Background: High tibial osteotomy (HTO) is often performed to postpone or avoid the need for subsequent total knee arthroplasty (TKA). We designed the present study to investigate the incidence rate and risk factors for subsequent revision in patients treated with HTO compared with those managed with TKA. Methods: In this retrospective nationwide cohort study, we reviewed the South Korean National Health Insurance claims database from January 1, 2009, to August 31, 2017. We evaluated patients ≥41 years old who had undergone TKA or HTO as the primary surgical procedure without a history of having undergone either procedure during the preceding 2 years. By including only new interventions without such prior surgery, we could eliminate the influence of previous TKA and HTO treatments. Multivariable logistic regression models were used to compare the risk of revision between the groups after propensity score matching with inverse probability of treatment weighting (IPTW). Revision was defined as conversion to revision TKA after primary TKA and conversion to TKA after HTO. Results: After applying the IPTW, a total of 436,538 patients with TKA and 452,724 patients with HTO were identified. The risk of revision during the entire study period was higher for patients with HTO than for patients with TKA (adjusted hazard ratio [HR], 2.47). The Kaplan-Meier 8-year survival was 97.8% in the TKA group and 91.5% in the HTO group. Compared with patients with TKA, patients with HTO had an increased risk of revision in cases of advanced age (HR of 1.85 for patients who were ≥61 to 69 years old and HR of 4.17 for those who were ≥70 years old), female sex (HR, 2.90), recipients of Medical Aid program benefits (HR, 4.77), the presence of hyperlipidemia (HR, 3.70), the presence of diabetes (HR, 4.86), and the presence of osteoporosis (HR, 3.53). However, younger patients with HTO (≤60 years old) had a lower risk of subsequent revision (HR, 0.64). Conclusions: The risk of revision was higher for patients with HTO than for patients with TKA. The risk factors for subsequent revision in patients with HTO in our cohort of patients were advanced age (>60 years), female sex, receipt of Medical Aid, and the presence of comorbidities, such as diabetes, osteoporosis, and hyperlipidemia. Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Recent studies have suggested an association between obesity and dyslipidemia in the development of type 2 diabetes (T2D). The purpose of this study was to explore the causal effects of obesity and dyslipidemia on T2D risk in Asians. Two-sample Mendelian randomization (MR) analyses were performed to assess genetically predicted obesity using body mass index (BMI) and dyslipidemia using high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TCHL), and triglycerides (TG) versus T2D susceptibility using genome-wide association study (GWAS) results derived from the summary statistics of Biobank Japan (n = 179,000) and DIAbetes Meta-ANalysis of Trans-Ethnic association studies (n = 50,533). The MR analysis demonstrated evidence of a causal effect of higher BMI on the risk of T2D (odds ratio (OR) > 1.0, p < 0.05). In addition, TG showed a protective effect on the risk of T2D (ORs 0.68–0.85). However, HDL, LDL, and TCHL showed little genetic evidence supporting a causal association between dyslipidemia and T2D. We found strong genetic evidence supporting a causal association of BMI with T2D. Although HDL, LDL, and TCHL did not show a causal association with T2D, TG had a causal relationship with the decrease of T2D. Although it was predicted that TG would be linked to a higher risk of T2D, it actually exhibited a paradoxical protective effect against T2D, which requires further investigation.

Metabolic syndrome is a risk factor for type 2 diabetes and cardiovascular disease. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We also performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set. We found an association between metabolic syndrome and an intronic SNP pair, rs7107152 and rs1242229, in SIDT2 gene at 11q23.3. Both SNPs correlate with the expression of SIDT2 and TAGLN, whose products promote insulin secretion and lipid metabolism, respectively. This SNP pair showed statistical significance at the replication stage. Our findings provide insight into an underlying mechanism that contributes to metabolic syndrome.

Serum carcinoembryonic antigen (CEA) is a well-known tumor marker for colorectal adenocarcinoma. However, CEA levels can be influenced by various nonmalignant conditions. A retrospective, cross-sectional study was performed including 18,131 healthy nonsmokers who underwent health check-ups with evaluation of the serum CEA level. In the training set, multivariate analysis revealed that the log-transformed CEA level had positive relationships with age (regression coefficient (r) = 0.005, P<0.001), white blood cell (WBC) count (r=0.007, P=0.016), hemoglobin (HB, r=0.016, P<0.001), aspartate aminotransferase (AST, r=0.002, P=0.005), creatinine (r=0.076, P=0.038), and glycosylated hemoglobin (HbA1c, r=0.052, P<0.001); body mass index (BMI, r=−0.007, P<0.001) showed a negative correlation. The results for age, BMI, WBC count, HB, AST, and HbA1c were validated in the test set. We were able to construct the following model to predict the log-transformed CEA level: log (CEA + 0.51) = −0.204 − 0.051 (gender) + 0.005 (age) − 0.006 (BMI) + 0.008 (WBC count) + 0.016 (HB) + 0.002 (AST) + 0.062 (creatinine) + 0.054 (HbA1c). For colorectal cancer prediction, the model with the observed CEA and adjusted CEA levels had significantly high predictive power (AUC 0.756, P<0.001) than the model only including the observed CEA level (AUC 0.693, P<0.001). Factors influencing serum CEA levels should be adjusted before clinical interpretation to increase the predictive value of CEA.

A relationship between lung function and sarcopenia has been suggested. This study aimed to evaluate the association between lung function and abdominal skeletal muscle mass, as measured by computed tomography (CT). The clinical records of 1907 subjects (1406 males, mean age 53.1 ± 9.2 years), who underwent routine health check-ups, including spirometry and abdominal CT, were retrospectively reviewed. The CT-measured skeletal muscle index (SMI_CT, cm²/(kg/m²) was defined as the skeletal muscle area of the third lumbar vertebrae (L3) level that is normalized by the body mass index. The mean values of forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) gradually increased as the SMI_CT quartiles increased (all p for trend < 0.05). The proportions of subjects with less than 80% of the predicted FVC (%) and predicted FEV1 (%) significantly decreased as the SMI_CT quartiles increased (all p for trend < 0.05). The β regression coefficients for FVC and FEV1 significantly increased as the SMI_CT quartiles increased after adjusting for other confounding variables (p for trend < 0.05). This study showed that abdominal muscle mass, which was precisely measured by CT, independently affected lung function proportionally after adjusting for confounding factors in relatively healthy adults.

Researchers have suggested a potential relationship between gamma-glutamyl transferase (GGT) level and stroke. We investigated a potential causal relationship between GGT level as exposures and stroke and stroke subtypes (cardioembolic, small vessel, and large artery) in a European population. We performed a two-sample Mendelian randomization (MR) study using the genome-wide association study (GWAS) data from the UK Biobank as the exposure set. For the outcome set, we used stroke in the GWAS data from the GIGASTROKE Consortium. We considered alcohol consumption, atrial fibrillation, and body mass index as confounders. We used PhenoScanner searches for removal of SNPs and multivariable MR analysis for assessing confounders. We observed significant causal associations between GGT level and stroke (odds ratio [OR] = 1.23, 95% CI = [1.05–1.44], and p = 0.012 with IVW; OR = 1.19, 95% CI= [1.02–1.39], and p = 0.031 with MR-PRESSO). These results were consistent after removing SNPs related to confounding factors. Similarly, in multivariable MR, GGT was associated with stroke after adjusting for confounding factors (OR = 1.30, 95% CI 1.07–1.60), p = 0.010). Because GGT level has a causal relationship with stroke, researchers should test its significance as a potential risk factor for stroke. Additional research is required to validate these results.