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.

Background: Information on the effectiveness of nirmatrelvir/ritonavir against the omicron is limited. The clinical response and viral kinetics to therapy in the real world need to be evaluated. Methods: Mild to moderate coronavirus disease 2019 (COVID-19) patients with risk factors for severe illness were prospectively enrolled as a treatment group with nirmatrelvir/ritonavir therapy versus a control group with supportive care. Serial viral load and culture from the upper respiratory tract were evaluated for seven days, and clinical responses and adverse reactions were evaluated for 28 days. Results: A total of 51 patients were analyzed including 40 in the treatment group and 11 in the control group. Faster symptom resolution during hospitalization (P= 0.048) was observed in the treatment group. Only minor adverse reactions were reported in 27.5% of patients. The viral load on Day 7 was lower in the treatment group (P = 0.002). The viral culture showed a positivity of 67.6% (25/37) vs. 100% (6/6) on Day 1, 0% (0/37) vs. 16.7 (1/6) on Day 5, and 0% (0/16) vs. 50.0% (2/4) on Day 7 in the treatment and control groups, respectively. Conclusions Nirmatrelvir/ritonavir against the omicron was safe and resulted in negative viral culture conversion after Day 5 of treatment with better symptomatic resolution.

Purpose: We investigated the consistent efficacy and safety of eflapegrastim, a novel long-acting granulocyte-colony stimulating factor (G-CSF), in Koreans and Asians compared with the pooled population of two global phase 3 trials. Materials and Methods: Two phase 3 trials (ADVANCE and RECOVER) evaluated the efficacy and safety of fixed-dose eflapegrastim (13.2 mg/0.6 mL [3.6 mg G-CSF equivalent]) compared to pegfilgrastim (6 mg based on G-CSF) in breast cancer patients who received neoadjuvant or adjuvant docetaxel/cyclophosphamide. The primary objective was to demonstrate non-inferiority of eflapegrastim compared to pegfilgrastim in mean duration of severe neutropenia (DSN) in cycle 1, in Korean and Asian subpopulations. Results: Among a total of 643 patients randomized to eflapegrastim (n=314) or pegfilgrastim (n=329), 54 Asians (29 to eflapegrastim and 25 to pegfilgrastim) including 28 Koreans (14 to both eflapegrastim and pegfilgrastim) were enrolled. The primary endpoint, DSN in cycle 1 in the eflapegrastim arm was non-inferior to the pegfilgrastim arm in Koreans and Asians. The DSN difference between the eflapegrastim and pegfilgrastim arms was consistent across populations: –0.120 days (95% confidence interval [CI], –0.227 to –0.016), –0.288 (95% CI, –0.714 to 0.143), and –0.267 (95% CI, –0.697 to 0.110) for pooled population, Koreans and Asians, respectively. There were few treatment-related adverse events that caused discontinuation of eflapegrastim (1.9%) or pegfilgrastim (1.5%) in total and no notable trends or differences across patient populations. Conclusion This study may suggest that eflapegrastim showed non-inferior efficacy and similar safety compared to pegfilgrastim in Koreans and Asians, consistently with those of pooled population.

