Background: This study aimed to compare the intraoperative stability and early clinical outcomes of 40-mm diameter dual mobility (DM)-total hip arthroplasty (THA) with 36-mm ceramic head (large head) THA in active elderly patients with hip fractures. Methods: A prospective randomized controlled trial was conducted from May 2022 to December 2022. Inclusion criteria were as follows: age ≥ 60 years, displaced femoral neck fracture, Koval grade 1 or 2, planned 54-mm acetabular component, and over 1-year follow-up. Intraoperative stability tests were performed on all patients (internal rotation at 45°, 60°, and 90° of hip fracture). Functional outcomes (Harris Hip Score and University of California, Los Angeles [UCLA] Score) were evaluated at 6 weeks and 3 months postoperatively. Gait analysis using artificial intelligence (AI) techniques was conducted at 3 months postoperatively. Results: The study included 36 DM-THA patients (mean age, 69.6 ± 2.2 years; 44% women) and 37 large head THA patients (mean age, 69.6 ± 1.2 years; 64% women). No statistically significant differences were observed in functional outcomes and hip range of motion between the 2 groups. However, there was a significant difference in the gait speed and stance-swing phase of the large head THA group and the DM-THA group: the DM-THA group demonstrated superior gait speed (2.85 ± 0.83 kph vs. 2.04 ± 1.04 kph, p = 0.003) and higher stance phase ratios (operated side: 63.57% ± 3.82% vs. 48.19% ± 5.50%, p < 0.001; opposite side: 62.77% ± 2.27% vs. 49.93% ± 6.94%, p < 0.001). In the stability test at 90° of hip flexion, the DM-THA group had a measurement of 48.40° ± 5.17°, while the large head THA group had a measurement of 30.94° ± 2.98° (p = 0.012). Despite the lack of statistical significance, the intraoperative stability test showed the dislocation angle was notably different between the groups in the hip flexion position of 60° (51.60° ± 6.09° in the DM-THA group and 40.00° ± 2.80° in the large head THA group, p = 0.072). Conclusions Superior results were observed in the intraoperative stability test and early recovery of gait after DM-THA compared to large head THA. We believe that DM-THA can be a useful surgical option for THA in elderly patients with hip fractures.

Background: F-18-fluorodeoxyglucose positron emission tomography (FDG-PET)/computed tomography (CT) can be used to measure bone mineral density (BMD), cross-sectional muscle area (CSMA), Hounsfield units (HU) of liver and muscle, subcutaneous adipose tissue (SAT), abdominal visceral adipose tissue (VAT), and glucose metabolism. The present study aimed to identify age-related changes in body composition and glucose metabolism in Korean using opportunistic FDG-PET/CT imaging. Methods: We analyzed FDG-PET/CT, clinical history, and laboratory data abstracted from the medical records of patients who underwent health screening at a single institute between 2017 and 2022. Results: In total, 278 patients were included in the analysis (male:female=140:138). Age and body mass index were positively correlated in female, but negatively correlated in male. BMD decreased with age more in female, and CSMA decreased with age more in male. Muscle HU decreased with age for both sexes. In female, SAT and VAT increased with age; and in male, SAT decreased slightly while VAT remained stable. Muscle glucose metabolism showed no association with age in male but increased with age in female. CSMA correlated positively with BMD overall; and positively correlated with VAT and SAT in male only. In female only, both SAT and VAT showed negative correlations with glucose metabolism and correlated positively with muscle glucose metabolism. Liver HU values were inversely correlated with VAT, especially in female; and positively correlated with muscle glucose metabolism in female only. Conclusion FDG-PET/CT demonstrated distinct patterns of age-related changes in body composition and glucose metabolism, with significant differences between sexes.

Background: Given the association between nonalcoholic fatty liver disease and metabolic risks, a new term, metabolic dysfunction- associated steatotic liver disease (MASLD) has been proposed. We aimed to explore the association between MASLD and all-cause, cause-specific mortalities. Methods: We included individuals with steatotic liver disease (SLD) from the Korean National Health Insurance Service. Moreover, SLD was defined as a fatty liver index ≥30. Furthermore, MASLD, metabolic alcohol-associated liver disease (MetALD), and alcoholic liver disease (ALD) with metabolic dysfunction (MD) were categorized based on alcohol consumption and MD. We also analyzed all-cause, liver-, cancer-, hepatocellular carcinoma (HCC)- and cardiovascular (CV)-related mortalities. Results: This retrospective nationwide cohort study included 1,298,993 individuals aged 40 to 79 years for a mean follow-up duration of 9.04 years. The prevalence of MASLD, MetALD, and ALD with MD was 33.11%, 3.93%, and 1.00%, respectively. Relative to the “no SLD” group, multivariable analysis identified that MASLD (adjusted hazard ratio [aHR], 1.28; 95% confidence interval [CI], 1.26 to 1.31), MetALD (aHR, 1.38; 95% CI, 1.32 to 1.44), and ALD with MD group (aHR, 1.80; 95% CI, 1.68 to 1.93) have a significantly higher risk of all-cause mortality. Furthermore, MASLD, MetALD, ALD with MD groups showed higher liver-, cancer- and HCC-related mortality than “no SLD” group. While all-cause specific mortalities increase from MASLD to MetALD to ALD with MD, the MetALD group shows a lower risk of CV-related mortality compared to MASLD. However, ALD with MD group still have a higher risk of CV-related mortality compared to MASLD. Conclusion SLD is associated with an increased risk of all-cause, liver-, cancer-, HCC-, and CV-related mortalities.

