Purpose: . This study evaluated the accuracy of implant impression techniques using scan healing abutments compared to conventional techniques. Materials and methods: . A mandibular model with implants at #34, 36, and 46 was used. Experiments were conducted for single implant and 3-unit bridge scenarios. Groups were as follows: Group IOS - Scan healing abutments were scanned with an intraoral scanner. Group Imp - Scan healing abutments were used, and impressions were taken with silicone material, followed by model scanning. Group Sb - Scan bodies were scanned with an intraoral scanner. Group Trans - Impressions were taken with transfer copings, and models were scanned. Each group was scanned 10 times, and deviations in central distance and angulation of analogs were measured. Statistical analyses were performed using ANOVA and post-hoc tests at a 95% confidence level. Results: . For single implants, there were no significant differences in distance deviation (P > .05). Angular deviation values were: IOS (0.24 ± 0.10°), Imp (0.19 ± 0.06°), Sb (0.38 ± 0.05°), and Trans (0.29 ± 0.06°), with Sb showing significantly larger values than IOS and Imp (P < .05). For bridges, distance deviation did not significantly differ (P > .05). Angular deviations were: IOS (0.21 ± 0.08°), Imp (0.21 ± 0.09°), Sb (0.25 ± 0.10°), and Trans (0.46 ± 0.19°), with Trans showing significantly larger values than the others (P < .05). Conclusion . Scan healing abutment techniques showed similar accuracy to traditional methods. They could be a viable alternative for single implant crowns or short-span fixed dental prostheses.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: . This study evaluated the accuracy of implant impression techniques using scan healing abutments compared to conventional techniques. Materials and methods: . A mandibular model with implants at #34, 36, and 46 was used. Experiments were conducted for single implant and 3-unit bridge scenarios. Groups were as follows: Group IOS - Scan healing abutments were scanned with an intraoral scanner. Group Imp - Scan healing abutments were used, and impressions were taken with silicone material, followed by model scanning. Group Sb - Scan bodies were scanned with an intraoral scanner. Group Trans - Impressions were taken with transfer copings, and models were scanned. Each group was scanned 10 times, and deviations in central distance and angulation of analogs were measured. Statistical analyses were performed using ANOVA and post-hoc tests at a 95% confidence level. Results: . For single implants, there were no significant differences in distance deviation (P > .05). Angular deviation values were: IOS (0.24 ± 0.10°), Imp (0.19 ± 0.06°), Sb (0.38 ± 0.05°), and Trans (0.29 ± 0.06°), with Sb showing significantly larger values than IOS and Imp (P < .05). For bridges, distance deviation did not significantly differ (P > .05). Angular deviations were: IOS (0.21 ± 0.08°), Imp (0.21 ± 0.09°), Sb (0.25 ± 0.10°), and Trans (0.46 ± 0.19°), with Trans showing significantly larger values than the others (P < .05). Conclusion . Scan healing abutment techniques showed similar accuracy to traditional methods. They could be a viable alternative for single implant crowns or short-span fixed dental prostheses.

Purpose: . This study evaluated the accuracy of implant impression techniques using scan healing abutments compared to conventional techniques. Materials and methods: . A mandibular model with implants at #34, 36, and 46 was used. Experiments were conducted for single implant and 3-unit bridge scenarios. Groups were as follows: Group IOS - Scan healing abutments were scanned with an intraoral scanner. Group Imp - Scan healing abutments were used, and impressions were taken with silicone material, followed by model scanning. Group Sb - Scan bodies were scanned with an intraoral scanner. Group Trans - Impressions were taken with transfer copings, and models were scanned. Each group was scanned 10 times, and deviations in central distance and angulation of analogs were measured. Statistical analyses were performed using ANOVA and post-hoc tests at a 95% confidence level. Results: . For single implants, there were no significant differences in distance deviation (P > .05). Angular deviation values were: IOS (0.24 ± 0.10°), Imp (0.19 ± 0.06°), Sb (0.38 ± 0.05°), and Trans (0.29 ± 0.06°), with Sb showing significantly larger values than IOS and Imp (P < .05). For bridges, distance deviation did not significantly differ (P > .05). Angular deviations were: IOS (0.21 ± 0.08°), Imp (0.21 ± 0.09°), Sb (0.25 ± 0.10°), and Trans (0.46 ± 0.19°), with Trans showing significantly larger values than the others (P < .05). Conclusion . Scan healing abutment techniques showed similar accuracy to traditional methods. They could be a viable alternative for single implant crowns or short-span fixed dental prostheses.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: We investigated the clinical features, current negative-pressure wound therapy (NPWT) management strategies, and outcomes of pelvic-perineal soft tissue infection after open pelvic fractures. Materials and Methods: We analyzed the data of patients admitted to our trauma center with pelvic-perineal soft tissue after open pelvic fractures over a 7-year period. We investigated the injury severity score (ISS), medical costs, number of NPWTs, time required to reach definite wound coverage, complications, fracture classifications, transfusion requirements, interventions, length of stay (LOS) in hospital and intensive care unit (ICU), and prognosis. Results: Twenty patients with open pelvic fractures were treated with NPWT, and one patient who underwent NPWT died of pelvic sepsis during ICU treatment. The median LOS in hospital and medical costs were 98 [56–164] days and 106400 [65600–171100] USD, respectively. Patients treated with instillation NPWT (iNPWT, n=10) had a shorter NPWT duration (24 [13–39] vs. 46 [42–91] days, p=0.023), time to definite wound coverage (30 [21–43] vs. 49 [42–93] days, p=0.026), and hospital LOS (56 [43–72] vs. 158 [101–192] days, p=0.001), as well as lower medical costs (67800 [42500–102500] vs. 144200 [110400–236000] USD, p=0.009) compared to those treated with conventional NPWT. Conclusion NPWT is a feasible method for treating pelvic soft tissue infections in patients with open pelvic fractures. iNPWT can reduce the duration of NPWT, hospital LOS, and medical costs.

Background: We aimed to investigate the predictive values of plasma C-peptide levels and the continuous glucose monitoring (CGM)-defined coefficient of variation (CV) in risk prediction for hypoglycemia in Korean people with diabetes with normal and impaired kidney function. Methods: We analyzed data from 1,185 participants diagnosed with type 1 and type 2 diabetes who underwent blinded professional CGM between January 2009 and May 2021 at outpatient clinics. We explored correlations among CGM-defined CV, plasma C-peptide levels, and time below range at <70 and 54 mg/dL across different kidney function categories. Results: In patients with chronic kidney disease (CKD) stages 1–2 (n=934), 89.3% who had a random plasma C-peptide level higher than 600 pmol/L exhibited a CV of ≤36%. Among those in CKD stage 3 (n=161) with a random plasma C-peptide level exceeding 600 pmol/L, 66.7% showed a CV of ≤36%. In stages 4–5 of CKD (n=90), the correlation between random C-peptide levels and CV was not significant (r=–0.05, P=0.640), including cases with a CV greater than 36% despite very high random plasma C-peptide levels. Random plasma C-peptide levels and CGM-assessed CV significantly predicted hypoglycemia in CKD stages 1–2 and 1–5, respectively. Conclusion The established C-peptide criteria in Western populations are applicable to Korean people with diabetes for hypoglycemic risk prediction, unless kidney function is impaired equivalent to CKD stage 3–5. The CGM-defined CV is informative for hypoglycemic risk prediction regardless of kidney function.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.