Objective: Multiple cohort studies have investigated the potential link between anesthesia and dementia. However, mixed findings necessitate closer examination. This study aimed to investigate the association between anesthesia exposure and the incidence of dementia, considering different anesthesia types and anesthetic agents. Methods: This nationwide cohort study utilized data from the South Korean Health Insurance Review and Assessment Service database, covering 62,541 participants, to investigate the correlation between anesthesia exposure and dementia incidence. Results: Results revealed an increased risk of dementia in individuals who underwent general (hazard ratio [HR], 1.318;95% confidence interval [CI], 1.061−1.637) or regional/local anesthesia (HR, 2.097; 95% CI, 1.887−2.329) compared to those who did not. However, combined general and regional/local anesthesia did not significantly increase dementia risk (HR, 1.097; 95% CI, 0.937−1.284). Notably, individual anesthetic agents exhibited varying risks; desflurane and midazolam showed increased risks, whereas propofol showed no significant difference. Conclusion This study provides unique insights into the nuanced relationship between anesthesia, individual anesthetic agents, and the incidence of dementia. While confirming a general association between anesthesia exposure and dementia risk, this study also emphasizes the importance of considering specific agents. These findings under-score the need for careful evaluation and long-term cognitive monitoring after anesthesia.

Objective: Multiple cohort studies have investigated the potential link between anesthesia and dementia. However, mixed findings necessitate closer examination. This study aimed to investigate the association between anesthesia exposure and the incidence of dementia, considering different anesthesia types and anesthetic agents. Methods: This nationwide cohort study utilized data from the South Korean Health Insurance Review and Assessment Service database, covering 62,541 participants, to investigate the correlation between anesthesia exposure and dementia incidence. Results: Results revealed an increased risk of dementia in individuals who underwent general (hazard ratio [HR], 1.318;95% confidence interval [CI], 1.061−1.637) or regional/local anesthesia (HR, 2.097; 95% CI, 1.887−2.329) compared to those who did not. However, combined general and regional/local anesthesia did not significantly increase dementia risk (HR, 1.097; 95% CI, 0.937−1.284). Notably, individual anesthetic agents exhibited varying risks; desflurane and midazolam showed increased risks, whereas propofol showed no significant difference. Conclusion This study provides unique insights into the nuanced relationship between anesthesia, individual anesthetic agents, and the incidence of dementia. While confirming a general association between anesthesia exposure and dementia risk, this study also emphasizes the importance of considering specific agents. These findings under-score the need for careful evaluation and long-term cognitive monitoring after anesthesia.

Objective: Multiple cohort studies have investigated the potential link between anesthesia and dementia. However, mixed findings necessitate closer examination. This study aimed to investigate the association between anesthesia exposure and the incidence of dementia, considering different anesthesia types and anesthetic agents. Methods: This nationwide cohort study utilized data from the South Korean Health Insurance Review and Assessment Service database, covering 62,541 participants, to investigate the correlation between anesthesia exposure and dementia incidence. Results: Results revealed an increased risk of dementia in individuals who underwent general (hazard ratio [HR], 1.318;95% confidence interval [CI], 1.061−1.637) or regional/local anesthesia (HR, 2.097; 95% CI, 1.887−2.329) compared to those who did not. However, combined general and regional/local anesthesia did not significantly increase dementia risk (HR, 1.097; 95% CI, 0.937−1.284). Notably, individual anesthetic agents exhibited varying risks; desflurane and midazolam showed increased risks, whereas propofol showed no significant difference. Conclusion This study provides unique insights into the nuanced relationship between anesthesia, individual anesthetic agents, and the incidence of dementia. While confirming a general association between anesthesia exposure and dementia risk, this study also emphasizes the importance of considering specific agents. These findings under-score the need for careful evaluation and long-term cognitive monitoring after anesthesia.

