Background: The relationship between circulating lipid levels and the risk for heart failure (HF) is controversial. We aimed to examine this association, and whether it is modified by the duration of diabetes or treatment regimens in people with type 2 diabetes mellitus. Methods: Individuals (n=2,439,978) who underwent health examinations in 2015 to 2016 were identified from the Korean National Health Information Database. Subjects were categorized according to the duration of diabetes (new-onset, <5, 5–10, or ≥10 years) and number of antidiabetic medications. Incident HF was defined according to the International Classification of Diseases, 10th Revision (ICD-10) code I50 as the primary diagnosis during hospitalization. The risk for HF was estimated using multivariate Cox proportional hazard analysis. Results: During a median follow-up of 4.0 years, 151,624 cases of HF occurred. An inverse association between low-density lipoprotein cholesterol (LDL-C) levels and incident HF was observed in the new-onset diabetes group, with an approximately 25% lower risk in those with LDL-C levels of 100–129, 130–159, and ≥160 mg/dL, compared to those with levels <70 mg/dL. However, J-shaped associations were noted in the long-standing diabetes group, with a 16% higher risk in those with LDL-C level ≥160 mg/dL, compared to those with levels <70 mg/dL. Similar patterns were observed in the relationship between total cholesterol or non-high-density lipoprotein cholesterol and the risk for HF, and when subjects were grouped according to the number of antidiabetic medications instead of diabetes duration. Conclusion Different associations between lipid levels and the risk for HF were noted according to disease progression status among individuals with diabetes.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background/Aims: Autoimmune gastritis (AIG) is a corpus-dominant atrophic gastritis in which patients are positive for antiparietal cell antibody (APCA) and/or anti-intrinsic factor antibody. The risk of developing gastric cancer in patients with AIG remains unclear, and reliable frequency data of AIG in patients with gastric cancer are lacking. Methods: We included 624 Korean patients with gastric tumors (612 gastric cancers and 12 neuroendocrine tumors) who had APCA results and were available for AIG evaluation. In patients with positive APCA results, endoscopy and histology findings were reviewed to diagnose AIG. Results: Of the 624 patients, 37 (5.9%) tested positive for APCA, and ultimately, 11 (1.8%) met the diagnostic criteria for AIG (5 both endoscopy and histology findings, 4 endoscopy-only findings, 2 histology-only findings). The frequency of AIG in patients with gastric cancer was 1.3% (8/612), and that in patients with neuroendocrine tumors was 25.0% (3/12). Of the 11 patients with AIG, serum Helicobacter pylori antibody was positive in six patients (54.5%), all of whom had gastric cancer. Histologically, three patients showed pure AIG, four patients exhibited concurrent AIG and H. pylori gastritis, and the findings for four were indefinite for AIG. The pepsinogen (PG) I levels and PG I/II ratio were significantly lower in patients with gastric cancer with AIG than in patients with gastric cancer without AIG (p=0.042 and p=0.016, respectively). Conclusions The frequency of AIG in gastric cancer patients was very low compared to that in patients with neuroendocrine tumors. Rather, concurrent AIG and H. pylori gastritis was common in patients with AIG with gastric cancer.

Objective: The association of lipid parameters with cardiovascular disease (CVD) and the impact of kidney function on this association have not been thoroughly evaluated in patients with type 2 diabetes mellitus (T2DM). Methods: Using the Korean National Health Insurance Service Cohort database, we identified 2,343,882 subjects with T2DM in 2015–2016. Baseline lipid levels and kidney function were evaluated and followed up until December 2020. Subjects were classified into three groups according to their estimated glomerular filtration rate (eGFR): ≥60, 30–59, or <30 mL/min/ 1.73 m2 . We analyzed the diabetes group with eGFR ≥60 and low-density lipoprotein cholesterol (LDL-C) <70 mg/dL as a reference group. Results: The risk of CVD began to increase at LDL-C ≥100 mg/dL in the eGFR ≥60 mL/min/m2group. The risk of CVD in the eGFR 30–59 mL/min/m2 group was increased by 43%, even in the LDL-C <70 mg/dL, and the risk increased progressively with LDL-C category. Among subjects with eGFR 30–59 mL/min/m2 , LDL-C 70–99, 100–129, 130–159, and ≥160 mg/ dL were significantly associated with the risk of CVD, with hazard ratio (95% confidence interval) of 1.48 (1.43–1.53), 1.54 (1.49–1.60), 1.55 (1.48–1.63), and 1.88 (1.77–2.00), respectively. In the eGFR <30 mL/min/m2 group, a 3.3-fold increased risk of CVD was seen, even at LDL-C <70 mg/dL. Conclusion The cutoff levels of LDL-C that increase CVD risk in patients with T2DM depend on kidney function, which influences the relationship between LDL-C and CVD risk in patients with T2DM.

