Heart failure (HF) is a major cause of mortality and morbidity in South Korea, imposing substantial physical, emotional, and financial burdens on patients and society. Despite the high burden of symptom and complex care needs of HF patients, palliative care and hospice services remain underutilized in South Korea due to cultural, institutional, and knowledge-related barriers. This position statement from the Korean Society of Heart Failure emphasizes the need for integrating palliative and hospice care into HF management to improve quality of life and support holistic care for patients and their families. By clarifying the role of palliative care in HF and proposing practical referral criteria, this position statement aims to bridge the gap between HF and palliative care services in South Korea, ultimately improving patient-centered outcomes and aligning treatment with the goals and values of HF patients.

Background and Objectives: Angiographic assessment of coronary stenosis severity using quantitative coronary angiography (QCA) is often inconsistent with that based on fractional flow reserve (FFR) or intravascular ultrasound (IVUS). We investigated the incidence of discrepancies between QCA and FFR or IVUS, and the outcomes of FFR- and IVUS-guided strategies in discordant coronary lesions. Methods: This study was a post-hoc analysis of the FLAVOUR study. We used a QCA-derived diameter stenosis (DS) of 60% or greater, the highest tertile, to classify coronary lesions as concordant or discordant with FFR or IVUS criteria for percutaneous coronary intervention (PCI). The patient-oriented composite outcome (POCO) was defined as a composite of death, myocardial infarction, or revascularization at 24 months. Results: The discordance rate between QCA and FFR or IVUS was 30.2% (n=551). The QCAFFR discordance rate was numerically lower than the QCA-IVUS discordance rate (28.2% vs. 32.4%, p=0.050). In 200 patients with ≥60% DS, PCI was deferred according to negative FFR (n=141) and negative IVUS (n=59) (15.3% vs. 6.5%, p<0.001). The POCO incidence was comparable between the FFR- and IVUS-guided deferral strategies (5.9% vs. 3.4%, p=0.479).Conversely, 351 patients with DS <60% underwent PCI according to positive FFR (n=118) and positive IVUS (n=233) (12.8% vs. 25.9%, p<0.001). FFR- and IVUS-guided PCI did not differ in the incidence of POCO (9.5% vs. 6.5%, p=0.294). Conclusions The proportion of QCA-FFR or IVUS discordance was approximately one third for intermediate coronary lesions. FFR- or IVUS-guided strategies for these lesions were comparable with respect to POCO at 24 months.

Background and Objectives: Angiographic assessment of coronary stenosis severity using quantitative coronary angiography (QCA) is often inconsistent with that based on fractional flow reserve (FFR) or intravascular ultrasound (IVUS). We investigated the incidence of discrepancies between QCA and FFR or IVUS, and the outcomes of FFR- and IVUS-guided strategies in discordant coronary lesions. Methods: This study was a post-hoc analysis of the FLAVOUR study. We used a QCA-derived diameter stenosis (DS) of 60% or greater, the highest tertile, to classify coronary lesions as concordant or discordant with FFR or IVUS criteria for percutaneous coronary intervention (PCI). The patient-oriented composite outcome (POCO) was defined as a composite of death, myocardial infarction, or revascularization at 24 months. Results: The discordance rate between QCA and FFR or IVUS was 30.2% (n=551). The QCAFFR discordance rate was numerically lower than the QCA-IVUS discordance rate (28.2% vs. 32.4%, p=0.050). In 200 patients with ≥60% DS, PCI was deferred according to negative FFR (n=141) and negative IVUS (n=59) (15.3% vs. 6.5%, p<0.001). The POCO incidence was comparable between the FFR- and IVUS-guided deferral strategies (5.9% vs. 3.4%, p=0.479).Conversely, 351 patients with DS <60% underwent PCI according to positive FFR (n=118) and positive IVUS (n=233) (12.8% vs. 25.9%, p<0.001). FFR- and IVUS-guided PCI did not differ in the incidence of POCO (9.5% vs. 6.5%, p=0.294). Conclusions The proportion of QCA-FFR or IVUS discordance was approximately one third for intermediate coronary lesions. FFR- or IVUS-guided strategies for these lesions were comparable with respect to POCO at 24 months.

Background: Thyroid function tests (TFT) produce varying results depending on the method, complicating standardization due to the lack of reference materials and methods. This study aims to harmonize TFT methods by deriving a recalibration equation using percentile transformation. Methods: Data from the Korean Association of External Quality Assessment Service (2017–2020) were analyzed, focusing on the three most used automated immunoassay analyzers. Outliers were excluded, and data were transformed into percentiles. A recalibration equation was derived through regression analysis, and the harmonization of results before and after recalibration was evaluated. Clinical sample measurements using the three methods and their reference intervals were applied to the recalibration equation. Results: Before recalibration, significant differences between methods were observed: 1.08 to 2.67 μIU/mL thyroid-stimulating hormone (TSH), 0.17 to 0.49 ng/mL triiodothyronine (T3), and 0.08 to 0.63 ng/dL free thyroxine (FT4).After recalibration, these differences were significantly reduced to 0.09 to 0.23 μIU/mL TSH, 0.002 to 0.006 ng/mL T3, and −0.01 to 0.02 ng/dL FT4.The distribution of clinical sample results remained consistent based on the reference interval before and after recalibration. However, differences persisted when applying clinical sample results to the recalibration equation. The difference in the TSH reference interval increased after recalibration, whereas the FT4 reference interval aligned more closely between methods. Conclusions Future studies should include multiple centers, sufficient clinical samples with various result levels, and multiple reagent lots. These studies should derive recalibration equations, and results from healthy individuals using various methods should be applied to establish a common reference interval.

