Vaccines are highly effective, but rare or delayed adverse events following immunization (AEFIs) require post-licensure surveillance beyond clinical trials. Korea lacks a comprehensive, active, database-based framework, yet key assets exist: nationwide claims databases (National Health Insurance Service/Health Insurance Review and Assessment Service), the national immunization registry (Korea Disease Control and Prevention Agency’s Immunization Registry Information System) for National Immunization Program (NIP) and non-NIP vaccines, and increasingly standardized hospital electronic health records.We propose a federated, code to data architecture with data linkages between these data.Implementation should adopt a common data model (CDM), standardized case definitions, latency accounting, and transparent public reporting under strong privacy governance. Major challenges include multi step administrative approvals for data linkage, incomplete capture of adult non-NIP vaccinations, heterogeneous hospital data structures, and strict data protection constraints. Strategic priorities are to streamline statutory and administrative processes for public health use, mandate or enable claims-based capture of adult vaccinations, enhance CDM based interoperability, and develop secure hubs for aggregated outputs. With these measures, Korea will be well positioned to establish a scalable active surveillance system capable of detecting rare AEFIs, supporting transparent and evidence-based communication, and ensuring equitable injury compensation grounded in domestic data.

South Korea’s current vaccination policies leave a surveillance gap for non-National Immunization Program (NIP) vaccines. In this study, we proposed a sentinel surveillance approach for monitoring the safety of non-NIP vaccines. Vaccination data were collected retrospectively among patients hospitalized with pre-defined adverse events of special interest (AESI) by reviewing electronic medical records in five university hospitals. This approach incorporates expert assessment to determine the causal relationship. We confirmed that 16 patients had received non-NIP vaccines among 860 patients diagnosed with AESI.We concluded one case of preeclampsia was possibly related to tetanus-diphtheria-pertussis vaccination. We propose a multi-hospital-based, retrospective assessment system for predefined AESIs as an alternative to active vaccine safety monitoring method. These efforts are expected to enhance both the accuracy and timeliness of safety monitoring in South Korea.

South Korea’s current vaccination policies leave a surveillance gap for non-National Immunization Program (NIP) vaccines. In this study, we proposed a sentinel surveillance approach for monitoring the safety of non-NIP vaccines. Vaccination data were collected retrospectively among patients hospitalized with pre-defined adverse events of special interest (AESI) by reviewing electronic medical records in five university hospitals. This approach incorporates expert assessment to determine the causal relationship. We confirmed that 16 patients had received non-NIP vaccines among 860 patients diagnosed with AESI.We concluded one case of preeclampsia was possibly related to tetanus-diphtheria-pertussis vaccination. We propose a multi-hospital-based, retrospective assessment system for predefined AESIs as an alternative to active vaccine safety monitoring method. These efforts are expected to enhance both the accuracy and timeliness of safety monitoring in South Korea.

Purpose: Determining the extent of radical lymphadenectomy at clinical early stage is challenging. We aimed to investigate the appropriate extent of lymphadenectomy in clinical early-stage right colon cancer. Methods: Patients with clinical stage 0 or I right colon cancer who underwent curative surgery from January 2007 to December 2021 were included in this retrospective study. The extent of lymph node (LN) metastases based on the distribution of LN metastases (LND: LND1 pericolic nodes, LND2 intermediate nodes, LND3 apical nodes), along with the depth of submucosal (SM) invasion (classed into SM1–3), were analyzed. Results: Of the 348 patients, distribution across pathologic stages was as follows: 30 patients (8.6%) at stage 0, 207 (59.5%) at stage I, 52 (14.9%) at stage II, and 59 (17.0%) at stage III. In pT1 tumor patients, LN metastases varied by SM invasion depth: 3.6% in SM1 (all LND1), 5.1% in SM2 (all LND1), and 17.5% in SM3 (LND1 10%, LND2 5%, LND3 2.5%). For pT2, pT3, and pT4 stages, LN metastasis rates were 16.2% (LND1 11.3%, LND2 3.8%, LND3 1.3%), 39.7% (LND1 28.9%, LND2 8.4%, LND3 2.4%), and 50% (LND1 25%, LND2 25%), respectively. Tumor invasion depth and lymphovascular invasion were identified as significant risk factors for LN metastasis extending to LND2–3. Conclusion Complete mesocolic excision should be considered for right-sided colon cancer because tumor infiltration deeper than SM2 could metastasize to LND2 or further. If preoperative endoscopy confirms SM1 or SM2 invasion, D2 lymphadenectomy could be a limited surgical option.

Purpose: Determining the extent of radical lymphadenectomy at clinical early stage is challenging. We aimed to investigate the appropriate extent of lymphadenectomy in clinical early-stage right colon cancer. Methods: Patients with clinical stage 0 or I right colon cancer who underwent curative surgery from January 2007 to December 2021 were included in this retrospective study. The extent of lymph node (LN) metastases based on the distribution of LN metastases (LND: LND1 pericolic nodes, LND2 intermediate nodes, LND3 apical nodes), along with the depth of submucosal (SM) invasion (classed into SM1–3), were analyzed. Results: Of the 348 patients, distribution across pathologic stages was as follows: 30 patients (8.6%) at stage 0, 207 (59.5%) at stage I, 52 (14.9%) at stage II, and 59 (17.0%) at stage III. In pT1 tumor patients, LN metastases varied by SM invasion depth: 3.6% in SM1 (all LND1), 5.1% in SM2 (all LND1), and 17.5% in SM3 (LND1 10%, LND2 5%, LND3 2.5%). For pT2, pT3, and pT4 stages, LN metastasis rates were 16.2% (LND1 11.3%, LND2 3.8%, LND3 1.3%), 39.7% (LND1 28.9%, LND2 8.4%, LND3 2.4%), and 50% (LND1 25%, LND2 25%), respectively. Tumor invasion depth and lymphovascular invasion were identified as significant risk factors for LN metastasis extending to LND2–3. Conclusion Complete mesocolic excision should be considered for right-sided colon cancer because tumor infiltration deeper than SM2 could metastasize to LND2 or further. If preoperative endoscopy confirms SM1 or SM2 invasion, D2 lymphadenectomy could be a limited surgical option.

