Janus kinase (JAK) inhibitors are an important treatment option for ulcerative colitis, providing rapid onset of action, oral administration, and efficacy even after biologic failure. The 3 approved agents—tofacitinib, filgotinib, and upadacitinib—differ in JAK isoform selectivity, leading to clinically meaningful differences in efficacy and safety. Evidence from network meta-analyses, clinical trials, and real-world studies consistently shows that upadacitinib provides the highest efficacy for induction and maintenance of remission, whereas filgotinib demonstrates the most favorable safety profile. The strong efficacy of upadacitinib and tofacitinib is particularly relevant in patients with severe disease, including acute severe ulcerative colitis, and upadacitinib maintains high efficacy regardless of prior advanced therapy exposure. JAK inhibitors also benefit extraintestinal manifestations. Although risks such as herpes zoster, serious infection, thromboembolism, and major cardiovascular events differ among agents, long-term data suggest generally acceptable safety when used appropriately. Intraclass JAK-to-JAK cycling is feasible, with about half of patients achieving steroid-free clinical remission in retrospective cohorts. Based on mechanistic, clinical, and real-world evidence, filgotinib may be a first-line option for patients with lower disease activity or when safety is a priority, whereas upadacitinib or tofacitinib may be preferred in higher disease activity. Strategically selecting agents may improve durability and outcomes.

Purpose: To investigate results of the single-loop suture scleral fixation technique with long-term follow-up. Methods: This retrospective study analyzed patients who underwent scleral fixation using the single-loop suture technique between January 2010 and June 2024 with a minimum follow-up period of one year. Ophthalmic outcomes and complications including polypropylene suture type and re-operation rates were evaluated. Results: A total of 215 eyes in 201 patients were included. Polypropylene suture types used included 10-0 in 52.1% (112 of 215), 9-0 in 44.2% (95 of 215), and 3.7% (8 of 215) remained unconfirmed. The re-operation rate was 22.3% (25 of 112) with 10-0 polypropylene, 1.1% (1 of 95) with 9-0 polypropylene, and 12.1% (26 of 215) in total. Intraocular lens repositioning was needed in 0.9% (2 of 215). Postoperative intraocular pressure (IOP) elevation occurred in 51.6% (83 of 161) of patients without baseline glaucoma history; 94.0% (78 of 83) of cases were well controlled with glaucoma medication and 44.6% (37 of 83) were able to discontinue it. Conclusions Single-loop suture scleral fixation is a safe and effective surgical technique with a low incidence of serious complications.This technique leads to stable lens centering with a low rate of lens repositioning. Polypropylene suture type can affect the re-operation rate. Close monitoring of IOP is recommended.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)