PURPOSE: This pilot study investigated the effect of surface roughness on osseointegration by comparing two types of commercial SLA-treated dental implants with different surface roughness levels: moderately rough (Sa = 1 – 2 µm) and rough surfaces (Sa > 2 µm). MATERIALS AND METHODS: Two implant groups were studied: TS (rough surface) and ADD (moderately rough surface) groups. Surface characteristics were analyzed using optical profilometry and SEM. In vitro studies using BRITER cells assessed cell adhesion, proliferation, and osteogenic differentiation through CCK-8 assay and qRT-PCR for osteopontin (OPN), osteocalcin (OCN), and alkaline phosphatase (ALP) expression. The in vivo study involved 12 implants (six per group) placed in mandibular defects of two beagle dogs. After 8 weeks, histomorphometric analysis evaluated bone to implant contact (BIC) and inter-thread bone density (ITBD). Statistical analysis used Student’s t-test and two-way ANOVA for in vitro data, and Mann-Whitney U test for in vivo data. RESULTS: Surface analysis revealed Sa values of 2.50 ± 0.27 µm for the TS group and 1.80 ± 0.06 µm for the ADD group. In vitro studies showed no significant differences in cell adhesion and proliferation between the groups (P > .05). However, gene expression patterns differed, with ADD group showing higher OPN expression (P < .001) and TS group showing higher ALP expression (P < .01). The in vivo study revealed no statistically significant differences in BIC and ITBD between the two groups (P > .05). CONCLUSION Surface roughness influenced osteoblast differentiation in vitro, but did not significantly affect osseointegration outcomes in vivo. Both moderately rough and rough surfaces appeared to support comparable levels of osseointegration. Larger studies are needed to confirm these findings and determine optimal implant surface characteristics.

PURPOSE: This pilot study investigated the effect of surface roughness on osseointegration by comparing two types of commercial SLA-treated dental implants with different surface roughness levels: moderately rough (Sa = 1 – 2 µm) and rough surfaces (Sa > 2 µm). MATERIALS AND METHODS: Two implant groups were studied: TS (rough surface) and ADD (moderately rough surface) groups. Surface characteristics were analyzed using optical profilometry and SEM. In vitro studies using BRITER cells assessed cell adhesion, proliferation, and osteogenic differentiation through CCK-8 assay and qRT-PCR for osteopontin (OPN), osteocalcin (OCN), and alkaline phosphatase (ALP) expression. The in vivo study involved 12 implants (six per group) placed in mandibular defects of two beagle dogs. After 8 weeks, histomorphometric analysis evaluated bone to implant contact (BIC) and inter-thread bone density (ITBD). Statistical analysis used Student’s t-test and two-way ANOVA for in vitro data, and Mann-Whitney U test for in vivo data. RESULTS: Surface analysis revealed Sa values of 2.50 ± 0.27 µm for the TS group and 1.80 ± 0.06 µm for the ADD group. In vitro studies showed no significant differences in cell adhesion and proliferation between the groups (P > .05). However, gene expression patterns differed, with ADD group showing higher OPN expression (P < .001) and TS group showing higher ALP expression (P < .01). The in vivo study revealed no statistically significant differences in BIC and ITBD between the two groups (P > .05). CONCLUSION Surface roughness influenced osteoblast differentiation in vitro, but did not significantly affect osseointegration outcomes in vivo. Both moderately rough and rough surfaces appeared to support comparable levels of osseointegration. Larger studies are needed to confirm these findings and determine optimal implant surface characteristics.

PURPOSE: This pilot study investigated the effect of surface roughness on osseointegration by comparing two types of commercial SLA-treated dental implants with different surface roughness levels: moderately rough (Sa = 1 – 2 µm) and rough surfaces (Sa > 2 µm). MATERIALS AND METHODS: Two implant groups were studied: TS (rough surface) and ADD (moderately rough surface) groups. Surface characteristics were analyzed using optical profilometry and SEM. In vitro studies using BRITER cells assessed cell adhesion, proliferation, and osteogenic differentiation through CCK-8 assay and qRT-PCR for osteopontin (OPN), osteocalcin (OCN), and alkaline phosphatase (ALP) expression. The in vivo study involved 12 implants (six per group) placed in mandibular defects of two beagle dogs. After 8 weeks, histomorphometric analysis evaluated bone to implant contact (BIC) and inter-thread bone density (ITBD). Statistical analysis used Student’s t-test and two-way ANOVA for in vitro data, and Mann-Whitney U test for in vivo data. RESULTS: Surface analysis revealed Sa values of 2.50 ± 0.27 µm for the TS group and 1.80 ± 0.06 µm for the ADD group. In vitro studies showed no significant differences in cell adhesion and proliferation between the groups (P > .05). However, gene expression patterns differed, with ADD group showing higher OPN expression (P < .001) and TS group showing higher ALP expression (P < .01). The in vivo study revealed no statistically significant differences in BIC and ITBD between the two groups (P > .05). CONCLUSION Surface roughness influenced osteoblast differentiation in vitro, but did not significantly affect osseointegration outcomes in vivo. Both moderately rough and rough surfaces appeared to support comparable levels of osseointegration. Larger studies are needed to confirm these findings and determine optimal implant surface characteristics.

