Background Statin treatment increases the risk of new-onset diabetes mellitus (NODM); however, data directly comparing the risk of NODM among individual statins is limited. We compared the risk of NODM between patients using pitavastatin and atorvastatin or rosuvastatin using reliable, large-scale data. Methods Data of electronic health records from ten hospitals converted to the Observational Medical Outcomes Partnership Common Data Model (n = 14,605,368 patients) were used to identify new users of pitavastatin, atorvastatin, or rosuvastatin (atorvastatin + rosuvastatin) for ≥ 180 days without a previous history of diabetes or HbA1c level ≥ 5.7%. We conducted a cohort study using Cox regression analysis to examine the hazard ratio (HR) of NODM after propensity score matching (PSM) and then performed an aggregate meta-analysis of the HR. Results After 1:2 PSM, 10,238 new pitavastatin users (15,998 person-years of follow-up) and 18,605 atorvastatin + rosuvastatin users (33,477 person-years of follow-up) were pooled from 10 databases. The meta-analysis of the HRs demonstrated that pitavastatin resulted in a significantly reduced risk of NODM than atorvastatin + rosuvastatin (HR 0.72; 95% CI 0.59–0.87). In sub-analysis, pitavastatin was associated with a lower risk of NODM than atorvastatin or rosuvastatin after 1:1 PSM (HR 0.69; CI 0.54–0.88 and HR 0.74; CI 0.55–0.99, respectively). A consistently low risk of NODM in pitavastatin users was observed when compared with low-to-moderate-intensity atorvastatin + rosuvastatin users (HR 0.78; CI 0.62–0.98). Conclusions In this retrospective, multicenter active-comparator, new-user, cohort study, pitavastatin reduced the risk of NODM compared with atorvastatin or rosuvastatin.

Background Acute kidney injury (AKI) is defined as a sudden event of kidney failure or kidney damage within a short period. Ischemia-reperfusion injury (IRI) is a critical factor associated with severe AKI and end-stage kidney disease (ESKD). However, the biological mechanisms underlying ischemia and reperfusion are incompletely understood, owing to the complexity of these pathophysiological processes. We aimed to investigate the key biological pathways individually affected by ischemia and reperfusion at the transcriptome level. Results We analyzed the steady-state gene expression pattern of human kidney tissues from normal (pre-ischemia), ischemia, and reperfusion conditions using RNA-sequencing. Conventional differential expression and self-organizing map (SOM) clustering analyses followed by pathway analysis were performed. Differential expression analysis revealed the metabolic pathways dysregulated in ischemia. Cellular assembly, development and migration, and immune response-related pathways were dysregulated in reperfusion. SOM clustering analysis highlighted the ischemia-mediated significant dysregulation in metabolism, apoptosis, and fibrosis-related pathways, while cell growth, migration, and immune response-related pathways were highly dysregulated by reperfusion after ischemia. The expression of pro-apoptotic genes and death receptors was downregulated during ischemia, indicating the existence of a protective mechanism against ischemic injury. Reperfusion induced alterations in the expression of the genes associated with immune response such as inflammasome and antigen representing genes. Further, the genes related to cell growth and migration, such as AKT, KRAS, and those related to Rho signaling, were downregulated, suggestive of injury responses during reperfusion. Semaphorin 4D and plexin B1 levels were also downregulated. Conclusions We show that specific biological pathways were distinctively involved in ischemia and reperfusion during IRI, indicating that condition-specific therapeutic strategies may be imperative to prevent severe kidney damage after IRI in the clinical setting.

Purpose: This study analyzed the effects of anti-hormonal treatment (HTx) on bone health using real-world evidence and machine-learning analysis.Methods: We extracted 20 clinical variables and patient history of HTx by reviewing the records of 244 patients treated for breast cancer between January 2014 and June 2018 at Pusan National University Hospital. Baseline and first follow-up dual-energy absorptiometry were analyzed. To identify which of the 20 clinical variables were highly associated with the patients’ bone mineral density and trabecular bone score (TBS), we applied partial least squares discriminant analysis (PLS-DA) and MetaboAnalyst. A self-organizing map (SOM) was used to sort the patient groups based on the selected variables.Results: The patients were classified as ‘no change’ (n=161, 70.6%), ‘deteriorated’ (n=43, 18.9%), or ‘improved’ (n=24, 10.5%) according to the change in TBS during the follow-up period. The baseline TBS value was significantly lower in the improved group. The top five variables (age, HTx, duration of vitamin D and/or calcium intake, cancer stage, and body mass index) were selected using PLS-DA, which generated variable importance value (VIP) scores for all variables and high VIP scores contributed greatly to patient classification. To identify the patients’ clinical patterns using the top five selected variables, a 3×4 grid structure SOM was generated. Clusters were selected to represent the most improved, no change, and most deteriorated groups.Conclusion: This study evaluated the clinical association between HTx and bone health in patients with breast cancer under various clinical conditions and found that the characteristics of patients included in the study were too heterogeneous to be classified in clusters. Therefore, additional data should be collected for future research.