South Korea’s current vaccination policies leave a surveillance gap for non-National Immunization Program (NIP) vaccines. In this study, we proposed a sentinel surveillance approach for monitoring the safety of non-NIP vaccines. Vaccination data were collected retrospectively among patients hospitalized with pre-defined adverse events of special interest (AESI) by reviewing electronic medical records in five university hospitals. This approach incorporates expert assessment to determine the causal relationship. We confirmed that 16 patients had received non-NIP vaccines among 860 patients diagnosed with AESI.We concluded one case of preeclampsia was possibly related to tetanus-diphtheria-pertussis vaccination. We propose a multi-hospital-based, retrospective assessment system for predefined AESIs as an alternative to active vaccine safety monitoring method. These efforts are expected to enhance both the accuracy and timeliness of safety monitoring in South Korea.

Purpose: Determining the extent of radical lymphadenectomy at clinical early stage is challenging. We aimed to investigate the appropriate extent of lymphadenectomy in clinical early-stage right colon cancer. Methods: Patients with clinical stage 0 or I right colon cancer who underwent curative surgery from January 2007 to December 2021 were included in this retrospective study. The extent of lymph node (LN) metastases based on the distribution of LN metastases (LND: LND1 pericolic nodes, LND2 intermediate nodes, LND3 apical nodes), along with the depth of submucosal (SM) invasion (classed into SM1–3), were analyzed. Results: Of the 348 patients, distribution across pathologic stages was as follows: 30 patients (8.6%) at stage 0, 207 (59.5%) at stage I, 52 (14.9%) at stage II, and 59 (17.0%) at stage III. In pT1 tumor patients, LN metastases varied by SM invasion depth: 3.6% in SM1 (all LND1), 5.1% in SM2 (all LND1), and 17.5% in SM3 (LND1 10%, LND2 5%, LND3 2.5%). For pT2, pT3, and pT4 stages, LN metastasis rates were 16.2% (LND1 11.3%, LND2 3.8%, LND3 1.3%), 39.7% (LND1 28.9%, LND2 8.4%, LND3 2.4%), and 50% (LND1 25%, LND2 25%), respectively. Tumor invasion depth and lymphovascular invasion were identified as significant risk factors for LN metastasis extending to LND2–3. Conclusion Complete mesocolic excision should be considered for right-sided colon cancer because tumor infiltration deeper than SM2 could metastasize to LND2 or further. If preoperative endoscopy confirms SM1 or SM2 invasion, D2 lymphadenectomy could be a limited surgical option.

South Korea’s current vaccination policies leave a surveillance gap for non-National Immunization Program (NIP) vaccines. In this study, we proposed a sentinel surveillance approach for monitoring the safety of non-NIP vaccines. Vaccination data were collected retrospectively among patients hospitalized with pre-defined adverse events of special interest (AESI) by reviewing electronic medical records in five university hospitals. This approach incorporates expert assessment to determine the causal relationship. We confirmed that 16 patients had received non-NIP vaccines among 860 patients diagnosed with AESI.We concluded one case of preeclampsia was possibly related to tetanus-diphtheria-pertussis vaccination. We propose a multi-hospital-based, retrospective assessment system for predefined AESIs as an alternative to active vaccine safety monitoring method. These efforts are expected to enhance both the accuracy and timeliness of safety monitoring in South Korea.

Purpose: The objective of this study was to propose a deep-learning model for the detection of the mandibular canal on dental panoramic radiographs. Materials and Methods: A total of 2,100 panoramic radiographs (PANs) were collected from 3 different machines: RAYSCAN Alpha (n=700, PAN A), OP-100 (n=700, PAN B), and CS8100 (n=700, PAN C). Initially, an oral and maxillofacial radiologist coarsely annotated the mandibular canals. For deep learning analysis, convolutional neural networks (CNNs) utilizing U-Net architecture were employed for automated canal segmentation. Seven independent networks were trained using training sets representing all possible combinations of the 3 groups. These networks were then assessed using a hold-out test dataset. Results: Among the 7 networks evaluated, the network trained with all 3 available groups achieved an average precision of 90.6%, a recall of 87.4%, and a Dice similarity coefficient (DSC) of 88.9%. The 3 networks trained using each of the 3 possible 2-group combinations also demonstrated reliable performance for mandibular canal segmentation, as follows: 1) PAN A and B exhibited a mean DSC of 87.9%, 2) PAN A and C displayed a mean DSC of 87.8%, and 3) PAN B and C demonstrated a mean DSC of 88.4%. Conclusion This multi-device study indicated that the examined CNN-based deep learning approach can achieve excellent canal segmentation performance, with a DSC exceeding 88%. Furthermore, the study highlighted the importance of considering the characteristics of panoramic radiographs when developing a robust deep-learning network, rather than depending solely on the size of the dataset.