Background: Limited data are available on the adverse effects of new-onset diabetes after transplantation (NODAT) in solid organ transplantation (TPL) other than kidney. This study aimed to identify the risk of complications associated with NODAT in recipients of kidney, liver, or heart TPL. Methods: Using the Korean National Health Insurance Service database, recipients of kidney, liver, or heart TPL between 2009 and 2015 were identified. The incidence of coronary artery disease (CAD), cerebrovascular accident (CVA), and malignancy was compared across groups with NODAT, pretransplant diabetes mellitus (DM), and without DM using Cox regression analysis. Results: A total of 9,632 kidney, liver, or heart TPL recipients were included. During the median follow-up of 5.9 years, NODAT independently increased the incidence of CAD (hazard ratio [HR], 2.46; 95% confidence interval [CI], 1.39 to 4.30) and overall mortality (HR, 1.48; 95% CI, 1.14 to 1.95) compared to the reference group even after adjustment for confounders; this was more prominent in kidney TPL than in liver TPL. The risk of CVA was significantly increased by pretransplant DM but not by NODAT in both kidney and liver TPL (HR, 2.47; 95% CI, 1.68 to 3.65; and HR, 3.18; 95% CI, 1.07 to 9.48, respectively). NODAT increased the risk of malignancy in the crude model, which lost its statistical significance after confounder adjustment. Conclusion NODAT independently increases the risk of CAD and mortality after TPL, which is more evident in kidney recipients. There was no additional increased risk of CVA or malignancy with NODAT in solid organ TPL.

Background: Limited data are available on the adverse effects of new-onset diabetes after transplantation (NODAT) in solid organ transplantation (TPL) other than kidney. This study aimed to identify the risk of complications associated with NODAT in recipients of kidney, liver, or heart TPL. Methods: Using the Korean National Health Insurance Service database, recipients of kidney, liver, or heart TPL between 2009 and 2015 were identified. The incidence of coronary artery disease (CAD), cerebrovascular accident (CVA), and malignancy was compared across groups with NODAT, pretransplant diabetes mellitus (DM), and without DM using Cox regression analysis. Results: A total of 9,632 kidney, liver, or heart TPL recipients were included. During the median follow-up of 5.9 years, NODAT independently increased the incidence of CAD (hazard ratio [HR], 2.46; 95% confidence interval [CI], 1.39 to 4.30) and overall mortality (HR, 1.48; 95% CI, 1.14 to 1.95) compared to the reference group even after adjustment for confounders; this was more prominent in kidney TPL than in liver TPL. The risk of CVA was significantly increased by pretransplant DM but not by NODAT in both kidney and liver TPL (HR, 2.47; 95% CI, 1.68 to 3.65; and HR, 3.18; 95% CI, 1.07 to 9.48, respectively). NODAT increased the risk of malignancy in the crude model, which lost its statistical significance after confounder adjustment. Conclusion NODAT independently increases the risk of CAD and mortality after TPL, which is more evident in kidney recipients. There was no additional increased risk of CVA or malignancy with NODAT in solid organ TPL.

Background: Limited data are available on the adverse effects of new-onset diabetes after transplantation (NODAT) in solid organ transplantation (TPL) other than kidney. This study aimed to identify the risk of complications associated with NODAT in recipients of kidney, liver, or heart TPL. Methods: Using the Korean National Health Insurance Service database, recipients of kidney, liver, or heart TPL between 2009 and 2015 were identified. The incidence of coronary artery disease (CAD), cerebrovascular accident (CVA), and malignancy was compared across groups with NODAT, pretransplant diabetes mellitus (DM), and without DM using Cox regression analysis. Results: A total of 9,632 kidney, liver, or heart TPL recipients were included. During the median follow-up of 5.9 years, NODAT independently increased the incidence of CAD (hazard ratio [HR], 2.46; 95% confidence interval [CI], 1.39 to 4.30) and overall mortality (HR, 1.48; 95% CI, 1.14 to 1.95) compared to the reference group even after adjustment for confounders; this was more prominent in kidney TPL than in liver TPL. The risk of CVA was significantly increased by pretransplant DM but not by NODAT in both kidney and liver TPL (HR, 2.47; 95% CI, 1.68 to 3.65; and HR, 3.18; 95% CI, 1.07 to 9.48, respectively). NODAT increased the risk of malignancy in the crude model, which lost its statistical significance after confounder adjustment. Conclusion NODAT independently increases the risk of CAD and mortality after TPL, which is more evident in kidney recipients. There was no additional increased risk of CVA or malignancy with NODAT in solid organ TPL.

