Background/Aims: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems have been introduced to increase the polyp detection rate (PDR) during colonoscopy, potentially enhancing its effectiveness. This study aimed to evaluate the efficacy of a CADe system in colorectal neoplasm detection. Methods: This prospective, randomized controlled trial was conducted at two tertiary centers (May 2023 to April 2025). Patients were randomly assigned to CADe or conventional colonoscopy and underwent screening, surveillance, or diagnostic colonoscopy. The primary endpoint was the adenoma detection rate (ADR), while the secondary endpoints were the PDR, relative risk (RR) of polyp detection, adenomas per colonoscopy (APC), and factors influencing adenoma detection. Results: Of 1,004 enrolled patients, 998 were randomly allocated into CADe and conventional colonoscopy groups (497 CADe system and 501 conventional colonoscopy). The CADe group had greater polyp counts (2.2 per colonoscopy vs 1.4 per colonoscopy; p<0.001) and APC values (1.2 vs 0.8; p<0.001). The CADe group showed significantly higher PDRs (72.2% vs 54.5%;p<0.001; RR, 2.173; 95% confidence interval [CI], 1.669 to 2.828) and ADRs (52.3% vs 36.1%;p<0.001; RR, 1.940; 95% CI, 1.505 to 2.499). CADe also significantly increased the detection rate of hyperplastic polyps (p=0.007; RR, 1.474; 95% CI, 1.113 to 1.952) and increased the detection rates across all sizes and locations. In multivariable analysis, CADe use was the strongest independent predictor of adenoma detection (odds ratio, 1.914; 95% CI, 1.467 to 2.496), outweighing male sex, older age, diagnostic indication, and withdrawal time. Conclusions Real-time CADe-assisted colonoscopy significantly increased PDR and ADR and proved to be a strong independent predictor of adenoma detection (cris.nih.go.kr, KCT0009664).

Objective: This study aims to objectively evaluate turning gait parameters in Parkinson’s disease (PD) patients using 2D-RGB video-based analysis and explore their relationships with imbalance. Methods: We prospectively enrolled PD patients for clinical assessment, balance analysis and gait with 180º turning. Spatiotemporal gait parameters during turning were derived using video-based analysis and correlated with modified Hoehn and Yahr (mHY) stages and center of pressure (COP) oscillations. Results: A total of 64 PD patients were enrolled. The PD patients with higher mHY stages (≥2.5) had significantly longer turning times, greater numbers of steps, wider step bases and less variability in step length during turns. COP oscillations were positively correlated with the mean turning time on both the anterior-posterior and right-left axes. Conclusion Spatiotemporal gait parameter during turning, derived from video-based gait analysis, may represent apromising biomarker for monitoring postural instability in PD patients.

Objective: This study aims to objectively evaluate turning gait parameters in Parkinson’s disease (PD) patients using 2D-RGB video-based analysis and explore their relationships with imbalance. Methods: We prospectively enrolled PD patients for clinical assessment, balance analysis and gait with 180º turning. Spatiotemporal gait parameters during turning were derived using video-based analysis and correlated with modified Hoehn and Yahr (mHY) stages and center of pressure (COP) oscillations. Results: A total of 64 PD patients were enrolled. The PD patients with higher mHY stages (≥2.5) had significantly longer turning times, greater numbers of steps, wider step bases and less variability in step length during turns. COP oscillations were positively correlated with the mean turning time on both the anterior-posterior and right-left axes. Conclusion Spatiotemporal gait parameter during turning, derived from video-based gait analysis, may represent apromising biomarker for monitoring postural instability in PD patients.

Objective: This study aims to objectively evaluate turning gait parameters in Parkinson’s disease (PD) patients using 2D-RGB video-based analysis and explore their relationships with imbalance. Methods: We prospectively enrolled PD patients for clinical assessment, balance analysis and gait with 180º turning. Spatiotemporal gait parameters during turning were derived using video-based analysis and correlated with modified Hoehn and Yahr (mHY) stages and center of pressure (COP) oscillations. Results: A total of 64 PD patients were enrolled. The PD patients with higher mHY stages (≥2.5) had significantly longer turning times, greater numbers of steps, wider step bases and less variability in step length during turns. COP oscillations were positively correlated with the mean turning time on both the anterior-posterior and right-left axes. Conclusion Spatiotemporal gait parameter during turning, derived from video-based gait analysis, may represent apromising biomarker for monitoring postural instability in PD patients.

Background/Aims: Intensive care unit (ICU) quality is largely determined by the mortality rate. Therefore, we aimed to develop and validate a novel prognostic model for predicting mortality in Korean ICUs, using national insurance claims data. Methods: Data were obtained from the health insurance claims database maintained by the Health Insurance Review and Assessment Service of South Korea. From patients who underwent the third ICU adequacy evaluation, 42,489 cases were enrolled and randomly divided into the derivation and validation cohorts. Using the models derived from the derivation cohort, we analyzed whether they accurately predicted death in the validation cohort. The models were verified using data from one general and two tertiary hospitals. Results: Two severity correction models were created from the derivation cohort data, by applying variables selected through statistical analysis, through clinical consensus, and from performing multiple logistic regression analysis. Model 1 included six categorical variables (age, sex, Charlson comorbidity index, ventilator use, hemodialysis or continuous renal replacement therapy, and vasopressor use). Model 2 additionally included presence/absence of ICU specialists and nursing grades. In external validation, the performance of models 1 and 2 for predicting in-hospital and ICU mortality was not inferior to that of pre-existing scoring systems. Conclusions The novel and simple models could predict in-hospital and ICU mortality and were not inferior compared to the pre-existing scoring systems.