Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019.In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virusinfected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Background: Current international guidelines recommend against deep sedation as it is associated with worse outcomes in the intensive care unit (ICU). However, in Korea the prevalence of deep sedation and its impact on patients in the ICU are not well known. Methods: From April 2020 to July 2021, a multicenter, prospective, longitudinal, noninterventional cohort study was performed in 20 Korean ICUs. Sedation depth extent was divided into light and deep using a mean Richmond Agitation–Sedation Scale value within the first 48 hours. Propensity score matching was used to balance covariables; the outcomes were compared between the two groups. Results: Overall, 631 patients (418 [66.2%] and 213 [33.8%] in the deep and light sedation groups, respectively) were included. Mortality rates were 14.1% and 8.4% in the deep and light sedation groups (P = 0.039), respectively. Kaplan-Meier estimates showed that time to extubation (P < 0.001), ICU length of stay (P = 0.005), and death P = 0.041) differed between the groups. After adjusting for confounders, early deep sedation was only associated with delayed time to extubation (hazard ratio [HR], 0.66; 95% confidence inter val [CI], 0.55– 0.80; P < 0.001). In the matched cohort, deep sedation remained significantly associated with delayed time to extubation (HR, 0.68; 95% 0.56–0.83; P < 0.001) but was not associated with ICU length of stay (HR, 0.94; 95% CI, 0.79–1.13; P = 0.500) and in-hospital mortality (HR, 1.19; 95% CI, 0.65–2.17; P = 0.582). Conclusion In many Korean ICUs, early deep sedation was highly prevalent in mechanically ventilated patients and was associated with delayed extubation, but not prolonged ICU stay or in-hospital death.