Background: Thyroid function tests (TFT) produce varying results depending on the method, complicating standardization due to the lack of reference materials and methods. This study aims to harmonize TFT methods by deriving a recalibration equation using percentile transformation. Methods: Data from the Korean Association of External Quality Assessment Service (2017–2020) were analyzed, focusing on the three most used automated immunoassay analyzers. Outliers were excluded, and data were transformed into percentiles. A recalibration equation was derived through regression analysis, and the harmonization of results before and after recalibration was evaluated. Clinical sample measurements using the three methods and their reference intervals were applied to the recalibration equation. Results: Before recalibration, significant differences between methods were observed: 1.08 to 2.67 μIU/mL thyroid-stimulating hormone (TSH), 0.17 to 0.49 ng/mL triiodothyronine (T3), and 0.08 to 0.63 ng/dL free thyroxine (FT4).After recalibration, these differences were significantly reduced to 0.09 to 0.23 μIU/mL TSH, 0.002 to 0.006 ng/mL T3, and −0.01 to 0.02 ng/dL FT4.The distribution of clinical sample results remained consistent based on the reference interval before and after recalibration. However, differences persisted when applying clinical sample results to the recalibration equation. The difference in the TSH reference interval increased after recalibration, whereas the FT4 reference interval aligned more closely between methods. Conclusions Future studies should include multiple centers, sufficient clinical samples with various result levels, and multiple reagent lots. These studies should derive recalibration equations, and results from healthy individuals using various methods should be applied to establish a common reference interval.

Background: Thyroid function tests (TFT) produce varying results depending on the method, complicating standardization due to the lack of reference materials and methods. This study aims to harmonize TFT methods by deriving a recalibration equation using percentile transformation. Methods: Data from the Korean Association of External Quality Assessment Service (2017–2020) were analyzed, focusing on the three most used automated immunoassay analyzers. Outliers were excluded, and data were transformed into percentiles. A recalibration equation was derived through regression analysis, and the harmonization of results before and after recalibration was evaluated. Clinical sample measurements using the three methods and their reference intervals were applied to the recalibration equation. Results: Before recalibration, significant differences between methods were observed: 1.08 to 2.67 μIU/mL thyroid-stimulating hormone (TSH), 0.17 to 0.49 ng/mL triiodothyronine (T3), and 0.08 to 0.63 ng/dL free thyroxine (FT4).After recalibration, these differences were significantly reduced to 0.09 to 0.23 μIU/mL TSH, 0.002 to 0.006 ng/mL T3, and −0.01 to 0.02 ng/dL FT4.The distribution of clinical sample results remained consistent based on the reference interval before and after recalibration. However, differences persisted when applying clinical sample results to the recalibration equation. The difference in the TSH reference interval increased after recalibration, whereas the FT4 reference interval aligned more closely between methods. Conclusions Future studies should include multiple centers, sufficient clinical samples with various result levels, and multiple reagent lots. These studies should derive recalibration equations, and results from healthy individuals using various methods should be applied to establish a common reference interval.

Background and Objectives: Angiographic assessment of coronary stenosis severity using quantitative coronary angiography (QCA) is often inconsistent with that based on fractional flow reserve (FFR) or intravascular ultrasound (IVUS). We investigated the incidence of discrepancies between QCA and FFR or IVUS, and the outcomes of FFR- and IVUS-guided strategies in discordant coronary lesions. Methods: This study was a post-hoc analysis of the FLAVOUR study. We used a QCA-derived diameter stenosis (DS) of 60% or greater, the highest tertile, to classify coronary lesions as concordant or discordant with FFR or IVUS criteria for percutaneous coronary intervention (PCI). The patient-oriented composite outcome (POCO) was defined as a composite of death, myocardial infarction, or revascularization at 24 months. Results: The discordance rate between QCA and FFR or IVUS was 30.2% (n=551). The QCAFFR discordance rate was numerically lower than the QCA-IVUS discordance rate (28.2% vs. 32.4%, p=0.050). In 200 patients with ≥60% DS, PCI was deferred according to negative FFR (n=141) and negative IVUS (n=59) (15.3% vs. 6.5%, p<0.001). The POCO incidence was comparable between the FFR- and IVUS-guided deferral strategies (5.9% vs. 3.4%, p=0.479).Conversely, 351 patients with DS <60% underwent PCI according to positive FFR (n=118) and positive IVUS (n=233) (12.8% vs. 25.9%, p<0.001). FFR- and IVUS-guided PCI did not differ in the incidence of POCO (9.5% vs. 6.5%, p=0.294). Conclusions The proportion of QCA-FFR or IVUS discordance was approximately one third for intermediate coronary lesions. FFR- or IVUS-guided strategies for these lesions were comparable with respect to POCO at 24 months.

