OR 5.632, 95% CI 1.208-26.262, P = 0.028) and urgent admission (OR 2.520, 95% CI 1.292-4.844, P = 0.007). Intraoperative predictors included prolonged cardiopulmonary bypass duration and aortic surgery. Postoperative factors associated with PMV were neurologic complications (OR 3.90, 95% CI 1.771-8.590, P = 0.001), acute kidney injury (OR 3.548, 95% CI 1.214-10.374, P = 0.021), transfusion volume (OR 1.043, 95% CI 1.016-1.071, P = 0.002), and continuous sedation duration (OR 1.038, 95% CI 1.026-1.050, P < 0.001). Delirium by Confusion Assessment Method - ICU was not significant (P = 0.053), whereas higher Numeric Rating Scale pain scores were inversely associated with PMV (OR 0.81, 95% CI 0.694-0.945, P = 0.008). PMV was linked to higher reintubation, higher ICU readmission, longer ICU stay (mean difference [MD] 7.4 d, P < 0.001), and extended hospitalization (MD 17.4 d, P < 0.001). Conclusions: PMV is associated with multiple modifiable perioperative factors and adverse outcomes. Early risk stratification and targeted preventive strategies may improve recovery and survival in this population. Tue, 01 Sep 2026 00:00:00 GMT https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212479 2026-09-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212754 Title: Effects of metaverse-based mock trials for nurses: A randomized controlled trial (vol 152, 106751, 2025) Authors: Yi, Yeojin; Lim, Haena; Hwang, Eunmi Abstract: The authors regret that the following typo is in the original text and should be corrected in this corrigendum: 1. Section 3.2.1: The clinical trial registration number is corrected to KCT0011865. 2. Table 2: The data rows for “Male” and “Female” in the Control and Experimental groups were reversed and are now corrected. These corrections do not affect the study design, methodology, results, interpretation, or conclusions of the article. The authors would like to apologise for any inconvenience caused. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. [Table presented] IM: internal medicine, NU: neurology, GS: general surgery, OB&GY: obstetrics & gynecology, ER: emergency room, Others: intensive care unit, pediatrics, psychiatry. Cont. = Control group. Exp. = Experimental group. Sat, 01 Aug 2026 00:00:00 GMT https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212754 2026-08-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212904 Title: Trait-environment diagnosis of ecological instability in Korean streams using benthic diatoms and machine learning: a UMAP-CDI framework Authors: Lee, Jun-Ho; Kim, Hyo Gyeom; Han, Byeong-Hun; Cho, In-Hwan; Kim, Ha-Kyung; Hwang, Eun-A.; Hwang, Su-Ok; Kim, Baik-Ho Abstract: This study presents a trait-integrated, multistressor-sensitive bioassessment framework that combines the Community Dynamics Index (CDI) and machine learning-based nonlinear ordination to quantify ecological instability in monsoon-impacted river systems. Using data encompassing benthic diatom species composition of 457 stream sites across five major Korean river basins (2013-2015), CDI values were calculated between pairs of sampling periods to capture both monsoon-related and longer-term community shifts. Among four ordination methods tested, uniform manifold approximation and projection (UMAP) most effectively resolved nonlinear transitions, outperforming principal component analysis (PCA) and nonmetric multidimensional scaling (NMDS) in silhouette width. Random forest modeling identified motility as a dominant predictor for UMAP-based CDI with monsoonal and non-monsoonal variations. Partial dependence plots indicated that changes in motility were strongly associated with variation in CDI during both monsoonal and non-monsoonal periods, with pronounced nonlinear responses across environmental gradients and distinct season-specific patterns. Functional analyses further indicated that this short-term instability was accompanied by a long-term shift from sensitive, low-profile taxa (e.g., Achnanthes spp.) to tolerant, motile taxa (e.g., Nitzschia or Navicula spp.). This integrated CDI-trait-UMAP approach enables scalable, ecologically interpretable, and nonlinearity-resolving assessment of river health. The framework can be extended to support international biomonitoring goals and offer early warning capacity for biodiversity loss under intensifying climatic and anthropogenic stressors. Fri, 01 May 2026 00:00:00 GMT https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212904 2026-05-01T00:00:00Z