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.

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.

Following the previous study, which investigated the pharmacological properties of the Technekitty injection (Tc-99m), the toxicity of a single intravenous administration of the Technekittyinjection (Tc-99m) and the side effects that may occur at the diagnostic dose were confirmed.The Technekitty injection (Tc-99m) was administered intravenously once at a dose of 0, 0.67, 2.0, and 6.0 mCi/kg to 5 male and female rats per group. Mortality, general symptom obser-vation, and weight measurement were performed for 2 weeks, followed by observation of autopsy findings. There were no deaths, and no statistically significant weight change was observed. No abnormal systemic signs related to the Technekitty injection (Tc-99m) were observed. These results confirmed that Technekitty injection (Tc-99m) can be safely admin-istered intravenously at doses up to 6.0 mCi/kg. Additionally, technetium-99m at an average dose of 2 mCi (74 MBq) has been verified as a diagnostic dose without adverse effects, al-lowing the Technekitty injection (Tc-99m) to be used safely without side effects at this dosage.This study demonstrates that the Technekitty injection (Tc-99m) has a wide safety margin, supporting its potential for clinical application. Moreover, these findings align with the nonclin-ical safety standards for radiopharmaceuticals, reinforcing its utility in veterinary medicine.The Technekitty injection (Tc-99m) is expected to be applicable for clinical diagnosis as a vet-erinary drug in Korea.

Thyroid scanning using technetium-99m ( 99mTc) is the gold standard for diagnosing feline hyperthyroidism. In cats with an overactive thyroid, a thyroid scan is the most appropriate imaging technique to detect and localize any hyperfunctional adenomatous thyroid tissue. In this study, the pharmacological properties of the Technekitty injection (Tc-99m), developed as a diagnostic agent for feline hyperthyroidism using 99mTc as an active ingredient, were tested in FRTL-5 thyroid follicular cell line and ICR mice. The percentage of cell uptake of the Tc-99m in FRTL-5 thyroid cells was 0.182 ± 0.018%, which was about 6 times higher compared to Clone 9 hepatocytes. This uptake decreased by 38.2% due to competitive inhibition by iodine (sodium iodide). In tissue distribution tests by using ICR mice, the highest distribution was observed in the liver, kidneys, spleen, lungs, and femur at 0.083 hours after administration, and this distribution decreased as the compound was excreted through the kidneys, the pri-mary excretory organ. Maximum distribution was confirmed at 1 hour in the small intestine, 6hours in the large intestine, and 2 hours in the thyroid gland. Additionally, the total amount excreted through urine and feces over 48 hours (2 days) was 78.80% of the injected dose, with 37.70% (47.84% of the total excretion) excreted through urine and 41.10% (52.16% of the total excretion) through feces. In conclusion, the Tc-99m has the same mechanism of action, potency, absorption, distribution, metabolism, and excretion characteristics as 99mTc used for feline hyperthyroidism in the United States, Europe, and other countries, because the Technekitty injection (Tc-99m) contains 99mTc as its sole active ingredient. Based on these results, the Technekitty injection (Tc-99m) is expected to be safely used in the clinical diagnosis of feline hyperthyroidism.

Background: Bulky or multiple lymph node (LN) metastases are associated with poor prognosis in cervical cancer, and the size or number of LN metastases is not yet reflected in the staging system and therapeutic strategy. Although the therapeutic effects of surgical resection of bulky LNs before standard treatment have been reported in several retrospective studies, wellplanned randomized clinical studies are lacking. Therefore, the aim of the Korean Gynecologic Oncology Group (KGOG) 1047/DEBULK trial is to investigate whether the debulking surgery of bulky or multiple LNs prior to concurrent chemoradiation therapy (CCRT) improves the survival rate of patients with cervical cancer IIICr diagnosed by imaging tests. Methods The KGOG 1047/DEBULK trial is a phase III, multicenter, randomized clinical trial involving patients with bulky or multiple LN metastases in cervical cancer IIICr. This study will include patients with a short-axis diameter of a pelvic or para-aortic LN ≥2 cm or ≥3 LNs with a short-axis diameter ≥1 cm and for whom CCRT is planned. The treatment arms will be randomly allocated in a 1:1 ratio to either receive CCRT (control arm) or undergo surgical debulking of bulky or multiple LNs before CCRT (experimental arm). CCRT consists of extended-field external beam radiotherapy/pelvic radiotherapy, brachytherapy and LN boost, and weekly chemotherapy with cisplatin (40 mg/m 2 ), 4–6 times administered intravenously.The primary endpoint will be 3-year progression-free survival rate. The secondary endpoints will be 3-year overall survival rate, treatment-related complications, and accuracy of radiological diagnosis of bulky or multiple LNs.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Background: Bulky or multiple lymph node (LN) metastases are associated with poor prognosis in cervical cancer, and the size or number of LN metastases is not yet reflected in the staging system and therapeutic strategy. Although the therapeutic effects of surgical resection of bulky LNs before standard treatment have been reported in several retrospective studies, wellplanned randomized clinical studies are lacking. Therefore, the aim of the Korean Gynecologic Oncology Group (KGOG) 1047/DEBULK trial is to investigate whether the debulking surgery of bulky or multiple LNs prior to concurrent chemoradiation therapy (CCRT) improves the survival rate of patients with cervical cancer IIICr diagnosed by imaging tests. Methods The KGOG 1047/DEBULK trial is a phase III, multicenter, randomized clinical trial involving patients with bulky or multiple LN metastases in cervical cancer IIICr. This study will include patients with a short-axis diameter of a pelvic or para-aortic LN ≥2 cm or ≥3 LNs with a short-axis diameter ≥1 cm and for whom CCRT is planned. The treatment arms will be randomly allocated in a 1:1 ratio to either receive CCRT (control arm) or undergo surgical debulking of bulky or multiple LNs before CCRT (experimental arm). CCRT consists of extended-field external beam radiotherapy/pelvic radiotherapy, brachytherapy and LN boost, and weekly chemotherapy with cisplatin (40 mg/m 2 ), 4–6 times administered intravenously.The primary endpoint will be 3-year progression-free survival rate. The secondary endpoints will be 3-year overall survival rate, treatment-related complications, and accuracy of radiological diagnosis of bulky or multiple LNs.

Following the previous study, which investigated the pharmacological properties of the Technekitty injection (Tc-99m), the toxicity of a single intravenous administration of the Technekittyinjection (Tc-99m) and the side effects that may occur at the diagnostic dose were confirmed.The Technekitty injection (Tc-99m) was administered intravenously once at a dose of 0, 0.67, 2.0, and 6.0 mCi/kg to 5 male and female rats per group. Mortality, general symptom obser-vation, and weight measurement were performed for 2 weeks, followed by observation of autopsy findings. There were no deaths, and no statistically significant weight change was observed. No abnormal systemic signs related to the Technekitty injection (Tc-99m) were observed. These results confirmed that Technekitty injection (Tc-99m) can be safely admin-istered intravenously at doses up to 6.0 mCi/kg. Additionally, technetium-99m at an average dose of 2 mCi (74 MBq) has been verified as a diagnostic dose without adverse effects, al-lowing the Technekitty injection (Tc-99m) to be used safely without side effects at this dosage.This study demonstrates that the Technekitty injection (Tc-99m) has a wide safety margin, supporting its potential for clinical application. Moreover, these findings align with the nonclin-ical safety standards for radiopharmaceuticals, reinforcing its utility in veterinary medicine.The Technekitty injection (Tc-99m) is expected to be applicable for clinical diagnosis as a vet-erinary drug in Korea.