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.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Purpose: This study developed a thermoelectric element (TEE) tourniquet integrating a tourniquet with a temperature control device capable of delivering heat or cold therapy. A randomized controlled trial was conducted to evaluate the effects of the TEE tourniquet on pain, stress, and satisfaction during venipuncture. Methods: In total, 118 hospitalized adults were randomly assigned to heat therapy (40~45°C), cold therapy (0~10°C), thermal grill illusion therapy (alternating heat and cold), or the control group. The TEE tourniquet was applied 10 cm above the puncture site. A temperature intervention began 5 seconds before cannulation and was maintained during the procedure, typically lasting 10 to 30 seconds. The control group received the TEE tourniquet without temperature activation. Outcomes included perceived pain and stress (numerical rating scale), observed pain (Wong-Baker FACES), SpO2, stress index, and participant satisfaction. Results: Significant differences were found among groups in perceived pain (F = 4.82, p = .003), observed pain (F = 5.50, p = .001), and perceived stress (F = 4.72, p = .004). The heat therapy group reported significantly lower pain and stress than the control group. No significant differences were found in SpO₂, the stress index, or satisfaction. Conclusion Heat therapy via the TEE tourniquet significantly reduced venipuncture-related pain and stress. Given its short application time and usability, this device may serve as a clinically useful nursing intervention to improve comfort during invasive procedures.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Purpose: This study developed a thermoelectric element (TEE) tourniquet integrating a tourniquet with a temperature control device capable of delivering heat or cold therapy. A randomized controlled trial was conducted to evaluate the effects of the TEE tourniquet on pain, stress, and satisfaction during venipuncture. Methods: In total, 118 hospitalized adults were randomly assigned to heat therapy (40~45°C), cold therapy (0~10°C), thermal grill illusion therapy (alternating heat and cold), or the control group. The TEE tourniquet was applied 10 cm above the puncture site. A temperature intervention began 5 seconds before cannulation and was maintained during the procedure, typically lasting 10 to 30 seconds. The control group received the TEE tourniquet without temperature activation. Outcomes included perceived pain and stress (numerical rating scale), observed pain (Wong-Baker FACES), SpO2, stress index, and participant satisfaction. Results: Significant differences were found among groups in perceived pain (F = 4.82, p = .003), observed pain (F = 5.50, p = .001), and perceived stress (F = 4.72, p = .004). The heat therapy group reported significantly lower pain and stress than the control group. No significant differences were found in SpO₂, the stress index, or satisfaction. Conclusion Heat therapy via the TEE tourniquet significantly reduced venipuncture-related pain and stress. Given its short application time and usability, this device may serve as a clinically useful nursing intervention to improve comfort during invasive procedures.

Purpose: This study developed a thermoelectric element (TEE) tourniquet integrating a tourniquet with a temperature control device capable of delivering heat or cold therapy. A randomized controlled trial was conducted to evaluate the effects of the TEE tourniquet on pain, stress, and satisfaction during venipuncture. Methods: In total, 118 hospitalized adults were randomly assigned to heat therapy (40~45°C), cold therapy (0~10°C), thermal grill illusion therapy (alternating heat and cold), or the control group. The TEE tourniquet was applied 10 cm above the puncture site. A temperature intervention began 5 seconds before cannulation and was maintained during the procedure, typically lasting 10 to 30 seconds. The control group received the TEE tourniquet without temperature activation. Outcomes included perceived pain and stress (numerical rating scale), observed pain (Wong-Baker FACES), SpO2, stress index, and participant satisfaction. Results: Significant differences were found among groups in perceived pain (F = 4.82, p = .003), observed pain (F = 5.50, p = .001), and perceived stress (F = 4.72, p = .004). The heat therapy group reported significantly lower pain and stress than the control group. No significant differences were found in SpO₂, the stress index, or satisfaction. Conclusion Heat therapy via the TEE tourniquet significantly reduced venipuncture-related pain and stress. Given its short application time and usability, this device may serve as a clinically useful nursing intervention to improve comfort during invasive procedures.

Purpose: This study developed a thermoelectric element (TEE) tourniquet integrating a tourniquet with a temperature control device capable of delivering heat or cold therapy. A randomized controlled trial was conducted to evaluate the effects of the TEE tourniquet on pain, stress, and satisfaction during venipuncture. Methods: In total, 118 hospitalized adults were randomly assigned to heat therapy (40~45°C), cold therapy (0~10°C), thermal grill illusion therapy (alternating heat and cold), or the control group. The TEE tourniquet was applied 10 cm above the puncture site. A temperature intervention began 5 seconds before cannulation and was maintained during the procedure, typically lasting 10 to 30 seconds. The control group received the TEE tourniquet without temperature activation. Outcomes included perceived pain and stress (numerical rating scale), observed pain (Wong-Baker FACES), SpO2, stress index, and participant satisfaction. Results: Significant differences were found among groups in perceived pain (F = 4.82, p = .003), observed pain (F = 5.50, p = .001), and perceived stress (F = 4.72, p = .004). The heat therapy group reported significantly lower pain and stress than the control group. No significant differences were found in SpO₂, the stress index, or satisfaction. Conclusion Heat therapy via the TEE tourniquet significantly reduced venipuncture-related pain and stress. Given its short application time and usability, this device may serve as a clinically useful nursing intervention to improve comfort during invasive procedures.

Temporomandibular disorders (TMD) and migraine are common comorbidities. Orofacial migraine (OFM), a rare subtype of migraine, is confined to the facial areas innervated by the maxillary (V2) and mandibular (V3) divisions of the trigeminal nerve, and presents significant diagnostic challenges because symptoms overlap with other facial disorders.This case report is of a 29-year-old woman patient with TMD who presented with migraine-related orofacial symptoms. Diagnostic evaluation included the Diagnostic Criteria for TMD and validated questionnaires, including Generalized Anxiety Disorder-7, Patient Health Questionnaire (PHQ)-9, PHQ-15, the Graded Chronic Pain Scale (GCPS), the Symptom Checklist-90-Revision (SCL-90-R) and headache questionnaire. Psychological evaluation results showed grade IV disability (GCPS), mild depression (PHQ-9) and low somatic symptom severity (PHQ-15). The SCL-90-R indicated high scores in somatization and positive symptom distress index. Treatment included behavioral therapy, physical therapy, stabilization splint therapy and pharmacological management including aceclofenac and sumatriptan. At 6-month follow-up, pain intensity significantly decreased from 9 to 3 on a 0-10 Numeric Rating Scale. Comfortable mouth opening range increased from 20 to 48 mm, and maximum mouth opening range increased from 40 to 48 mm. Tenderness on palpation of the left temporomandibular joint (TMJ) capsule, masseter, and temporalis muscles resolved, and TMJ noise on the left side also disappeared. This case highlights the importance of recognizing migraine symptoms that can manifest in the orofacial region. Such symptoms may coexist with TMD, necessitating a multidisciplinary diagnostic and therapeutic approach.