Background Plasma aldosterone-to-renin ratio (ARR) is popularly used for screening primary aldosteronism (PA). Some medications, including diuretics, are known to have an effect on ARR and cause false-negative and false-positive results in PA screening. Currently, there are no studies on the effects of sodium–glucose cotransporter-2 (SGLT2) inhibitors, which are known to have diuretic effects, on ARR. We aimed to investigate the effects of SGLT2 inhibitors on ARR. Methods We employed a retrospective design; the study was conducted from April 2016 to December 2018 and carried out in three hospitals. Forty patients with diabetes and hypertension were administered SGLT2 inhibitors. ARR was evaluated before 2 to 6 months after the administration of SGLT2 inhibitors to determine their effects on ARR. Results No significant changes in the levels of ARR (90.9 ± 51.6 vs. 81.4 ± 62.9) were found. Body mass index, diastolic blood pressure, heart rate, fasting plasma glucose, and hemoglobin A1c were significantly decreased by SGLT2 inhibitors. Serum creatinine was significantly increased. Conclusion SGLT2 inhibitor administration yielded minimal effects on ARR and did not increase false-negative results in PA screening in patients with diabetes and hypertension more than 2 months after administration.

Salt intake is one of the most important environmental factors impacting hypertension onset. Meanwhile, the potential roles of the gut microbiome (GM) in altering the health status of hosts have drawn considerable attention. Here, we aimed to perform an observational study to investigate the impact of intestinal bacterial flora in hypertensive patients with low-salt or high-salt intake. A total of 239 participants were enrolled, and their gut microbiomes, clinical and demographic details, as well as physiological parameters pertaining to the renin-angiotensin-aldosterone system and inflammatory cytokine profiles, were examined. The participants were classified into four groups based on the presence of different enterotype bacteria, as determined via cluster analysis, and salt intake: low salt/GM enterotype 1, low salt/GM enterotype 2, high salt/GM enterotype 1, and high salt/GM enterotype 2. Results show that the prevalence of hypertension was significantly lower in the low-salt/GM enterotype 2 group (27%) compared to the low salt/GM enterotype 1 group (47%; p = 0.04). Alternatively, no significant differences were observed in hypertension prevalence between the two high-salt intake groups (GM enterotype 1 = 50%, GM enterotype 2 = 47%; p = 0.83). Furthermore, The low-salt/GM enterotype 2 was higher in the relative abundances of Blautia, Bifidobacterium, Escherichia-Shigella, Lachnoclostridium , and Clostridium sensu stricto than the low-salt/GM enterotype 1. differed significantly between the GM enterotypes. These results suggested that consumption of a low-salt diet was ineffective in regulating hypertension in individuals with a specific gut bacteria composition. Our findings support the restoration of GM homeostasis as a new strategy for controlling blood pressure and preventing the development of hypertension.

Diabetes mellitus (DM) is a chronic disorder, characterized by impaired glucose metabolism. It is linked to increased risks of several diseases such as atrial fibrillation, cancer, and cardiovascular diseases. Therefore, DM prevention is essential. However, the traditional regression-based DM-onset prediction methods are incapable of investigating future DM for generally healthy individuals without DM. Employing gradient-boosting decision trees, we developed a machine learning-based prediction model to identify the DM signatures, prior to the onset of DM. We employed the nationwide annual specific health checkup records, collected during the years 2008 to 2018, from Kanazawa city, Ishikawa, Japan. The data included the physical examinations, blood and urine tests, and participant questionnaires. Individuals without DM (at baseline), who underwent more than two annual health checkups during the said period, were included. The new cases of DM onset were recorded when the participants were diagnosed with DM in the annual check-ups. The dataset was divided into three subsets in a 6:2:2 ratio to constitute the training, tuning (internal validation), and testing datasets. Employing the testing dataset, the ability of our trained prediction model to calculate the area under the curve (AUC), precision, recall, F1 score, and overall accuracy was evaluated. Using a 1,000-iteration bootstrap method, every performance test resulted in a two-sided 95% confidence interval (CI). We included 509,153 annual health checkup records of 139,225 participants. Among them, 65,505 participants without DM were included, which constituted36,303 participants in the training dataset and 13,101 participants in each of the tuning and testing datasets. We identified a total of 4,696 new DM-onset patients (7.2%) in the study period. Our trained model predicted the future incidence of DM with the AUC, precision, recall, F1 score, and overall accuracy of 0.71 (0.69-0.72 with 95% CI), 75.3% (71.6-78.8), 42.2% (39.3-45.2), 54.1% (51.2-56.7), and 94.9% (94.5-95.2), respectively. In conclusion, the machine learning-based prediction model satisfactorily identified the DM onset prior to the actual incidence.

Objective Primary aldosteronism (PA) is a major cause of secondary hypertension. The association between PA and other hormone disorders is unclear. The present study aimed to evaluate whether the parathyroid hormone (PTH) value is associated with PA subtypes or specific treatments. Methods We enrolled 135 patients with PA who had their PTH value measured before undergoing a specific treatment. We evaluated whether PTH value is associated with PA subtypes or with specific treatments. The present study is a single-center retrospective study (2011-2018). Results Our study showed that, among the patients with PA, the proportion of those with PTH elevation was >30%. The PTH value was significantly correlated with both the basal plasma aldosterone concentration (PAC) and PAC after a captopril challenge test. However, the PTH value was not significantly different between the patients with unilateral and bilateral PA. We observed that the serum PTH value decreased after treatment of PA with unilateral adrenalectomy or mineralocorticoid receptor antagonists. Conclusion Our findings suggest that the PTH value in PA patients might be associated with the autonomous production of aldosterone. However, there was no correlation between the PTH value and PA subtypes in our study. Additionally, our study showed that targeted treatment for PA may lead to a decrease in the serum PTH levels. Hence, the PTH value could potentially be used as an index for measuring the suitability for PA treatment.

No abstract