Background: Limited data are available on the adverse effects of new-onset diabetes after transplantation (NODAT) in solid organ transplantation (TPL) other than kidney. This study aimed to identify the risk of complications associated with NODAT in recipients of kidney, liver, or heart TPL. Methods: Using the Korean National Health Insurance Service database, recipients of kidney, liver, or heart TPL between 2009 and 2015 were identified. The incidence of coronary artery disease (CAD), cerebrovascular accident (CVA), and malignancy was compared across groups with NODAT, pretransplant diabetes mellitus (DM), and without DM using Cox regression analysis. Results: A total of 9,632 kidney, liver, or heart TPL recipients were included. During the median follow-up of 5.9 years, NODAT independently increased the incidence of CAD (hazard ratio [HR], 2.46; 95% confidence interval [CI], 1.39 to 4.30) and overall mortality (HR, 1.48; 95% CI, 1.14 to 1.95) compared to the reference group even after adjustment for confounders; this was more prominent in kidney TPL than in liver TPL. The risk of CVA was significantly increased by pretransplant DM but not by NODAT in both kidney and liver TPL (HR, 2.47; 95% CI, 1.68 to 3.65; and HR, 3.18; 95% CI, 1.07 to 9.48, respectively). NODAT increased the risk of malignancy in the crude model, which lost its statistical significance after confounder adjustment. Conclusion NODAT independently increases the risk of CAD and mortality after TPL, which is more evident in kidney recipients. There was no additional increased risk of CVA or malignancy with NODAT in solid organ TPL.

The indolent nature and favorable outcomes associated with papillary thyroid microcarcinoma have prompted numerous prospective studies on active surveillance (AS) and its adoption as an alternative to immediate surgery in managing low-risk thyroid cancer. This article reviews the current status of AS, as outlined in various international practice guidelines. AS is typically recommended for tumors that measure 1 cm or less in diameter and do not exhibit aggressive subtypes on cytology, extrathyroidal extension, lymph node metastasis, or distant metastasis. To determine the most appropriate candidates for AS, factors such as tumor size, location, multiplicity, and ultrasound findings are considered, along with patient characteristics like medical condition, age, and family history. Moreover, shared decision-making, which includes patient-reported outcomes such as quality of life and cost-effectiveness, is essential. During AS, patients undergo regular ultrasound examinations to monitor for signs of disease progression, including tumor growth, extrathyroidal extension, or lymph node metastasis. In conclusion, while AS is a feasible and reliable approach for managing lowrisk thyroid cancer, it requires careful patient selection, effective communication for shared decision-making, standardized follow-up protocols, and a clear definition of disease progression.

Differentiated thyroid cancer demonstrates a wide range of clinical presentations, from very indolent cases to those with an aggressive prognosis. Therefore, diagnosing and treating each cancer appropriately based on its risk status is important. The Korean Thyroid Association (KTA) has provided and amended the clinical guidelines for thyroid cancer management since 2007. The main changes in this revised 2024 guideline include 1) individualization of surgical extent according to pathological tests and clinical findings, 2) application of active surveillance in low-risk papillary thyroid microcarcinoma, 3) indications for minimally invasive surgery, 4) adoption of World Health Organization pathological diagnostic criteria and definition of terminology in Korean, 5) update on literature evidence of recurrence risk for initial risk stratification, 6) addition of the role of molecular testing, 7) addition of definition of initial risk stratification and targeting thyroid stimulating hormone (TSH) concentrations according to ongoing risk stratification (ORS), 8) addition of treatment of perioperative hypoparathyroidism, 9) update on systemic chemotherapy, and 10) addition of treatment for pediatric patients with thyroid cancer.