Objective: The association of lipid parameters with cardiovascular disease (CVD) and the impact of kidney function on this association have not been thoroughly evaluated in patients with type 2 diabetes mellitus (T2DM). Methods: Using the Korean National Health Insurance Service Cohort database, we identified 2,343,882 subjects with T2DM in 2015–2016. Baseline lipid levels and kidney function were evaluated and followed up until December 2020. Subjects were classified into three groups according to their estimated glomerular filtration rate (eGFR): ≥60, 30–59, or <30 mL/min/ 1.73 m2 . We analyzed the diabetes group with eGFR ≥60 and low-density lipoprotein cholesterol (LDL-C) <70 mg/dL as a reference group. Results: The risk of CVD began to increase at LDL-C ≥100 mg/dL in the eGFR ≥60 mL/min/m2group. The risk of CVD in the eGFR 30–59 mL/min/m2 group was increased by 43%, even in the LDL-C <70 mg/dL, and the risk increased progressively with LDL-C category. Among subjects with eGFR 30–59 mL/min/m2 , LDL-C 70–99, 100–129, 130–159, and ≥160 mg/ dL were significantly associated with the risk of CVD, with hazard ratio (95% confidence interval) of 1.48 (1.43–1.53), 1.54 (1.49–1.60), 1.55 (1.48–1.63), and 1.88 (1.77–2.00), respectively. In the eGFR <30 mL/min/m2 group, a 3.3-fold increased risk of CVD was seen, even at LDL-C <70 mg/dL. Conclusion The cutoff levels of LDL-C that increase CVD risk in patients with T2DM depend on kidney function, which influences the relationship between LDL-C and CVD risk in patients with T2DM.

This study evaluated the long-term stability and efficacy of occlusion achieved by setting a normalized chewing position as the therapeutic position in patients with abnormal chewing positions due to tooth loss or malocclusion. Furthermore, the study monitored the recovery rate of the stomatognathic system. Sixteen patients undergoing oral functional rehabilitation participated in the study, utilizing an intraoral Gothic arch tracer to normalize abnormal chewing positions and designate the apex of the resultant chewing patterns as the therapeutic position. The first set of data was gathered during occlusal reconstruction at the point when a therapeutic position was necessary, and the second set was collected approximately 10 years later under the same conditions. Four mandibular movements—chewing movements for hard food (CM-H), chewing movements for soft food (CM-S), border movement (BM), and maximum intercuspation position (MICP)—were compared to assess the long-term stability between the chewing position and occlusion and the recovery rate of the stomatognathic system. The findings showed a 63% concordance between CM-H and MICP, confirming the long-term stability of both the chewing position and occlusion. Furthermore, the concordance between CM-H and CM-S increased by 13%, whereas the alignment between the chewing position and BM increased by 25%. In summary, the concordance across all four movements improved by 19%, demonstrating increased long-term recovery rate of the stomatognathic system. These findings provide clinical evidence that occlusal reconstruction centered on the chewing position offers long-term stability and recovery. By establishing an efficient occlusion that harmonized with the chewing patterns, this approach compensates for age-related declines in chewing function and helps maintain the stomatognathic system health.

