Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Objective: Mental health is a global concern and needs to be studied more closely. We aimed to estimate the prevalence of mental disorders and their associated factors among the general population in Korea. Methods: The National Mental Health Survey of Korea 2021 was conducted between June 19 and August 31, 2021 and included 13,530 households; 5,511 participants completed the interview (response rate: 40.7%). The lifetime and 12-month diagnosis rates of mental disorders were made using the Korean version of the Composite International Diagnostic Interview 2.1. Factors associated with alcohol use disorder (AUD), nicotine use disorder, depressive disorder, and anxiety disorder were analyzed, and mental health service utilization rates were estimated. Results: The lifetime prevalence of mental disorders was 27.8%. The 12-month prevalence rates of alcohol use, nicotine use, depressive, and anxiety disorders were 2.6%, 2.7%, 1.7%, and 3.1%, respectively. The risk factors associated with 12-month diagnosis rates were as follows: AUD: sex and age; nicotine use disorder: sex; depressive disorder: marital status and job status; anxiety disorder: sex, marital status, and job status. The 12-month treatment and service utilization rates for 12-month AUD, nicotine use disorder, depressive disorder, and anxiety disorder were 2.6%, 1.1%, 28.2%, and 9.1%, respectively. Conclusion Approximately 25% of adults in the general population were diagnosed with mental disorders during their lifetime. The treatment rates were substantially low. Future studies on this topic and efforts to increase the mental health treatment rate at a national level are needed.

Purpose: We investigated whether response classification after total thyroidectomy and radioactive iodine (RAI) therapy could be affected by serum levels of recombinant human thyrotropin (rhTSH)-stimulated thyroglobulin (Tg) measured at different time points in a follow-up of patients with papillary thyroid carcinoma (PTC). Methods: A total of 147 PTC patients underwent serum Tg measurement for response assessment 6 to 24 months after the first RAI therapy. Serum Tg levels were measured at 24 h (D1Tg) and 48–72 h (D2-3Tg) after the 2nd injection of rhTSH. Responses were classified into three categories based on serum Tg corresponding to the excellent response (ER-Tg), indeterminate response (IR-Tg), and biochemical incomplete response (BIR-Tg). The distribution pattern of response classification based on serum Tg at different time points (D1Tg vs. D2-3Tg) was compared. Results: Serum D2-3Tg level was higher than D1Tg level (0.339 ng/mL vs. 0.239 ng/mL, P < 0.001). The distribution of response categories was not significantly different between D1Tg-based and D2-3Tg-based classification. However, 8 of 103 (7.8%) patients and 3 of 40 (7.5%) patients initially categorized as ER-Tg and IR-Tg based on D1Tg, respectively, were reclassified to IR-Tg and BIR-Tg based on D2-3Tg, respectively. The optimal cutoff values of D1Tg for the change of response categories were 0.557 ng/mL (from ER-Tg to IR-Tg) and 6.845 ng/mL (from IR-Tg to BIR-Tg). Conclusion D1Tg measurement was sufficient to assess the therapeutic response in most patients with low level of D1Tg. Nevertheless, D2-3Tg measurement was still necessary in the patients with D1Tg higher than a certain level as response classification based on D2-3Tg could change.

Purpose: We investigated the clinical role of F-18 fluorodeoxyglucose (FDG) positron emission tomography-computed tomography(PET-CT) in the identification of the primary site and the selection of the optimal biopsy site in patients with suspectedbone metastasis of unknown primary site. Methods: The patients with suspected bone metastasis who underwent PET-CT for evaluation of primary site were enrolled inthis study. The primary sites were identified by the histopathologic or imaging studies and were classified according to the FDGuptake positivity of the primary site. To evaluate the guiding capability of PET-CT in biopsy site selection, we statisticallyanalyzed whether the biopsy site could be affected according to the presence of extra-skeletal FDG uptake. Results: Among 74 enrolled patients, 51 patients had a metastatic bone disease. The primary site was identified in 48 of 51patients (94.1%). Forty-six patients were eligible to test the association of clinical choice of biopsy site with PET positivity ofextra-skeletal lesion. The extra-skeletal biopsies were done in 42 out of 43 patients with positive extra-skeletal uptake lesions.Bone biopsies were inevitably performed in the other three patients without extra-skeletal uptake lesions. The association cameout to be significant (Fisher’s exact test, P< 0.001). Conclusion F-18 FDG PET-CT significantly contributed not only to identify the primary site but also to suggest optimal biopsysites in patients with suspected bone metastasis.