Background: Nirmatrelvir-ritonavir is highly effective in preventing severe coronavirus disease 2019 (COVID-19) in high-risk patients with mild-to-moderate severity. However, real-world performance data are limited, and the drug is not so acceptable to the COVID-19 patients at high risk who need it in Korea. Methods: To evaluate the effectiveness of nirmatrelvir-ritonavir, we conducted a propensity score-matched retrospective cohort study on patients with mild-to-moderate COVID-19 at high risk for a severe disease who were hospitalized at four hospitals in South Korea from February 2022 to April 2022. A total of 236 patients in the treatment group (administered nirmatrelvir-ritonavir) and 236 in the matched control group (supportive care only) were analyzed for the primary outcome, i.e., the time to oxygen support-free survival. The secondary outcome was a composite result of disease progression. The reason for not prescribing nirmatrelvir-ritonavir to the indicated patients was also investigated. Results: The treatment group showed significantly longer oxygen support-free survival than the matched control group (adjusted hazard ratio [aHR], 0.07; 95% confidence interval [CI], 0.01–0.31; P < 0.001). Multivariate Cox regression analysis showed that age (aHR, 1.03; 95% CI, 1.00–1.07), National Early Warning Score-2 at admission (aHR, 1.36; 95% CI, 1.08–1.71), nirmatrelvir-ritonavir treatment, female sex (aHR, 0.37; 95% CI, 0.15–0.88), and time from symptom onset to admission (aHR, 0.67; 95% CI, 0.48–0.95) were significantly associated with oxygen therapy. However, none of the factors were related to the composite outcome. In the unmatched control group, 19.9% of 376 patients had documented explanations for nirmatrelvir-ritonavir non-prescription, and 44.0% of these were due to contraindication criteria. In the treatment group, 10.9% of patients discontinued the medication primarily because of adverse events (71.4%), with gastrointestinal symptoms being the most common (50.0%). Conclusion Nirmatrelvir-ritonavir treatment significantly reduced oxygen therapy requirements in high-risk patients with COVID-19 during the omicron variant surge in South Korea. Physicians are encouraged to consider the active use of nirmatrelvir-ritonavir and to be watchful for gastrointestinal symptoms during medication.

Female ; Humans ; Middle Aged ; Nasal Cavity ; Nasal Obstruction ; Parotid Gland ; Pathology ; Salivary Glands ; Turbinates

BACKGROUND: The duration of immobilization after arthroscopic rotator cuff repair and the optimal time to commence rehabilitation are still the subject of ongoing debates. This study was undertaken to evaluate the functional outcome and rotator cuff healing status after arthroscopic rotator cuff repair by comparing early and delayed rehabilitation. METHODS: Totally, 76 patients with small, medium, and large sized rotator cuff tears underwent arthroscopic repair using the suture-bridge technique. In early rehabilitation group, 38 patients commenced passive range of motion at postoperative day 2 whereas 38 patients assigned to the delayed rehabilitation group commenced passive range of motion at postoperative week 3. At the end of the study period, clinical and functional evaluations (Constant score, the University of California, Los Angeles [UCLA] shoulder score) were carried out, subsequent to measuring the range of motion, visual analogue scale for pain, and isokinetic dynamometer test. Rotator cuff healing was confirmed by magnetic resonance imaging at least 6 months after surgery. RESULTS: No significant difference was obtained in range of motion and visual analogue scale between both groups. Functional outcomes showed similar improvements in the Constant score (early: 67.0–88.0; delayed: 66.9–91.0; p<0.001) and the UCLA shoulder score (early: 20.3–32.3; delayed: 20.4–32.4; p<0.001). Furthermore, rotator cuff healing showed no significant differences between the groups (range, 6–15 months; average, 10.4 months). CONCLUSIONS Delayed passive rehabilitation does not bring about superior outcomes. Therefore, early rehabilitation would be useful to help patients resume their daily lives.

The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). The analysis was performed in two stages (training and test sets). Model A was designed with only clinical information (age, sex, body mass index, smoking status, alcohol consumption status, and exercise status), and for model B, genetic information (for 10 polymorphisms) was added to model A. Of the 7,502 nonobese participants, 647 (8.6%) had MS. In the test set analysis, for the maximum sensitivity criterion, NB showed the highest sensitivity: 0.38 for model A and 0.42 for model B. The specificity of NB was 0.79 for model A and 0.80 for model B. In a comparison of the performances of models A and B by NB, model B (area under the receiver operating characteristic curve [AUC] = 0.69, clinical and genetic information input) showed better performance than model A (AUC = 0.65, clinical information only input). We designed a prediction model for MS in a nonobese population using clinical and genetic information. With this model, we might convince nonobese MS individuals to undergo health checks and adopt behaviors associated with a preventive lifestyle.
Alcohol Drinking ; Bays ; Body Mass Index ; Classification ; Life Style ; Machine Learning ; Polymorphism, Genetic ; Prevalence ; ROC Curve ; Sensitivity and Specificity ; Smoke ; Smoking