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.

Background: Trapeziectomy with suspension arthroplasty is a reliable treatment for thumb carpometacarpal (CMC) osteoarthritis.We modified the suture suspension technique to add further support to maintain the arthroplasty space by interposition of the dermal allograft. Our aim was to investigate the surgical outcomes of our technique of suspension arthroplasty with dermal allograft interposition (SADI) compared with those of traditional ligament reconstruction with tendon interposition (LRTI) using a half-sling of the flexor carpi radialis (FCR) tendon. Methods: This retrospective study enrolled 26 patients (29 thumbs) with thumb CMC arthritis who underwent trapeziectomy with traditional LRTI using the FCR tendon (15 thumbs; LRTI group) or SADI (14 thumbs; SADI group) between January 2017 and May 2022. Patient-reported outcomes (visual analog scale; the Disabilities of the Arm, Shoulder and Hand score; and patient-rated wrist evaluation), grip strength, and scaphometacarpal distance were measured at baseline and 3 and 12 months postoperatively. The operation time was checked by reviewing medical records. All measurements were compared between the 2 groups. Results: Between baseline and 12-month postoperative follow-up, all patient-reported outcomes significantly improved in both groups. Patient-reported outcomes, grip strength, and scaphometacarpal distance showed no differences between the 2 groups at all follow-up assessments, except for the scaphometacarpal distance being significantly greater in the SADI group at 3 months postoperatively. The operation time was significantly shorter in the SADI group. No complication was observed in either group. Conclusions Our modified suture suspension arthroplasty technique using dermal allograft interposition results in markedly shorter surgical times with similar surgical outcomes compared with those of traditional LRTI using the FCR tendon. This procedure appears to be an effective alternative treatment for thumb CMC arthritis.

Background: This study aimed to compare the effectiveness and complications between classic palmaris longus tendon landmark-based corticosteroid injection (CI) and transverse carpal ligament (TCL)-penetrating CI for carpal tunnel syndrome (CTS). Methods: We performed a landmark-based CI on one hand and a TCL-penetrating CI on the other side after randomization in 30 consecutive patients with bilateral CTS. The pain visual analog scale (VAS) and the Boston Carpal Tunnel Questionnaire (BCTQ) were assessed at baseline, 4 weeks, and 3 and 6 months after injection. Skin hypopigmentation of the injection site was evaluated using the modified Vancouver scar scale (mVSS). Pain during needle insertion was evaluated using a VAS for each hand. Results: The mean patient age was 56 ± 11 years (range, 32–77 years), and 27 patients (90.0%) were women. The pain VAS, BCTQ scores, and the incidence of skin hypopigmentation were not significantly different between the 2 groups after injection, but the mean mVSS scores were significantly higher in the landmark-based CI group at all time points. The pain VAS score during needle insertion was significantly higher in the TCL-penetrating CI group. Conclusions When comparing the pain VAS and BCTQ scores, the difference between the 2 groups was not statistically significant. TCL-penetrating CI causes considerable pain during needle insertion but causes less severe skin hypopigmentation than landmark-based CI in CTS treatment.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Background/Aims: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted global health, exacerbated metabolic health issues, and altered lifestyle behaviors. This study examined the sex-specific impact of the COVID-19 outbreak on the incidence of metabolic syndrome using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: Data from the KNHANES VII (2018) and VIII (2019–2021), including 15,499 participants, were analyzed. The study population was stratified by sex, and further subdivisions were conducted based on the timeframe relative to the COVID-19 outbreak. Variables such as age, education level, household income, smoking status, and high-risk drinking were analyzed to assess their influence on the prevalence of metabolic syndrome. Results: The overall prevalence of metabolic syndrome significantly increased from 28.11% before the outbreak to 29.69% after the outbreak. Both males and females reported significant increases in waist circumference and fasting glucose levels. Age and education level differentially influenced the prevalence of metabolic syndrome between the sex. Smoking was significantly associated with increased prevalence in males, whereas high-risk drinking was associated with increased prevalence in males and decreased prevalence in females. Conclusions The COVID-19 pandemic has significantly increased the prevalence of metabolic syndrome with notable sex-specific differences. These findings highlight the need for sex-specific public health interventions to mitigate the impact of the pandemic on metabolic health.

Background/Aims: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted global health, exacerbated metabolic health issues, and altered lifestyle behaviors. This study examined the sex-specific impact of the COVID-19 outbreak on the incidence of metabolic syndrome using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: Data from the KNHANES VII (2018) and VIII (2019–2021), including 15,499 participants, were analyzed. The study population was stratified by sex, and further subdivisions were conducted based on the timeframe relative to the COVID-19 outbreak. Variables such as age, education level, household income, smoking status, and high-risk drinking were analyzed to assess their influence on the prevalence of metabolic syndrome. Results: The overall prevalence of metabolic syndrome significantly increased from 28.11% before the outbreak to 29.69% after the outbreak. Both males and females reported significant increases in waist circumference and fasting glucose levels. Age and education level differentially influenced the prevalence of metabolic syndrome between the sex. Smoking was significantly associated with increased prevalence in males, whereas high-risk drinking was associated with increased prevalence in males and decreased prevalence in females. Conclusions The COVID-19 pandemic has significantly increased the prevalence of metabolic syndrome with notable sex-specific differences. These findings highlight the need for sex-specific public health interventions to mitigate the impact of the pandemic on metabolic health.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

Background: Computed tomography (CT) scans are utilized to assess emphysema, a prominent phenotype of chronic obstructive pulmonary disease (COPD). Variability in CT protocols and equipment across hospitals can impact accuracy. This study aims to implement kernel conversion across different CT settings and evaluate changes in the correlation between the emphysema index pre- and post-kernel conversion, along with clinical measures in COPD patients. Methods: Data were extracted from the Korea COPD Subgroup Study database, which included CT scan images from 484 COPD patients. These images underwent kernel conversion. Emphysema extent was quantified using the percentage of low-attenuation areas (%LAA-950) determined by a deep learning-based program. The correlation between %LAA-950 and clinical parameters, including lung function tests, the modified Medical Research Council (mMRC), 6-minute walking distance (6MWD), COPD assessment test (CAT), and the St. George’s Respiratory Questionnaire for COPD (SGRQ-c), was analyzed. Subsequently, these values were compared across various CT settings. Results: A total of 484 participants were included. Kernel conversion significantly reduced the variance in %LAA-950 values (before vs. after: 12.6±11.0 vs. 8.8±11.9). Post-kernel conversion, %LAA-950 demonstrated moderate correlations with forced expiratory volume in 1 second (r=–0.41), residual volume/total lung capacity (r=0.42), mMRC (r=0.25), CAT score (r=0.12), SGRQ-c (r=0.21), and 6MWD (r=0.15), all of which were improved compared to the unconverted dataset (all p<0.01). Conclusion CT images processed through kernel conversion enhance the correlation between the extent of emphysema and clinical parameters in COPD.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.