OBJECTIVE: Concerns over behavioral and emotional problems caused by excessive internet usage have been developed. This study intended to develop and a standardize questionnaire that can efficiently identify at-risk internet users through their internet usage habits. METHODS: Participants (n=158) were recruited at six I-will-centers located in Seoul, South Korea. From the initial 36 questionnaire item pool, 28 preliminary items were selected through expert evaluation and panel discussions. The construct validity, internal consistency, and concurrent validity were examined. We also conducted Receiver Operating Curve (ROC) analysis to assess diagnostic ability of the Internet Overuse Screening-Questionnaire (IOS-Q). RESULTS: The exploratory factor analysis yielded a five factor structure. Four factors with 17 items remained after items that had unclear factor loading were removed. The Cronbach’s alpha for the IOS-Q total score was 0.91, and test-retest reliability was 0.72. The correlation between Young’s internet addiction scale and K-scale supported concurrent validity. ROC analysis showed that the IOS-Q has superior diagnostic ability with the Area Under the Curve of 0.87. At the cut-off point of 25.5, the sensitivity was 0.93 and specificity was 0.86. CONCLUSION: Overall, this study supports the use of IOS-Q for internet addiction research and for screening high-risk individuals.
Internet* ; Korea ; Mass Screening* ; Reproducibility of Results ; ROC Curve ; Sensitivity and Specificity ; Seoul

PURPOSE: Thyroglobulin (Tg) may be released from damaged residual thyroid tissues after radioactive iodine (RAI) therapy in patients with differentiated thyroid carcinoma (DTC). We investigated whether altered levels of serum Tg after recombinant human thyrotropin (rhTSH)-aided RAI therapy could be a prognostic marker in patients with DTC.METHODS: We evaluated 68 patients who underwent RAI therapy after total thyroidectomy. Serum Tg levels were measured just before RAI administration (D0Tg) and 7 days after RAI therapy (D7Tg). Patients with a D0Tg level greater than 2.0 ng/mL were excluded to more precisely evaluate the injury effect of RAI in small remnant tissues. The ratioTg was defined as the D7Tg level divided by that on D0Tg. The therapeutic responses were classified as acceptable or non-acceptable. Finally, we investigated which clinicopathologic parameters were associated with therapeutic response.RESULTS: At the follow-up examination, an acceptable response was observed in 50 patients (73.5%). Univariate analysis revealed significant differences in N stage (P = 0.003) and ratioTg (acceptable vs. non-acceptable responses, 21.9 ± 33.6 vs. 3.8 ± 6.5; P = 0.006). In multivariate analysis, only ratioTg significantly predicted an acceptable response (odds ratio 1.104; 95% confidence interval 1.005–1.213; P = 0.040). A ratioTg above 3.5 predicted an acceptable response with a sensitivity of 66.0%, specificity of 83.3%, and accuracy of 70.6% (area under the curve = 0.718; P = 0.006).CONCLUSIONS: Altered levels of serum Tg after RAI therapy, calculated as the ratioTg (D7Tg/D0Tg), significantly predicted an acceptable response in patients with DTC.
Follow-Up Studies ; Humans ; Iodine ; Multivariate Analysis ; Sensitivity and Specificity ; Thyroglobulin ; Thyroid Gland ; Thyroid Neoplasms ; Thyroidectomy ; Thyrotropin

PURPOSE: Thyroglobulin (Tg) may be released from damaged residual thyroid tissues after radioactive iodine (RAI) therapy in patients with differentiated thyroid carcinoma (DTC). We investigated whether altered levels of serum Tg after recombinant human thyrotropin (rhTSH)-aided RAI therapy could be a prognostic marker in patients with DTC. METHODS: We evaluated 68 patients who underwent RAI therapy after total thyroidectomy. Serum Tg levels were measured just before RAI administration (D0Tg) and 7 days after RAI therapy (D7Tg). Patients with a D0Tg level greater than 2.0 ng/mL were excluded to more precisely evaluate the injury effect of RAI in small remnant tissues. The ratioTg was defined as the D7Tg level divided by that on D0Tg. The therapeutic responses were classified as acceptable or non-acceptable. Finally, we investigated which clinicopathologic parameters were associated with therapeutic response. RESULTS: At the follow-up examination, an acceptable response was observed in 50 patients (73.5%). Univariate analysis revealed significant differences in N stage (P = 0.003) and ratioTg (acceptable vs. non-acceptable responses, 21.9 ± 33.6 vs. 3.8 ± 6.5; P = 0.006). In multivariate analysis, only ratioTg significantly predicted an acceptable response (odds ratio 1.104; 95% confidence interval 1.005–1.213; P = 0.040). A ratioTg above 3.5 predicted an acceptable response with a sensitivity of 66.0%, specificity of 83.3%, and accuracy of 70.6% (area under the curve = 0.718; P = 0.006). CONCLUSIONS Altered levels of serum Tg after RAI therapy, calculated as the ratioTg (D7Tg/D0Tg), significantly predicted an acceptable response in patients with DTC.