Purpose: To investigate the clinical characteristics of South Korean patients with pericentral retinitis pigmentosa (RP) and to identify clinical biomarkers associated with rapid visual acuity decline based on baseline factors. Methods: This retrospective study included 59 eyes of 31 patients diagnosed with pericentral RP. Comprehensive ophthalmological examinations and genetic sequencing were conducted to assess the baseline characteristics. For biomarker analysis, eyes were categorized into two groups based on the annual rate of change in visual acuity. The clinical findings of the two groups were evaluated to identify the biomarkers associated with rapid loss of visual acuity. Results: Patients with pericentral RP in this study exhibited a mean best-corrected visual acuity of 0.17 ± 0.23 in logarithm of the minimum angle of resolution. The visual field test showed annular or semicircular scotoma with relatively preserved periphery and 27 eyes (45.8%) exhibited no macular complications in optical coherence tomography. Genetic analysis identified genes associated with previous typical and pericentral RP studies but also highlighted that many genetic causes of pericentral RP remain unidentified. Of the 55 eyes for which the rate of visual acuity change could be estimated, 18 exhibited an annual decline of ≥10%, whereas 37 showed an annual decline of <10%. Male sex and prolonged b-wave latency on dark-adapted 0.01 electroretinogram correlated with rapid visual acuity decline in the multivariate analysis. Conclusions South Korean patients with pericentral RP exhibited a milder phenotype compared to typical RP patients reported in previous studies. Genetic analysis revealed heterogeneity, with mutations in some genes commonly associated with milder forms of RP. Male sex and prolonged b-wave latency on dark-adapted 0.01 electroretinogram were significant biomarkers for predicting rapid visual acuity decline. Monitoring initial b-wave latency is important for predicting visual decline, particularly in male patients with pericentral RP.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Purpose: To describe the process of systematically developing an integrated health promotion program for school-age children from vulnerable families. Methods: In this study, we applied the first three steps—analysis, design, and development (ADD)—of the analysis, design, development, implementation, and evaluation (ADDIE) model. The analysis step involved a literature review and needs assessment. In the design step, program components were considered and a program draft was developed. The program content was modified based on expert validation in the development step. The preliminary program was administered in the implementation step, and the final program was confirmed in the evaluation step. Results: The program contents were based on the literature review, needs assessment, and Ryan’s integrated theory of health behavior change. The content was valid, and the educational material was appropriate for school-age children from vulnerable families. The finalized program consists of six sessions to promote physical, psychological, and social health using individual/group and face-to-face/online methods, including two that involve both parents and children. Conclusion This study presents a detailed description of how the program was developed and illustrates the critical elements that should be considered during similar program development. The effect of this program on health promotion behavior should be examined in future research.

Purpose: To investigate the clinical characteristics of South Korean patients with pericentral retinitis pigmentosa (RP) and to identify clinical biomarkers associated with rapid visual acuity decline based on baseline factors. Methods: This retrospective study included 59 eyes of 31 patients diagnosed with pericentral RP. Comprehensive ophthalmological examinations and genetic sequencing were conducted to assess the baseline characteristics. For biomarker analysis, eyes were categorized into two groups based on the annual rate of change in visual acuity. The clinical findings of the two groups were evaluated to identify the biomarkers associated with rapid loss of visual acuity. Results: Patients with pericentral RP in this study exhibited a mean best-corrected visual acuity of 0.17 ± 0.23 in logarithm of the minimum angle of resolution. The visual field test showed annular or semicircular scotoma with relatively preserved periphery and 27 eyes (45.8%) exhibited no macular complications in optical coherence tomography. Genetic analysis identified genes associated with previous typical and pericentral RP studies but also highlighted that many genetic causes of pericentral RP remain unidentified. Of the 55 eyes for which the rate of visual acuity change could be estimated, 18 exhibited an annual decline of ≥10%, whereas 37 showed an annual decline of <10%. Male sex and prolonged b-wave latency on dark-adapted 0.01 electroretinogram correlated with rapid visual acuity decline in the multivariate analysis. Conclusions South Korean patients with pericentral RP exhibited a milder phenotype compared to typical RP patients reported in previous studies. Genetic analysis revealed heterogeneity, with mutations in some genes commonly associated with milder forms of RP. Male sex and prolonged b-wave latency on dark-adapted 0.01 electroretinogram were significant biomarkers for predicting rapid visual acuity decline. Monitoring initial b-wave latency is important for predicting visual decline, particularly in male patients with pericentral RP.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Purpose: To investigate the clinical characteristics of South Korean patients with pericentral retinitis pigmentosa (RP) and to identify clinical biomarkers associated with rapid visual acuity decline based on baseline factors. Methods: This retrospective study included 59 eyes of 31 patients diagnosed with pericentral RP. Comprehensive ophthalmological examinations and genetic sequencing were conducted to assess the baseline characteristics. For biomarker analysis, eyes were categorized into two groups based on the annual rate of change in visual acuity. The clinical findings of the two groups were evaluated to identify the biomarkers associated with rapid loss of visual acuity. Results: Patients with pericentral RP in this study exhibited a mean best-corrected visual acuity of 0.17 ± 0.23 in logarithm of the minimum angle of resolution. The visual field test showed annular or semicircular scotoma with relatively preserved periphery and 27 eyes (45.8%) exhibited no macular complications in optical coherence tomography. Genetic analysis identified genes associated with previous typical and pericentral RP studies but also highlighted that many genetic causes of pericentral RP remain unidentified. Of the 55 eyes for which the rate of visual acuity change could be estimated, 18 exhibited an annual decline of ≥10%, whereas 37 showed an annual decline of <10%. Male sex and prolonged b-wave latency on dark-adapted 0.01 electroretinogram correlated with rapid visual acuity decline in the multivariate analysis. Conclusions South Korean patients with pericentral RP exhibited a milder phenotype compared to typical RP patients reported in previous studies. Genetic analysis revealed heterogeneity, with mutations in some genes commonly associated with milder forms of RP. Male sex and prolonged b-wave latency on dark-adapted 0.01 electroretinogram were significant biomarkers for predicting rapid visual acuity decline. Monitoring initial b-wave latency is important for predicting visual decline, particularly in male patients with pericentral RP.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Purpose: To describe the process of systematically developing an integrated health promotion program for school-age children from vulnerable families. Methods: In this study, we applied the first three steps—analysis, design, and development (ADD)—of the analysis, design, development, implementation, and evaluation (ADDIE) model. The analysis step involved a literature review and needs assessment. In the design step, program components were considered and a program draft was developed. The program content was modified based on expert validation in the development step. The preliminary program was administered in the implementation step, and the final program was confirmed in the evaluation step. Results: The program contents were based on the literature review, needs assessment, and Ryan’s integrated theory of health behavior change. The content was valid, and the educational material was appropriate for school-age children from vulnerable families. The finalized program consists of six sessions to promote physical, psychological, and social health using individual/group and face-to-face/online methods, including two that involve both parents and children. Conclusion This study presents a detailed description of how the program was developed and illustrates the critical elements that should be considered during similar program development. The effect of this program on health promotion behavior should be examined in future research.