Background: The mortality of sepsis without direct drugs is high. The association between prediabetes, based on a single fasting glucose (FG), or long-term type 2 diabetes mellitus (T2DM) and sepsis remains unclear. Methods: Of the adults aged ≥20 years who were included in the National Health Screening Program (NHSP) in 2009, 40% were randomly sampled. After excluding patients with type 1 diabetes mellitus, with missing information, and who were diagnosed with sepsis during the wash-out (between 2001 and the NHSP) or 1-year lag period, a cohort comprised of 3,863,323 examinees. Body mass index (BMI) measurements, FG tests, and self-reported questionnaires on health-related behaviors were conducted. Individual information was followed up until 2020 and censored upon the first occurrence of sepsis or death. The incidence of sepsis was compared using a multivariable regression adjusted for age, sex, income, BMI, smoking, drinking, physical activity levels, and chronic diseases. Results: The cohort was divided into those with normal FG (n=2,675,476), impaired fasting glucose (IFG) (n=890,402, 23.0%), T2DM <5 years (n=212,391, 5.5%), or T2DM for ≥5 years (n=85,054, 2.2%). The groups with IFG (adjusted hazard ratio [aHR], 1.03; 95% confidence interval [CI], 1.01 to 1.05), T2DM <5 years (aHR, 1.43; 95% CI, 1.40 to 1.47), and T2DM for ≥5 years (aHR, 1.82; 95% CI, 1.77 to 1.87) exhibited significantly higher incidence of sepsis (P<0.001), with the greatest risk in patients with T2DM aged <40 years (aHR, 1.96; 95% CI, 1.71 to 2.25). Conclusion Patients with long-standing and young-onset T2DM show a substantially high risk of sepsis, emphasizing the need for infection prevention and vaccination.

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: The associations between thyroid cancer and skeletal outcomes have not been thoroughly investigated. We aimed to investigate the risk of osteoporotic fractures in patients with thyroid cancer compared to that in a matched control group. Methods: This retrospective cohort study included 2,514 patients with thyroid cancer and 75,420 matched controls from the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC, 2006–2019). The rates of osteoporotic fractures were analyzed, and associations with the levothyroxine dose were evaluated. Results: Patients with thyroid cancer had a significantly lower risk of fracture than did the control group (hazard ratio [HR], 0.81; 95% confidence interval [CI], 0.69 to 0.94; P=0.006). Patients diagnosed with thyroid cancer after the age of 50 years (older cancer group) had a significantly lower risk of fracture than did those in the control group (HR, 0.72; 95% CI, 0.6 to 0.85; P<0.001), especially those diagnosed with spinal fractures (HR, 0.66; 95% CI, 0.51 to 0.85; P=0.001). Patients in the older cancer group started osteoporosis treatment earlier than did those in the control group (65.5±7.5 years vs. 67.3±7.6 years, P<0.001). Additionally, a lower dose of levothyroxine was associated with a reduced risk of fractures. Conclusion In the clinical setting, the risk of fracture in women diagnosed with thyroid cancer after the age of 50 years was lower than that in the control group, which was caused by more proactive osteoporosis treatment in postmenopausal women with thyroid cancer.

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.

Background: Recombinant human follicle-stimulating hormone (rhFSH) is commonly used to treat female infertility, but its short half-life necessitates multiple doses. Even corifollitropin alfa, with an extended half-life, requires supplementary injections of rhFSH after 7 days. This study aimed to develop and evaluate a long-acting follicle-stimulating hormone (FSH) formulation using anti-serum albumin Fab-associated (SAFA) technology to avoid additional injections and enhance ovarian function. Methods: SAFA-FSH was synthesized using a Chinese hamster ovary expression system. Its biological efficacy was confirmed through assays measuring its ability to stimulate cyclic adenosine monophosphate (cAMP) production, estradiol synthesis, and the expression of human cytochrome P450 family 19 subfamily A member 1 (hCYP19α1) and human steroidogenic acute regulatory protein (hSTAR) in human ovarian granulosa (KGN) cells. To evaluate the effects of SAFA-FSH, we compared its impact on serum estradiol levels and ovarian weight increase with that of rhFSH in Sprague-Dawley (SD) rats using the modified Steelman-Pohley test. Results: The results indicated that SAFA-FSH induces cAMP synthesis in KGN cells and upregulates the expression of hCYP19α1 and hSTAR in a dose-dependent manner. Female SD rats, aged 21 days, receiving daily subcutaneous human chorionic gonadotropin injections for 5 days exhibited a significant increase in serum estradiol levels and ovarian weight when administered SAFA-FSH on the first day or when given nine injections of rhFSH over 5 days. Notably, the group receiving SAFA-FSH on the first and third days demonstrated an even greater rise in serum estradiol levels and ovarian weight. Conclusion These findings suggest that SAFA-FSH presents a promising alternative to current rhFSH treatments for female infertility. However, further research is essential to thoroughly assess its safety and efficacy in clinical contexts.

Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.