Objective: Multiple cohort studies have investigated the potential link between anesthesia and dementia. However, mixed findings necessitate closer examination. This study aimed to investigate the association between anesthesia exposure and the incidence of dementia, considering different anesthesia types and anesthetic agents. Methods: This nationwide cohort study utilized data from the South Korean Health Insurance Review and Assessment Service database, covering 62,541 participants, to investigate the correlation between anesthesia exposure and dementia incidence. Results: Results revealed an increased risk of dementia in individuals who underwent general (hazard ratio [HR], 1.318;95% confidence interval [CI], 1.061−1.637) or regional/local anesthesia (HR, 2.097; 95% CI, 1.887−2.329) compared to those who did not. However, combined general and regional/local anesthesia did not significantly increase dementia risk (HR, 1.097; 95% CI, 0.937−1.284). Notably, individual anesthetic agents exhibited varying risks; desflurane and midazolam showed increased risks, whereas propofol showed no significant difference. Conclusion This study provides unique insights into the nuanced relationship between anesthesia, individual anesthetic agents, and the incidence of dementia. While confirming a general association between anesthesia exposure and dementia risk, this study also emphasizes the importance of considering specific agents. These findings under-score the need for careful evaluation and long-term cognitive monitoring after anesthesia.

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: Long-term care facilities (LTCFs) are communal environments for patients with chronic diseases or older adults, making them particularly susceptible to significant harm during infectious disease outbreaks. Nonetheless, LTCFs have historically been subject to less stringent infection prevention and control (IPC) mandates. This study aimed to assess the current state of LTCFs and to develop an IPC system tailored for these facilities following the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We conducted an online survey of 11,366 LTCFs in Korea from December 30, 2022 to January 20, 2023, to evaluate the components of IPC in LTCFs. The infectious diseases targeted for IPC included COVID-19, influenza, and scabies. Additionally, we compared institution-based and home-based long-term care insurance facilities. RESULTS: Overall, 3,537 (31.1%) LTCFs responded to the survey, comprising 1,819 (51.4%) institution-based and 1,718 (48.6%) home-based facilities. A majority (87.4%, 2,376/2,720) of these facilities experienced COVID-19 outbreaks. However, only 42.2% of home-based facilities, in contrast to 90.6% of institution-based facilities, were equipped to manage concurrent COVID-19 cases. Similarly, while 92.1% of institution-based facilities were capable of managing influenza, only 50.5% of home-based facilities could do the same. The incidence of scabies was significantly higher in institution-based facilities than in home-based ones (26.1 vs. 4.3%). Additionally, 88.7% of institution-based facilities managed scabies cases effectively, compared to only 42.1% of home-based facilities. CONCLUSIONS Approximately half of the LTCFs had a basic capacity to respond to infectious diseases. However, there were differences in response capabilities between institution-based facilities and home-based facilities.

OBJECTIVES: Long-term care facilities (LTCFs) are communal environments for patients with chronic diseases or older adults, making them particularly susceptible to significant harm during infectious disease outbreaks. Nonetheless, LTCFs have historically been subject to less stringent infection prevention and control (IPC) mandates. This study aimed to assess the current state of LTCFs and to develop an IPC system tailored for these facilities following the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We conducted an online survey of 11,366 LTCFs in Korea from December 30, 2022 to January 20, 2023, to evaluate the components of IPC in LTCFs. The infectious diseases targeted for IPC included COVID-19, influenza, and scabies. Additionally, we compared institution-based and home-based long-term care insurance facilities. RESULTS: Overall, 3,537 (31.1%) LTCFs responded to the survey, comprising 1,819 (51.4%) institution-based and 1,718 (48.6%) home-based facilities. A majority (87.4%, 2,376/2,720) of these facilities experienced COVID-19 outbreaks. However, only 42.2% of home-based facilities, in contrast to 90.6% of institution-based facilities, were equipped to manage concurrent COVID-19 cases. Similarly, while 92.1% of institution-based facilities were capable of managing influenza, only 50.5% of home-based facilities could do the same. The incidence of scabies was significantly higher in institution-based facilities than in home-based ones (26.1 vs. 4.3%). Additionally, 88.7% of institution-based facilities managed scabies cases effectively, compared to only 42.1% of home-based facilities. CONCLUSIONS Approximately half of the LTCFs had a basic capacity to respond to infectious diseases. However, there were differences in response capabilities between institution-based facilities and home-based facilities.