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.

Background: Radioactive iodine treatment (RAIT) is an essential therapy for differentiated thyroid cancer. However, unforeseen complications arising during thyroid hormone withdrawal (THW) can lead to Cancellation of the scheduled treatment. This study aimed to identify cases in which THW-RAIT was discontinued due to THW-related complications and to explore potentially preventable causes to improve patient management. Methods: Among 4,174 patients who underwent THW-RAIT between 2012 and 2024, 39 did not complete the planned treatment. After excluding Cancellations unrelated to THW, 11 (0.26%) patients with unexpected THW-related medical issues were analyzed. Results: The median age of the included patients was 61 years (range, 23 to 70), and 10 were male. The reasons for THW-RAIT Cancellation were hyponatremia (n=1), abnormal liver function (n=1), renal dysfunction (n=3), and combined liver and renal dysfunction (n=6). The patient with hyponatremia was taking a thiazide diuretic. Most cases of liver dysfunction were associated with prior use of herbal medications, whereas renal dysfunction was linked to diuretic or nonsteroidal anti-inflammatory drug use, pre-existing conditions such as single kidney or diabetic nephropathy, or inadequate oral intake during low-iodine preparation. Two cases of concurrent liver and renal dysfunction were attributed to rhabdomyolysis following intense exercise or heavy physical labor. Conclusion Enhanced patient education, comprehensive pre-treatment assessment, and careful avoidance of high-risk medications are essential to prevent THW-related complications and minimize disruptions in RAIT.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.