PURPOSE: This pilot study investigated the effect of surface roughness on osseointegration by comparing two types of commercial SLA-treated dental implants with different surface roughness levels: moderately rough (Sa = 1 – 2 µm) and rough surfaces (Sa > 2 µm). MATERIALS AND METHODS: Two implant groups were studied: TS (rough surface) and ADD (moderately rough surface) groups. Surface characteristics were analyzed using optical profilometry and SEM. In vitro studies using BRITER cells assessed cell adhesion, proliferation, and osteogenic differentiation through CCK-8 assay and qRT-PCR for osteopontin (OPN), osteocalcin (OCN), and alkaline phosphatase (ALP) expression. The in vivo study involved 12 implants (six per group) placed in mandibular defects of two beagle dogs. After 8 weeks, histomorphometric analysis evaluated bone to implant contact (BIC) and inter-thread bone density (ITBD). Statistical analysis used Student’s t-test and two-way ANOVA for in vitro data, and Mann-Whitney U test for in vivo data. RESULTS: Surface analysis revealed Sa values of 2.50 ± 0.27 µm for the TS group and 1.80 ± 0.06 µm for the ADD group. In vitro studies showed no significant differences in cell adhesion and proliferation between the groups (P > .05). However, gene expression patterns differed, with ADD group showing higher OPN expression (P < .001) and TS group showing higher ALP expression (P < .01). The in vivo study revealed no statistically significant differences in BIC and ITBD between the two groups (P > .05). CONCLUSION Surface roughness influenced osteoblast differentiation in vitro, but did not significantly affect osseointegration outcomes in vivo. Both moderately rough and rough surfaces appeared to support comparable levels of osseointegration. Larger studies are needed to confirm these findings and determine optimal implant surface characteristics.

Objective: Endovascular coil embolization is the primary treatment modality for intracranial aneurysms. However, its long-term durability remains of concern, with a considerable proportion of cases requiring aneurysm reopening and retreatment. Therefore, establishing optimal follow-up imaging protocols is necessary to ensure a durable occlusion. This study aimed to develop guidelines for follow-up imaging strategies after endovascular treatment of intracranial aneurysms. Methods: A committee comprising members of the Korean Neuroendovascular Society and other relevant societies was formed. A literature review and analyses of the major published guidelines were conducted to gather evidence. A panel of 40 experts convened to achieve a consensus on the recommendations using the modified Delphi method. Results: The panel members reached the following consensus: 1. Schedule the initial follow-up imaging within 3-6 months of treatment. 2. Noninvasive imaging modalities, such as three-dimensional time-of-flight magnetic resonance angiography (MRA) or contrast-enhanced MRA, are alternatives to digital subtraction angiography (DSA) during the first follow-up. 3. Schedule mid-term follow-up imaging at 1, 2, 4, and 6 years after the initial treatment. 4. If noninvasive imaging reveals unstable changes in the treated aneurysms, DSA should be considered. 5. Consider late-term follow-up imaging every 3–5 years for lifelong monitoring of patients with unstable changes or at high risk of recurrence. Conclusions The guidelines aim to provide physicians with the information to make informed decisions and provide patients with high-quality care. However, owing to a lack of specific recommendations and scientific data, these guidelines are based on expert consensus and should be considered in conjunction with individual patient characteristics and circumstances.

Background: Limited data are available on the mortality rates of patients receiving extracorporeal membrane oxygenation (ECMO) support for coronavirus disease 2019 (COVID-19). We aimed to analyze the relationship between COVID-19 and clinical outcomes for patients receiving ECMO. Methods: We retrospectively investigated patients with COVID-19 pneumonia requiring ECMO in 19 hospitals across Korea from January 1, 2020 to August 31, 2021. The primary outcome was the 90-day mortality after ECMO initiation. We performed multivariate analysis using a logistic regression model to estimate the odds ratio (OR) of 90-day mortality. Survival differences were analyzed using the Kaplan–Meier (KM) method. Results: Of 127 patients with COVID-19 pneumonia who received ECMO, 70 patients (55.1%) died within 90 days of ECMO initiation. The median age was 64 years, and 63% of patients were male. The incidence of ECMO was increased with age but was decreased after 70 years of age. However, the survival rate was decreased linearly with age. In multivariate analysis, age (OR, 1.048; 95% confidence interval [CI], 1.010–1.089; P = 0.014) and receipt of continuous renal replacement therapy (CRRT) (OR, 3.069; 95% CI, 1.312–7.180; P = 0.010) were significantly associated with an increased risk of 90-day mortality. KM curves showed significant differences in survival between groups according to age (65 years) (log-rank P = 0.021) and receipt of CRRT (log-rank P = 0.004). Conclusion Older age and receipt of CRRT were associated with higher mortality rates among patients with COVID-19 who received ECMO.

Further study is warranted to determine the association between estimated glomerular filtration rate (eGFR) or albuminuria and the risk of death from diverse causes. Methods: We screened >10 million general health screening examinees who received health examinations conducted in 2009 using the claims database of Korea. After the exclusion of those previously diagnosed with renal failure and those with missing data, 9,917,838 individuals with available baseline kidney function measurements were included. The primary outcome was mortality and cause-specific death between 2009 and 2019 identified through death certificates based on the diagnostic codes of International Classification of Diseases, 10th revision. Multivariable Cox regression analysis adjusted for various clinicodemographic and social characteristics was used to assess mortality risk. Results: The hazard ratio of death was significantly high in both the eGFR <60 mL/min/1.73 m2 and in the eGFR ≥120 mL/ min/1.73 m2 groups in univariable and multivariable regression analyses when compared to those within the reference range (eGFR of 90–120 mL/min/1.73 m2). The results were similar for death by cardiovascular, cancer, infection, endocrine, respiratory, and digestive causes. We also found that albuminuria was associated with higher risk of death regardless of eGFR range, and those in the higher categories of dipstick albuminuria showed higher risk. Conclusion: We reconfirmed the significant association between eGFR, albuminuria, and mortality. Healthcare providers should keep in mind that albuminuria and decreased eGFR as well as kidney hyperfiltration are independent predictors of mortality.