Background: The relationship between circulating lipid levels and the risk for heart failure (HF) is controversial. We aimed to examine this association, and whether it is modified by the duration of diabetes or treatment regimens in people with type 2 diabetes mellitus. Methods: Individuals (n=2,439,978) who underwent health examinations in 2015 to 2016 were identified from the Korean National Health Information Database. Subjects were categorized according to the duration of diabetes (new-onset, <5, 5–10, or ≥10 years) and number of antidiabetic medications. Incident HF was defined according to the International Classification of Diseases, 10th Revision (ICD-10) code I50 as the primary diagnosis during hospitalization. The risk for HF was estimated using multivariate Cox proportional hazard analysis. Results: During a median follow-up of 4.0 years, 151,624 cases of HF occurred. An inverse association between low-density lipoprotein cholesterol (LDL-C) levels and incident HF was observed in the new-onset diabetes group, with an approximately 25% lower risk in those with LDL-C levels of 100–129, 130–159, and ≥160 mg/dL, compared to those with levels <70 mg/dL. However, J-shaped associations were noted in the long-standing diabetes group, with a 16% higher risk in those with LDL-C level ≥160 mg/dL, compared to those with levels <70 mg/dL. Similar patterns were observed in the relationship between total cholesterol or non-high-density lipoprotein cholesterol and the risk for HF, and when subjects were grouped according to the number of antidiabetic medications instead of diabetes duration. Conclusion Different associations between lipid levels and the risk for HF were noted according to disease progression status among individuals with diabetes.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background/Aims: Autoimmune gastritis (AIG) is a corpus-dominant atrophic gastritis in which patients are positive for antiparietal cell antibody (APCA) and/or anti-intrinsic factor antibody. The risk of developing gastric cancer in patients with AIG remains unclear, and reliable frequency data of AIG in patients with gastric cancer are lacking. Methods: We included 624 Korean patients with gastric tumors (612 gastric cancers and 12 neuroendocrine tumors) who had APCA results and were available for AIG evaluation. In patients with positive APCA results, endoscopy and histology findings were reviewed to diagnose AIG. Results: Of the 624 patients, 37 (5.9%) tested positive for APCA, and ultimately, 11 (1.8%) met the diagnostic criteria for AIG (5 both endoscopy and histology findings, 4 endoscopy-only findings, 2 histology-only findings). The frequency of AIG in patients with gastric cancer was 1.3% (8/612), and that in patients with neuroendocrine tumors was 25.0% (3/12). Of the 11 patients with AIG, serum Helicobacter pylori antibody was positive in six patients (54.5%), all of whom had gastric cancer. Histologically, three patients showed pure AIG, four patients exhibited concurrent AIG and H. pylori gastritis, and the findings for four were indefinite for AIG. The pepsinogen (PG) I levels and PG I/II ratio were significantly lower in patients with gastric cancer with AIG than in patients with gastric cancer without AIG (p=0.042 and p=0.016, respectively). Conclusions The frequency of AIG in gastric cancer patients was very low compared to that in patients with neuroendocrine tumors. Rather, concurrent AIG and H. pylori gastritis was common in patients with AIG with gastric cancer.

Background: The relationship between circulating lipid levels and the risk for heart failure (HF) is controversial. We aimed to examine this association, and whether it is modified by the duration of diabetes or treatment regimens in people with type 2 diabetes mellitus. Methods: Individuals (n=2,439,978) who underwent health examinations in 2015 to 2016 were identified from the Korean National Health Information Database. Subjects were categorized according to the duration of diabetes (new-onset, <5, 5–10, or ≥10 years) and number of antidiabetic medications. Incident HF was defined according to the International Classification of Diseases, 10th Revision (ICD-10) code I50 as the primary diagnosis during hospitalization. The risk for HF was estimated using multivariate Cox proportional hazard analysis. Results: During a median follow-up of 4.0 years, 151,624 cases of HF occurred. An inverse association between low-density lipoprotein cholesterol (LDL-C) levels and incident HF was observed in the new-onset diabetes group, with an approximately 25% lower risk in those with LDL-C levels of 100–129, 130–159, and ≥160 mg/dL, compared to those with levels <70 mg/dL. However, J-shaped associations were noted in the long-standing diabetes group, with a 16% higher risk in those with LDL-C level ≥160 mg/dL, compared to those with levels <70 mg/dL. Similar patterns were observed in the relationship between total cholesterol or non-high-density lipoprotein cholesterol and the risk for HF, and when subjects were grouped according to the number of antidiabetic medications instead of diabetes duration. Conclusion Different associations between lipid levels and the risk for HF were noted according to disease progression status among individuals with diabetes.