Background/Aims: The Gout Impact Scale (GIS), a part of the Gout Assessment Questionnaire 2.0, is used to measure gout-specific health-related quality of life (HRQOL). Although several studies have been conducted on the factors affecting the HRQOL of patients with gout, few have focused on lifestyle factors. This study aimed to investigate the correlation between lifestyle habits and HRQOL using the GIS in patients with gout. Methods: We used data from the Urate-Lowering TheRApy in Gout (ULTRA) registry, a prospective cohort of Korean patients with gout treated at multiple centers nationwide. The patients were aged ≥18 years and met the 2015 American College of Rheumatology/European League Against Rheumatism gout classification criteria. They were asked to complete a GIS and questions regarding their lifestyle habits at enrollment. Results: The study included 232 patients. ‘Gout concern overall’ scores in the GIS were significantly lower in patients who exercised more frequently and consumed soft drinks and meat less, and ‘well-being during attack’ scores were significantly lower in patients who consumed vegetables and exercised more frequently. The frequency of vegetable consumption had a negative linear relationship with the ‘well-being during attack’ and ‘gout concern during attack’ scores (p = 0.01, p = 0.001, respectively). The frequency of exercise had a negative linear relationship with the ‘gout concern overall’ and ‘gout concern during attack’ scores (p = 0.04 and p = 0.002, respectively). Conclusions Patients with gout who frequently consumed vegetables and exercised regularly experienced less impact of gout, exhibiting a better GIS that represented HRQOL.

Dyslipidemia in patients with diabetes is an important treatment target as a modifiable risk factor for cardiovascular disease (CVD). Although the primary treatment goal for dyslipidemia is to control low-density lipoprotein cholesterol (LDL-C), achieving this goal remains suboptimal according to recent studies. It is important to set the target goal for LDL-C control based on an accurate risk assessment for CVD. Here, we summarize the latest evidence on lipid management in patients with diabetes and present a consensus of the Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis on the treatment goals of LDL-C according to the duration of diabetes, presence of CVD, target organ damage, or major cardiovascular risk factors. In patients with type 2 diabetes mellitus (T2DM) and CVD, an LDL-C goal of <55 mg/dL and a reduction in LDL-C level by 50% or more from the baseline is recommended. For the primary prevention of CVD in patients with T2DM with a duration of diabetes ≥10 years, major cardiovascular risk factors, or target organ damage, an LDL-C goal of <70 mg/dL is recommended. In patients with T2DM with a duration of diabetes <10 years and no major cardiovascular risk factors, an LDL-C goal of <100 mg/dL is recommended.

Background/Aims: The Korean Diabetes Association (KDA) guidelines recommend adults aged ≥ 40 years and adults aged ≥ 30 years with diabetes risk factors for diabetes screening. This study aimed to determine the age threshold for diabetes screening in Korean adults. Methods: This study was based on the analyses of Korean adults aged ≥ 20 years using the Korea National Health and Nutrition Examination Survey (KNHANES) and the National Health Insurance Service-National Sample Cohort (NHIS-NSC). To evaluate screening effectiveness, we calculated the number needed to screen (NNS). Results: NNS to detect diabetes decreased from 63 to 34 in the KNHANES and from 71 to 42 in the NHIS-NSC between the ages of 30–34 and 35–39. When universal screening was applied to adults aged ≥ 35, the NNS was similar to that of adults aged ≥ 40. Compared to the KDA guidelines, the rate of missed screening positive in adults aged ≥ 20 decreased from 4.0% to 0.2% when the newly suggested screening criteria were applied. Conclusions Universal screening for adults aged ≥ 35 and selective screening for adults aged 20 to 34, considering diabetes risk factors, may be appropriate for detecting prediabetes and diabetes in South Korea.