Rectal cancer, which accounts for approximately 40% of colorectal cancers, remains a major clinical concern. Recent advances in diagnostic imaging, surgical techniques, radiotherapy, and systemic treatment have steadily improved rectal cancer outcomes. Considering this, the Korean Rectal Cancer Multidisciplinary (KRCM) Committee has aimed to provide clinicians and policymakers with up-to-date, evidence-based clinical practice guidelines to support optimal decision-making, reflecting current evidence, the Korean healthcare context, and patient values and preferences. The Clinical Practice Guidelines for Rectal Cancer version 2.0 were developed through multidisciplinary collaboration with related academic societies, building upon and updating the KRCM Clinical Practice Guidelines version 1.0 (titled “Multidisciplinary guidelines for the management of rectal cancer”). These consensus guidelines of the KRCM were established based on a comprehensive literature review, evidence synthesis, with recommendation development guided by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology, and consideration of applicability in real-world clinical practice under the national health insurance system. Each recommendation has been presented with its strength and level of evidence.

Myopia, particularly high myopia, is a significant risk factor for several ocular pathologies including cataract, glaucoma, and retinal detachment. Excessive axial elongation associated with high myopia can induce biomechanical stretching, increasing the risk of serious complications like posterior staphyloma and myopic maculopathy. Global meta-analyses estimate that approximately 10 million people were visually impaired due to myopic maculopathy in 2015, with 3 million being blind. Recent nationwide surveys in South Korea revealed a prevalence of 65.4% for myopia and 6.9% for high myopia in children and adolescents, highlighting the urgent need for effective management. Delaying the onset and slowing the progression of myopia during childhood and adolescence is crucial for reducing the potential lifetime risk of these complications. This consensus statement, prepared by the Korean Myopia Society for the Korean Association for Pediatric Ophthalmology and Strabismus (KAPOS), reviews the current evidence for myopia control interventions and provides management strategies applicable to the South Korean clinical setting. Key interventions covered include lifestyle modifications (outdoor time, near work adjustment), optical methods (myopia-control spectacle lenses, dual-focus soft contact lenses, orthokeratology), and pharmacologic treatment (low-concentration atropine), as well as combination therapies. The statement also addresses patient selection, treatment outcome evaluation using spherical equivalent and axial length changes, and the crucial aspects related to treatment cessation and the rebound effect.

Objectives: This study investigated medication perceptions, adherence patterns, self-discontinuation experiences, and information sources among psychiatric outpatients to provide evidence for improving adherence strategies. Methods: A cross-sectional survey was conducted with 79 outpatients from a University Hospital, Department of Psychiatry. Self-administered questionnaires assessed diagnostic awareness, medication perceptions, adherence behaviors, discontinuation experiences, side effects, and information sources. Results: Overall, 89.7% knew their psychiatric diagnosis and 88.2% perceived medication as effective. While 73.1% rarely forgot medication, 35.9% had previously self-discontinued treatment. Medication adherence was significantly associated with previous discontinuation experience (p=0.006), whereas diagnostic awareness and efficacy perception were not. Primary discontinuation reasons were symptom improvement (53.6%) and physical discomfort (35.7%). Common side effects included weight gain (n=31), daytime drowsiness (n=26), memory impairment (n=24), and concentration problems (n=22). Patients primarily obtained side effect information from TV/internet (27.8%) rather than healthcare providers (20.3%). Most patients desired additional information about side effects (57.0%) and medication effects (54.4%). Conclusion Daily medication-taking behaviors were more predictive of treatment discontinuation than cognitive factors in this outpatient sample. Discontinuation due to symptom improvement and reliance on non-medical information sources highlights the need for enhanced patient education regarding relapse risks and systematic provision of accurate medication information.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

High-flow nasal cannula (HFNC) is a noninvasive respiratory support system that delivers air that is heated at 31°C−38°C, humidified 100%, and oxygen-enriched at a constant high flow rate of 15−60 L/min. Because of its numerous physiological benefits, convenience, and minimal side effects, HFNC has been increasingly used over the past decade in patients with acute hypoxemic respiratory failure, yet the clinical benefits of long-term HFNC remain uncertain. Several studies have suggested its potential use as an alternative home oxygen therapy for patients with chronic stable lung diseases, such as chronic obstructive pulmonary disease (COPD), interstitial lung disease, and bronchiectasis. The use of long-term home HFNC in patients with chronic respiratory failure is an emerging area with promising potential. Despite limited clinical research, this review aims to describe the physiology of HFNC use and summarize the current evidence on its long-term application, to provide healthcare providers with insights and perspectives on the potential role of long-term home HFNC.

Purpose: This study aimed to explore the effects of both the presence and size of posterior subependymal germinal matrix hemorrhage (PS-GMH), considered a mild form of hemorrhage, on the neurodevelopmental outcomes of extremely preterm infants. Methods: A retrospective analysis was conducted on 221 extremely preterm infants, assessing their initial and term-equivalent age (TEA) cranial ultrasound (cUS) examinations from 2016 to 2021. Infants were classified based on the presence and size (small/large) of PS-GMH. Neurodevelopmental outcomes at corrected ages of 18-24 months were analyzed in 135 infants. Results: PS-GMH was identified in 86.9% (192/221) of the infants, with 13.5% (26/192) exhibiting large PS-GMH. Among the 135 infants who were followed up, those with PS-GMH were found to have younger gestational ages (P<0.001) and a higher incidence of maternal chorioamnionitis (P=0.016) than those without PS-GMH. Significant differences were observed in the incidence of grade II intraventricular hemorrhage (IVH) on initial cUS (P=0.003) and ventriculomegaly at TEA cUS (P=0.026) across the groups with no PS-GMH, small PS-GMH, and large PS-GMH. The large PS-GMH group exhibited a higher occurrence of grade II IVH than the small PS-GMH group (P=0.006). However, ventriculomegaly incidence did not significantly vary with PS-GMH status. Neurodevelopmental outcomes were also not significantly different across PS-GMH statuses. The adjusted odds ratios for any neurodevelopmental impairment, compared to the no PS-GMH group, were 1.70 (95% confidence interval [CI], 0.40 to 7.26; P=0.471) for all PS-GMH, 1.61 (95% CI, 0.37 to 6.93; P=0.526) for small PS-GMH, and 3.84 (95% CI, 0.62 to 24.00; P=0.150) for large PS-GMH. Conclusion PS-GMH was frequently observed in extremely preterm infants; however, it did not independently predict adverse neurodevelopmental outcomes.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.