Background: This study aimed to identify key priorities for the development of guidelines for information and communication technology (ICT)-based patient education tailored to the needs of patients with rheumatic diseases (RDs) in the Republic of Korea, based on expert consensus. Methods: A two-round modified Delphi study was conducted with 20 rheumatology, patient education, and digital health literacy experts. A total of 35 items covering 7 domains and 18 subdomains were evaluated. Each item was evaluated for its level of importance, and the responses were rated on a 4-point Likert scale. Consensus levels were defined as “high” (interquartile range [IQR] ≤ 1, agreement ≥ 80%, content validity ratio [CVR] ≥ 0.7), "Moderate" (IQR ≥ 1, agreement 50–79%, CVR 0.5–0.7), and "Low" (IQR > 1, agreement < 50%, CVR < 0.5). Results: Strong consensus was reached for key priorities for developing guidelines in areas such as health literacy, digital health literacy, medical terminology, user interface, and user experience design for mobile apps. Chatbot use and video (e.g., YouTube) also achieved high consensus, whereas AI-powered platforms such as ChatGPT showed moderate-to-high agreement. Telemedicine was excluded because of insufficient consensus. Conclusion The key priorities identified in this study provide a foundation for the development of ICT-based patient education guidelines for RDs in the Republic of Korea.Future efforts should focus on integrating digital tools into clinical practice to enhance patient engagement and improve clinical outcomes.

Background: This study aimed to identify key priorities for the development of guidelines for information and communication technology (ICT)-based patient education tailored to the needs of patients with rheumatic diseases (RDs) in the Republic of Korea, based on expert consensus. Methods: A two-round modified Delphi study was conducted with 20 rheumatology, patient education, and digital health literacy experts. A total of 35 items covering 7 domains and 18 subdomains were evaluated. Each item was evaluated for its level of importance, and the responses were rated on a 4-point Likert scale. Consensus levels were defined as “high” (interquartile range [IQR] ≤ 1, agreement ≥ 80%, content validity ratio [CVR] ≥ 0.7), "Moderate" (IQR ≥ 1, agreement 50–79%, CVR 0.5–0.7), and "Low" (IQR > 1, agreement < 50%, CVR < 0.5). Results: Strong consensus was reached for key priorities for developing guidelines in areas such as health literacy, digital health literacy, medical terminology, user interface, and user experience design for mobile apps. Chatbot use and video (e.g., YouTube) also achieved high consensus, whereas AI-powered platforms such as ChatGPT showed moderate-to-high agreement. Telemedicine was excluded because of insufficient consensus. Conclusion The key priorities identified in this study provide a foundation for the development of ICT-based patient education guidelines for RDs in the Republic of Korea.Future efforts should focus on integrating digital tools into clinical practice to enhance patient engagement and improve clinical outcomes.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: Despite the increase in daily alcohol intake in recent decades and the implementation of national health screenings, effective management strategies for alcohol consumption remain outdated. This review evaluates intervention studies on screening and behavioral counseling for unhealthy alcohol use, with the aim of enhancing the effectiveness of interventions and improving health outcomes. Methods: On the basis of the GRADE (Grading of Recommendations Assessment, Development, and Evaluation)- ADOLOPMENT framework, systematic reviews and randomized controlled trials were examined to investigate the effectiveness of screening and counseling interventions in reducing unhealthy alcohol use. Five key questions were generated, and an evaluation and quality assessment of existing systematic reviews and new evidence related to each key question were conducted. Results: Updating the U.S. Preventive Services Task Force and Cochrane 2018 reviews, we identified five new randomized trials that evaluated screening and counseling interventions for unhealthy alcohol use. For Key Question 2, the sensitivity and specificity of the new screening studies were consistent with those of prior research. Brief interventions were confirmed to reduce alcohol use (Key Question 4a), although additional research is required for a wider array of health outcomes. One study highlighted the benefits of counseling interventions for newborn health indicators in pregnant women (Key Question 4b). No new evidence was found regarding the harms of screening (Key Question 3) or alcohol use reduction interventions (Key Question 5). Conclusion This review supports the continued use of brief interventions to reduce alcohol consumption in highrisk groups and highlights the need for culturally tailored research in Korea.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.