Background: Thyroid function tests (TFT) produce varying results depending on the method, complicating standardization due to the lack of reference materials and methods. This study aims to harmonize TFT methods by deriving a recalibration equation using percentile transformation. Methods: Data from the Korean Association of External Quality Assessment Service (2017–2020) were analyzed, focusing on the three most used automated immunoassay analyzers. Outliers were excluded, and data were transformed into percentiles. A recalibration equation was derived through regression analysis, and the harmonization of results before and after recalibration was evaluated. Clinical sample measurements using the three methods and their reference intervals were applied to the recalibration equation. Results: Before recalibration, significant differences between methods were observed: 1.08 to 2.67 μIU/mL thyroid-stimulating hormone (TSH), 0.17 to 0.49 ng/mL triiodothyronine (T3), and 0.08 to 0.63 ng/dL free thyroxine (FT4).After recalibration, these differences were significantly reduced to 0.09 to 0.23 μIU/mL TSH, 0.002 to 0.006 ng/mL T3, and −0.01 to 0.02 ng/dL FT4.The distribution of clinical sample results remained consistent based on the reference interval before and after recalibration. However, differences persisted when applying clinical sample results to the recalibration equation. The difference in the TSH reference interval increased after recalibration, whereas the FT4 reference interval aligned more closely between methods. Conclusions Future studies should include multiple centers, sufficient clinical samples with various result levels, and multiple reagent lots. These studies should derive recalibration equations, and results from healthy individuals using various methods should be applied to establish a common reference interval.

Background and Objectives: Angiographic assessment of coronary stenosis severity using quantitative coronary angiography (QCA) is often inconsistent with that based on fractional flow reserve (FFR) or intravascular ultrasound (IVUS). We investigated the incidence of discrepancies between QCA and FFR or IVUS, and the outcomes of FFR- and IVUS-guided strategies in discordant coronary lesions. Methods: This study was a post-hoc analysis of the FLAVOUR study. We used a QCA-derived diameter stenosis (DS) of 60% or greater, the highest tertile, to classify coronary lesions as concordant or discordant with FFR or IVUS criteria for percutaneous coronary intervention (PCI). The patient-oriented composite outcome (POCO) was defined as a composite of death, myocardial infarction, or revascularization at 24 months. Results: The discordance rate between QCA and FFR or IVUS was 30.2% (n=551). The QCAFFR discordance rate was numerically lower than the QCA-IVUS discordance rate (28.2% vs. 32.4%, p=0.050). In 200 patients with ≥60% DS, PCI was deferred according to negative FFR (n=141) and negative IVUS (n=59) (15.3% vs. 6.5%, p<0.001). The POCO incidence was comparable between the FFR- and IVUS-guided deferral strategies (5.9% vs. 3.4%, p=0.479).Conversely, 351 patients with DS <60% underwent PCI according to positive FFR (n=118) and positive IVUS (n=233) (12.8% vs. 25.9%, p<0.001). FFR- and IVUS-guided PCI did not differ in the incidence of POCO (9.5% vs. 6.5%, p=0.294). Conclusions The proportion of QCA-FFR or IVUS discordance was approximately one third for intermediate coronary lesions. FFR- or IVUS-guided strategies for these lesions were comparable with respect to POCO at 24 months.

Background: Thyroid function tests (TFT) produce varying results depending on the method, complicating standardization due to the lack of reference materials and methods. This study aims to harmonize TFT methods by deriving a recalibration equation using percentile transformation. Methods: Data from the Korean Association of External Quality Assessment Service (2017–2020) were analyzed, focusing on the three most used automated immunoassay analyzers. Outliers were excluded, and data were transformed into percentiles. A recalibration equation was derived through regression analysis, and the harmonization of results before and after recalibration was evaluated. Clinical sample measurements using the three methods and their reference intervals were applied to the recalibration equation. Results: Before recalibration, significant differences between methods were observed: 1.08 to 2.67 μIU/mL thyroid-stimulating hormone (TSH), 0.17 to 0.49 ng/mL triiodothyronine (T3), and 0.08 to 0.63 ng/dL free thyroxine (FT4).After recalibration, these differences were significantly reduced to 0.09 to 0.23 μIU/mL TSH, 0.002 to 0.006 ng/mL T3, and −0.01 to 0.02 ng/dL FT4.The distribution of clinical sample results remained consistent based on the reference interval before and after recalibration. However, differences persisted when applying clinical sample results to the recalibration equation. The difference in the TSH reference interval increased after recalibration, whereas the FT4 reference interval aligned more closely between methods. Conclusions Future studies should include multiple centers, sufficient clinical samples with various result levels, and multiple reagent lots. These studies should derive recalibration equations, and results from healthy individuals using various methods should be applied to establish a common reference interval.